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tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py

Summary

Maintainability
F
1 mo
Test Coverage

File rnn_cell_test.py has 2912 lines of code (exceeds 250 allowed). Consider refactoring.
Open

# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
Severity: Major
Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 1 wk to fix

    LSTMTest has 25 functions (exceeds 20 allowed). Consider refactoring.
    Open

    class LSTMTest(test.TestCase):
    
      def setUp(self):
        self._seed = 23489
        np.random.seed(self._seed)
    Severity: Minor
    Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 2 hrs to fix

      Function _testDynamicEquivalentToStaticRNN has a Cognitive Complexity of 18 (exceeds 5 allowed). Consider refactoring.
      Open

        def _testDynamicEquivalentToStaticRNN(self, use_sequence_length):
          time_steps = 8
          num_units = 3
          num_proj = 4
          input_size = 5
      Severity: Minor
      Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 2 hrs to fix

      Cognitive Complexity

      Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

      A method's cognitive complexity is based on a few simple rules:

      • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
      • Code is considered more complex for each "break in the linear flow of the code"
      • Code is considered more complex when "flow breaking structures are nested"

      Further reading

      RNNCellTest has 22 functions (exceeds 20 allowed). Consider refactoring.
      Open

      class RNNCellTest(test.TestCase, parameterized.TestCase):
      
        @test_util.run_v1_only("b/124229375")
        def testBasicRNNCell(self):
          with self.cached_session() as sess:
      Severity: Minor
      Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 2 hrs to fix

        Function _testDropoutWrapper has 6 arguments (exceeds 4 allowed). Consider refactoring.
        Open

          def _testDropoutWrapper(self,
        Severity: Minor
        Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 45 mins to fix

          Function _testBidirectionalDynamicRNN has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.
          Open

            def _testBidirectionalDynamicRNN(self, use_shape, use_state_tuple,
                                             use_time_major, use_sequence_length):
              with self.session(graph=ops.Graph()) as sess:
                input_value, inputs, outputs, state_fw, state_bw, sequence_length = (
                    self._createBidirectionalDynamicRNN(
          Severity: Minor
          Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 45 mins to fix

          Cognitive Complexity

          Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

          A method's cognitive complexity is based on a few simple rules:

          • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
          • Code is considered more complex for each "break in the linear flow of the code"
          • Code is considered more complex when "flow breaking structures are nested"

          Further reading

          Function _testRawRNN has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.
          Open

            def _testRawRNN(self, max_time):
              with self.session(graph=ops.Graph()) as sess:
                batch_size = 16
                input_depth = 4
                num_units = 3
          Severity: Minor
          Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 45 mins to fix

          Cognitive Complexity

          Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

          A method's cognitive complexity is based on a few simple rules:

          • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
          • Code is considered more complex for each "break in the linear flow of the code"
          • Code is considered more complex when "flow breaking structures are nested"

          Further reading

          Function testDynamicRNNWithNestedTupleStates has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.
          Open

            def testDynamicRNNWithNestedTupleStates(self):
              num_units = 3
              input_size = 5
              batch_size = 2
              num_proj = 4
          Severity: Minor
          Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 45 mins to fix

          Cognitive Complexity

          Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

          A method's cognitive complexity is based on a few simple rules:

          • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
          • Code is considered more complex for each "break in the linear flow of the code"
          • Code is considered more complex when "flow breaking structures are nested"

          Further reading

          Function _createBidirectionalDynamicRNN has 5 arguments (exceeds 4 allowed). Consider refactoring.
          Open

            def _createBidirectionalDynamicRNN(self,
          Severity: Minor
          Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 35 mins to fix

            Function testDynamicRNNWithTupleStates has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.
            Open

              def testDynamicRNNWithTupleStates(self):
                num_units = 3
                input_size = 5
                batch_size = 2
                num_proj = 4
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py - About 25 mins to fix

            Cognitive Complexity

            Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

            A method's cognitive complexity is based on a few simple rules:

            • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
            • Code is considered more complex for each "break in the linear flow of the code"
            • Code is considered more complex when "flow breaking structures are nested"

            Further reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  if in_graph_mode:
            
                    # Generate gradients of sum of outputs w.r.t. inputs
                    dynamic_gradients = gradients_impl.gradients(
                        split_outputs_dynamic + [state_dynamic], [concat_inputs])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 2 days to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1178..1211

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 255.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  if in_graph_mode:
                    # Generate gradients of sum of outputs w.r.t. inputs
                    static_gradients = gradients_impl.gradients(
                        outputs_static + [state_static], [concat_inputs])
                    # Generate gradients of individual outputs w.r.t. inputs
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 2 days to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1244..1287

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 255.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

              def _testScope(self, factory, prefix="prefix", use_outer_scope=True):
                with self.session(graph=ops.Graph()):
                  if use_outer_scope:
                    with variable_scope.variable_scope(prefix) as scope:
                      factory(scope)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 day to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2441..2459

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 173.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

              def _testScope(self, factory, prefix="prefix", use_outer_scope=True):
                with self.session(graph=ops.Graph()):
                  if use_outer_scope:
                    with variable_scope.variable_scope(prefix) as scope:
                      factory(scope)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 day to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2148..2166

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 173.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

              def _testScope(self, factory, prefix="prefix", use_outer_scope=True):
                with self.session(graph=ops.Graph()):
                  if use_outer_scope:
                    with variable_scope.variable_scope(prefix) as scope:
                      factory(scope)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 day to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1721..1742

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 173.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

              def _testScope(self, factory, prefix="prefix", use_outer_scope=True):
                # REMARKS: factory(scope) is a function accepting a scope
                #          as an argument, such scope can be None, a string
                #          or a VariableScope instance.
                with self.session(graph=ops.Graph()):
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 day to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 325..343

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 173.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  def loop_fn(time_, cell_output, cell_state, unused_loop_state):
                    emit_output = cell_output  # == None for time == 0
                    if cell_output is None:  # time == 0
                      next_state = cell.zero_state(batch_size, dtypes.float32)
                    else:
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 7 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2479..2493

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 117.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  def loop_fn(time_, cell_output, cell_state, unused_loop_state):
                    emit_output = cell_output  # == None for time == 0
                    if cell_output is None:  # time == 0
                      next_state = cell.zero_state(batch_size, dtypes.float32)
                    else:
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 7 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2216..2229

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 117.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

              def _retrieve_cpu_gpu_stats(self, run_metadata):
                cpu_stats = None
                gpu_stats = None
                step_stats = run_metadata.step_stats
                for ds in step_stats.dev_stats:
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 5 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3027..3036

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 96.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

              def _retrieve_cpu_gpu_stats(self, run_metadata):
                cpu_stats = None
                gpu_stats = None
                step_stats = run_metadata.step_stats
                for ds in step_stats.dev_stats:
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 5 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2568..2577

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 96.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  with variable_scope.variable_scope("root") as scope:
                    outputs_static, state_static = rnn.static_rnn(
                        cell,
                        inputs,
                        dtype=dtypes.float32,
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 4 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1076..1087

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 76.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  with variable_scope.variable_scope("root") as scope:
                    outputs_static, state_static = rnn.static_rnn(
                        cell,
                        inputs,
                        dtype=dtypes.float32,
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 4 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 979..990

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 76.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  if in_graph_mode:
                    inputs = max_length * [
                        array_ops.placeholder(dtypes.float32, shape=(None, input_size))
                    ]
                  else:
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1043..1050

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 69.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  if in_graph_mode:
                    inputs = max_length * [
                        array_ops.placeholder(dtypes.float32, shape=(None, input_size))
                    ]
                  else:
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 963..970

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 69.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 3 locations. Consider refactoring.
            Open

                def _assert_in(op_str, in_stats, out_stats):
                  self.assertTrue(any(op_str in s.node_name for s in in_stats))
                  self.assertFalse(any(op_str in s.node_name for s in out_stats))
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 2 other locations - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2612..2614
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2628..2630

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 66.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 3 locations. Consider refactoring.
            Open

                def _assert_in(op_str, in_stats, out_stats):
                  self.assertTrue(any(op_str in s.node_name for s in in_stats))
                  self.assertFalse(any(op_str in s.node_name for s in out_stats))
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 2 other locations - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2589..2591
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2628..2630

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 66.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 3 locations. Consider refactoring.
            Open

                def _assert_in(op_str, in_stats, out_stats):
                  self.assertTrue(any(op_str in s.node_name for s in in_stats))
                  self.assertFalse(any(op_str in s.node_name for s in out_stats))
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 2 other locations - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2589..2591
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2612..2614

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 66.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                      self.assertTrue(
                          float(np.linalg.norm((res[1][0, :] - res[1][i, :]))) > 1e-6)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2921..2922

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 63.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                      self.assertTrue(
                          float(np.linalg.norm((res[0][0, :] - res[0][i, :]))) > 1e-6)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2923..2924

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 63.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    self.assertAllClose(out[i][1][0:3], out[8 - 1 - i][1][3:6])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1581..1581

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 62.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    self.assertAllClose(out[i][0][0:3], out[8 - 1 - i][0][3:6])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 3 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1582..1582

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 62.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

            class Plus1RNNCell(rnn_cell.RNNCell):
              """RNN Cell generating (output, new_state) = (input + 1, state + 1)."""
            
              @property
              def output_size(self):
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 2 hrs to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_test.py on lines 48..60

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 60.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[1][1][0], out[1][1][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[0][1][2], out[2][1][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[2][1][0], out[0][1][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[2][1][1], out[0][1][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[0][0][0], out[1][0][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[0][0][0], out[1][0][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[0][0][1], out[1][0][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[0][1][0], out[2][1][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[1][1][1], out[1][1][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[1][1][1], out[1][1][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[1][1][0], out[1][1][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[2][1][2], out[0][1][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[0][0][2], out[1][0][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[0][1][1], out[2][1][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[2][1][1], out[0][1][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[1][0][2], out[0][0][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[1][0][1], out[0][0][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[1][0][0], out[0][0][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[0][1][0], out[2][1][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[1][1][2], out[1][1][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[0][1][1], out[2][1][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[2][1][2], out[0][1][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[0][0][1], out[1][0][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[2][1][0], out[0][1][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[0][0][2], out[1][0][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[1][0][1], out[0][0][4])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[1][0][0], out[0][0][3])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                  self.assertAllClose(out[1][1][2], out[1][1][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[1][0][2], out[0][0][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1691..1691
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 30 locations. Consider refactoring.
            Open

                    self.assertEqual(out[0][1][2], out[2][1][5])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 29 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1536..1536
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1537..1537
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1538..1538
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1540..1540
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1541..1541
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1542..1542
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1546..1546
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1547..1547
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1548..1548
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1550..1550
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1551..1551
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1552..1552
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1554..1554
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1555..1555
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1556..1556
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1679..1679
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1680..1680
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1681..1681
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1683..1683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1684..1684
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1685..1685
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1689..1689
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1690..1690
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1693..1693
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1694..1694
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1695..1695
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1697..1697
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1698..1698
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1699..1699

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  for i, (a, b) in enumerate(
                      zip(static_individual_var_grad_values,
                          dynamic_individual_var_grad_values)):
                    tf_logging.info(
                        "Comparing individual variable gradients iteration %d" % i)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1313..1316

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    self.assertEqual(test_zero[i][1].get_shape()[1], cell.state_size[i][1])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1073..1073

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    self.assertEqual(test_zero[i][0].get_shape()[1], cell.state_size[i][0])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1074..1074

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  for i, (a, b) in enumerate(
                      zip(static_individual_grad_values, dynamic_individual_grad_values)):
                    tf_logging.info("Comparing individual gradients iteration %d" % i)
                    self.assertAllClose(a, b)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1318..1323

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 46.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                for time_step in output_mask:
                  # Ensure the same dropout output pattern for all time steps
                  self.assertAllClose(output_mask[0], time_step)
                  for batch_entry in time_step:
                    # Assert all batch entries get the same mask
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3492..3497

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 44.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                for time_step in output_mask:
                  # Ensure the same dropout output pattern for all time steps
                  self.assertAllClose(output_mask[0], time_step)
                  for batch_entry in time_step:
                    # Assert all batch entries get the same mask
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3446..3451

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 44.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 3 locations. Consider refactoring.
            Open

                    res = sess.run([g], {
                        x: np.array([[1., 1.]]),
                        m: np.array([[0.1, 0.1]])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 2 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2653..2655
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2696..2698

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 42.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 3 locations. Consider refactoring.
            Open

                    res = sess.run([g], {
                        x: np.array([[1., 1.]]),
                        m: np.array([[0.1, 0.1]])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 2 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2653..2655
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2681..2683

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 42.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 3 locations. Consider refactoring.
            Open

                    res = sess.run([g], {
                        x: np.array([[1., 1.]]),
                        m: np.array([[0.1, 0.1]])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 2 other locations - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2681..2683
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2696..2698

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 42.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  self.evaluate(
                      gen_rnn_ops.BlockLSTM(
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/keras/legacy_tf_layers/variable_scope_shim.py on lines 326..326

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 42.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    self.assertEqual([
                        "root/basic_rnn_cell/%s:0" % rnn_cell_impl._WEIGHTS_VARIABLE_NAME,
                        "root/basic_rnn_cell/%s:0" % rnn_cell_impl._BIAS_VARIABLE_NAME
                    ], [v.name for v in cell.trainable_variables])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2676..2679

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 41.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    self.assertEqual([
                        "root/basic_rnn_cell/%s:0" % rnn_cell_impl._WEIGHTS_VARIABLE_NAME,
                        "root/basic_rnn_cell/%s:0" % rnn_cell_impl._BIAS_VARIABLE_NAME
                    ], [v.name for v in cell.non_trainable_variables])
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2647..2650

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 41.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                res1 = self._testDropoutWrapper(
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3466..3466

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 40.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                res0 = self._testDropoutWrapper(
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3479..3479

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 40.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  single_input_using_dim = (array_ops.placeholder(
                      dtypes.float32, shape=(batch_size, input_size)),
                                            array_ops.placeholder(
                                                dtypes.float32,
                                                shape=(batch_size, input_size)))
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1905..1908

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 38.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  single_input = (array_ops.placeholder(
                      dtypes.float32, shape=(None, input_size)),
                                  array_ops.placeholder(
                                      dtypes.float32, shape=(None, input_size)))
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 1 hr to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1912..1916

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 38.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  if in_graph_mode:
                    concat_inputs = array_ops.placeholder(
                        dtypes.float32, shape=(time_steps, batch_size, input_size))
                  else:
                    concat_inputs = constant_op.constant(input_values)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 55 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1216..1220

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 37.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  if in_graph_mode:
                    concat_inputs = array_ops.placeholder(
                        dtypes.float32, shape=(time_steps, batch_size, input_size))
                  else:
                    concat_inputs = constant_op.constant(input_values)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 55 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1156..1160

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 37.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  self._testBidirectionalDynamicRNN(
                      use_shape=option[0],
                      use_state_tuple=option[1],
                      use_time_major=option[2],
                      use_sequence_length=option[3])
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 55 mins to fix
            tensorflow/python/kernel_tests/image_ops/decode_jpeg_op_test.py on lines 98..103

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 37.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                      cell = rnn_cell_impl.MultiRNNCell(
                          [
                              rnn_cell_impl.BasicLSTMCell(2, state_is_tuple=False)
                              for _ in range(2)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 55 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2864..2867

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 37.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    cell = rnn_cell_impl.MultiRNNCell(
                        [
                            rnn_cell_impl.BasicLSTMCell(2, state_is_tuple=False)
                            for _ in range(2)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 55 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2725..2728

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 37.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 4 locations. Consider refactoring.
            Open

              @test_util.run_v1_only("b/124229375")
              def testBidirectionalRNNWithoutSequenceLength(self):
                self._testBidirectionalRNNWithoutSequenceLength(use_shape=False)
                self._testBidirectionalRNNWithoutSequenceLength(use_shape=True)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 3 other locations - About 50 mins to fix
            tensorflow/python/kernel_tests/data_structures/stack_ops_test.py on lines 96..99
            tensorflow/python/kernel_tests/data_structures/stack_ops_test.py on lines 249..252
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1587..1590

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 36.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 4 locations. Consider refactoring.
            Open

              @test_util.run_v1_only("b/124229375")
              def testBidirectionalRNN(self):
                self._testBidirectionalRNN(use_shape=False)
                self._testBidirectionalRNN(use_shape=True)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 3 other locations - About 50 mins to fix
            tensorflow/python/kernel_tests/data_structures/stack_ops_test.py on lines 96..99
            tensorflow/python/kernel_tests/data_structures/stack_ops_test.py on lines 249..252
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1592..1595

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 36.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  with variable_scope.variable_scope("share_scope", reuse=True):
                    outputs1, _ = rnn.static_rnn(cell, inputs, dtype=dtypes.float32)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 45 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 928..930

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 35.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  with ops.name_scope("scope1"):
                    with variable_scope.variable_scope("share_scope", reuse=True):
                      outputs1, _ = rnn.static_rnn(cell, inputs, dtype=dtypes.float32)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 45 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 884..885

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 35.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                if use_time_major:
                  outputs_shape[0], outputs_shape[1] = outputs_shape[1], outputs_shape[0]
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 45 mins to fix
            tensorflow/python/kernel_tests/linalg/linear_operator_adjoint_test.py on lines 269..270

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 35.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                with variable_scope.variable_scope("drop_scope"):
                  dynamic_outputs, dynamic_state = rnn.static_rnn(
                      cell, inputs, sequence_length=sequence_length, dtype=dtypes.float32)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 40 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1174..1176

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 34.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                res = self._testDropoutWrapper(
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 40 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3417..3417

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 34.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  with variable_scope.variable_scope("dynamic_scope"):
                    outputs_static, state_static = rnn.static_rnn(
                        cell, inputs, sequence_length=sequence_length, dtype=dtypes.float32)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 40 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 285..287

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 34.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    _, ml = rnn_cell_impl.MultiRNNCell(
                        [rnn_cell_impl.GRUCell(2) for _ in range(2)],
                        state_is_tuple=True)(x, m_good)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 40 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3097..3099

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 34.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                      rnn_cell_impl.MultiRNNCell(
                          [rnn_cell_impl.GRUCell(2) for _ in range(2)],
                          state_is_tuple=True)(x, m_bad)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 40 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3101..3103

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 34.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                res = self._testDropoutWrapper(
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 40 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3434..3434

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 34.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  values = sess.run(outputs + [state], feed_dict={inputs[0]: input_value})
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 35 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 264..264

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 33.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  values = sess.run(outputs + [state], feed_dict={inputs[0]: input_value})
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 35 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 228..228

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 33.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    cell = rnn_cell_impl.MultiRNNCell(
                        [rnn_cell_impl.BasicLSTMCell(2) for _ in range(2)],
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 35 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3071..3072

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 33.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  inputs = max_length * [
                      array_ops.placeholder(dtypes.float32, shape=(None,) + input_size)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 35 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1795..1797

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 33.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  inputs_using_dim = max_length * [
                      array_ops.placeholder(
                          dtypes.float32, shape=(batch_size,) + input_size)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 35 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1792..1793

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 33.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                    multi_rnn_cell = rnn_cell_impl.MultiRNNCell(
                        [rnn_cell_impl.GRUCell(2) for _ in range(2)],
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 35 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 2832..2833

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 33.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 6 locations. Consider refactoring.
            Open

                  x = constant_op.constant(
                      [[[2., 2., 2.]], [[1., 1., 1.]]], dtype=dtypes.float32)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 5 other locations - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3300..3302
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3315..3317
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3362..3364
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3383..3385
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3398..3400

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 6 locations. Consider refactoring.
            Open

                true_full_output = np.array(
                    [[[0.751109, 0.751109, 0.751109]], [[0.895509, 0.895509, 0.895509]]],
                    dtype=np.float32)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 5 other locations - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3247..3248
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3300..3302
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3362..3364
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3383..3385
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3398..3400

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 6 locations. Consider refactoring.
            Open

                true_full_output = np.array(
                    [[[0.751109, 0.751109, 0.751109]], [[0.895509, 0.895509, 0.895509]]],
                    dtype=np.float32)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 5 other locations - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3247..3248
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3315..3317
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3362..3364
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3383..3385
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3398..3400

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 6 locations. Consider refactoring.
            Open

                true_full_output = np.array(
                    [[[0.751109, 0.751109, 0.751109]], [[0.895509, 0.895509, 0.895509]]],
                    dtype=np.float32)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 5 other locations - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3247..3248
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3300..3302
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3315..3317
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3383..3385
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3398..3400

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 6 locations. Consider refactoring.
            Open

                true_full_output = np.array(
                    [[[0.751109, 0.751109, 0.751109]], [[0.895509, 0.895509, 0.895509]]],
                    dtype=np.float32)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 5 other locations - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3247..3248
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3300..3302
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3315..3317
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3362..3364
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3383..3385

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 6 locations. Consider refactoring.
            Open

                true_full_output = np.array(
                    [[[0.751109, 0.751109, 0.751109]], [[0.895509, 0.895509, 0.895509]]],
                    dtype=np.float32)
            Severity: Major
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 5 other locations - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3247..3248
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3300..3302
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3315..3317
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3362..3364
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 3398..3400

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  for i in range(4):
                    self.assertEqual(len(cell.state_size[i]), 2)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 540..541

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Identical blocks of code found in 2 locations. Consider refactoring.
            Open

                  for i in range(4):
                    self.assertEqual(len(cell.state_size[i]), 2)
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 1067..1068

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  dynamic_state_value = sess.run(
                      [dynamic_state],
                      feed_dict={
                          inputs[0]: input_value,
                          sequence_length: [2, 3]
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 847..850

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

            Similar blocks of code found in 2 locations. Consider refactoring.
            Open

                  state_value = sess.run(
                      [state], feed_dict={
                          inputs[0]: input_value,
                          sequence_length: [2, 3]
            Severity: Minor
            Found in tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py and 1 other location - About 30 mins to fix
            tensorflow/python/kernel_tests/nn_ops/rnn_cell_test.py on lines 298..302

            Duplicated Code

            Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

            Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

            When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

            Tuning

            This issue has a mass of 32.

            We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

            The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

            If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

            See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

            Refactorings

            Further Reading

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