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tensorflow/python/distribute/custom_training_loop_input_test.py

Summary

Maintainability
F
1 wk
Test Coverage

File custom_training_loop_input_test.py has 804 lines of code (exceeds 250 allowed). Consider refactoring.
Open

# Copyright 2019 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/distribute/custom_training_loop_input_test.py - About 1 day to fix

    InputIterationTest has 39 functions (exceeds 20 allowed). Consider refactoring.
    Open

    class InputIterationTest(test.TestCase, parameterized.TestCase,
                         AssertFlattenedMixin):

  @combinations.generate(
      combinations.combine(
    Severity: Minor
    Found in tensorflow/python/distribute/custom_training_loop_input_test.py - About 5 hrs to fix

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

        def testDatasetAssertWithDynamicBatch(self, distribution):
    # Regression test for github issue 33517.
    def step_fn(data):
      assert_op = control_flow_assert.Assert(
          math_ops.less_equal(math_ops.reduce_max(data), 100.), [data])
      Severity: Minor
      Found in tensorflow/python/distribute/custom_training_loop_input_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

        @combinations.generate(
      combinations.combine(
          distribution=strategy_combinations.all_strategies,
          mode=["eager"]
      ))
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 1 day to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 218..239

      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 155.

      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

        @combinations.generate(
      combinations.combine(
          distribution=strategy_combinations.all_strategies,
          mode=["eager"]
      ))
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 1 day to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 273..294

      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 155.

      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

        @combinations.generate(
      combinations.combine(
          distribution=strategy_combinations.multidevice_strategies,
          mode=["eager"]
      ))
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 1 day to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 640..658

      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 136.

      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

        @combinations.generate(
      combinations.combine(
          distribution=strategy_combinations.multidevice_strategies,
          mode=["eager"]
      ))
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 1 day to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 587..605

      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 136.

      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

        @combinations.generate(
      combinations.combine(
          distribution=strategy_combinations.all_strategies,
          mode=["eager"]
      ))
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 1 day to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 801..822

      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 125.

      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

        @combinations.generate(
      combinations.combine(
          distribution=strategy_combinations.all_strategies,
          mode=["eager"]
      ))
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 1 day to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 845..865

      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 125.

      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

      class AssertFlattenedMixin(object):
  """Mixin for specialized asserts."""

  def assert_equal_flattened(self, expected_results, actual_results):
    """Asserts that flattened results are equal.
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 5 hrs to fix
      tensorflow/python/distribute/custom_training_loop_gradient_test.py on lines 38..58

      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 94.

      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_function.function
    def train(dataset):
      results = []
      iterator = iter(dataset)
      # we iterate through the loop 5 times since we have 3 elements and a
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 4 hrs to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 913..924

      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 78.

      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_function.function
    def train(dataset):
      results = []
      iterator = iter(dataset)
      # we iterate through the loop 2 times since we have 4 elements and a
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 4 hrs to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 348..359

      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 78.

      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 dataset_fn(_):
      data = array_ops.zeros((5, 1, 2), dtype=dtypes.int32)
      dataset = get_dataset_from_tensor_slices(data)
      dataset = dataset.batch(3)
      return dataset
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 2 hrs to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 774..778

      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 50.

      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 dataset_fn(_):
      data = array_ops.zeros((20, 300, 32), dtype=dtypes.int32)
      dataset = get_dataset_from_tensor_slices(data)
      dataset = dataset.batch(16)
      return dataset
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 2 hrs to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 694..698

      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 50.

      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 get_dataset_from_tensor_slices(inp_array):
  dataset = dataset_ops.DatasetV2.from_tensor_slices(inp_array)
  # TODO(b/138326910): Remove Dataset V1 version once bug resolved.
  if not tf2.enabled():
    dataset = dataset_ops.Dataset.from_tensor_slices(inp_array)
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 1 hr to fix
      tensorflow/python/distribute/custom_training_loop_gradient_test.py on lines 30..35

      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 47.

      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

          for x in dist_dataset:
      output = distribution.experimental_local_results(
          distribution.run(train_step, args=(x,)))
      results.append(output)
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 2 other locations - About 1 hr to fix
      tensorflow/python/distribute/custom_training_loop_gradient_test.py on lines 84..87
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 212..215

      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 3 locations. Consider refactoring.
      Open

          for x in dist_dataset:
      output = distribution.experimental_local_results(
          distribution.run(train_step, args=(x,)))
      results.append(output)
      Severity: Major
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 2 other locations - About 1 hr to fix
      tensorflow/python/distribute/custom_training_loop_gradient_test.py on lines 84..87
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 132..135

      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

          @def_function.function
    def run(iterator):
      inputs = next(iterator)
      return distribution.reduce(reduce_util.ReduceOp.MEAN, inputs, axis=0)
      Severity: Minor
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 55 mins to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 633..636

      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

          @def_function.function
    def run(iterator):
      inputs = next(iterator)
      return distribution.reduce(reduce_util.ReduceOp.MEAN, inputs, axis=0)
      Severity: Minor
      Found in tensorflow/python/distribute/custom_training_loop_input_test.py and 1 other location - About 55 mins to fix
      tensorflow/python/distribute/custom_training_loop_input_test.py on lines 616..619

      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

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