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tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py

Summary

Maintainability
F
1 mo
Test Coverage

File parse_example_dataset_test.py has 1016 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/data/experimental/kernel_tests/parse_example_dataset_test.py - About 2 days to fix

    ParseExampleDatasetTest has 23 functions (exceeds 20 allowed). Consider refactoring.
    Open

    class ParseExampleDatasetTest(test_base.DatasetTestBase,
                              parameterized.TestCase):

  def _compare_output_to_expected(self, dict_tensors, expected_tensors):
    self.assertEqual(set(dict_tensors.keys()), set(expected_tensors.keys()))
    Severity: Minor
    Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py - About 2 hrs to fix

      Function _test has a Cognitive Complexity of 10 (exceeds 5 allowed). Consider refactoring.
      Open

        def _test(self,
            input_tensor,
            feature_val,
            expected_values=None,
            expected_err=None,
      Severity: Minor
      Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py - About 1 hr 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 _test has 5 arguments (exceeds 4 allowed). Consider refactoring.
      Open

        def _test(self,
      Severity: Minor
      Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py - About 35 mins to fix

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

            original = [
        example(
            features=features({
                # rt = [[3], [4, 5, 6]]
                "rt_values": float_feature([3, 4, 5, 6]),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 days to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 1022..1061

        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 254.

        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

            test_features = {
        "rt1":
            parsing_ops.RaggedFeature(
                value_key="rt_values",
                partitions=[parsing_ops.RaggedFeature.RowSplits("rt_splits")],
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 1 day to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 1067..1105

        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 212.

        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

            original = [
        example(features=features({
            "val": float_feature([3, 4]),
            "idx0": int64_feature([5, 10]),
            "idx1": int64_feature([0, 2]),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 1 day to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 364..382
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 380..402

        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 137.

        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

            expected_output = {
        aname:
            np.array(  # pylint: disable=too-many-function-args
                [
                    [0, 0, 0, 0],
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 1 day to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 796..813

        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

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

            original = [
        # rt shape: [(batch), 2, None, None]
        example(
            features=features({
                # rt = [[[[1]], [[2, 3], [4]]], [[], [[5, 6, 7]]]]
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 1 day to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 1141..1157

        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 129.

        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 4 locations. Consider refactoring.
        Open

            original = [
        example(features=features({
            cname: int64_feature([2]),
        })),
        example(features=features({
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 3 other locations - About 7 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 753..770
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 705..719
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 772..789

        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 4 locations. Consider refactoring.
        Open

            original = [
        example(features=features({
            cname: int64_feature([2]),
        })),
        example(
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 3 other locations - About 7 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 699..713
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 705..719
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 772..789

        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 3 locations. Consider refactoring.
        Open

            original = [
        (example(features=features({
            aname: float_feature([10, 10]),
        })), example(features=features({
            aname: float_feature([1, 1]),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 7 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 461..474
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 478..494

        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 113.

        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

            original = [
        example(features=features({
            "val": float_feature([3, 4]),
            "idx": int64_feature([5, 10])
        })),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 7 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 278..294
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 285..305

        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 112.

        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(batch_size):
      col = 1
      if np.random.rand() < 0.25:
        # w.p. 25%, drop out the second entry
        expected_str[i][col] = b"default"
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 6 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 712..722

        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 105.

        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

            original = [
        example(features=features({
            "st_c": float_feature([3, 4])
        })),
        example(features=features({
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 3 other locations - About 5 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 232..244
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 242..255
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 964..977

        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 95.

        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

            input_features = {
        "st_a":
            parsing_ops.VarLenFeature(dtypes.int64),
        "a":
            parsing_ops.FixedLenFeature(
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 5 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 161..175
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 158..172

        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 88.

        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._test(
        ops.convert_to_tensor(serialized), {
            aname:
                parsing_ops.FixedLenSequenceFeature(
                    (2, 1), dtype=dtypes.float32, allow_missing=True),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 5 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 796..809

        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 88.

        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._test(
        ops.convert_to_tensor(serialized), {
            aname:
                parsing_ops.FixedLenSequenceFeature(
                    (2, 1), dtype=dtypes.float32, allow_missing=True),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 5 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 881..894

        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 88.

        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

            original = [
        example(features=features({
            "c": float_feature([3, 4]),
            "val": bytes_feature([b"a", b"b"]),
            "idx": int64_feature([0, 3])
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 4 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 593..601
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 602..613

        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 84.

        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

                ops.convert_to_tensor(serialized), {
            aname:
                parsing_ops.FixedLenSequenceFeature(
                    (2, 1),
                    dtype=dtypes.float32,
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 4 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 854..868

        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 83.

        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

            expected_st_c = sparse_tensor.SparseTensorValue(  # indices, values, shape
        np.array([[0, 0], [0, 1], [3, 0], [3, 1], [3, 2]], dtype=np.int64),
        np.array([3.0, 4.0, 1.0, 2.0, -1.0], dtype=np.float32),
        np.array([4, 3], dtype=np.int64))  # batch == 2, max_elems = 3
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 4 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 281..284

        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 79.

        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

            expected_sp = sparse_tensor.SparseTensorValue(  # indices, values, shape
        np.array([[0, 5], [0, 10], [3, 0], [3, 3], [3, 9]], dtype=np.int64),
        np.array([3.0, 4.0, 1.0, -1.0, 2.0], dtype=np.float32),
        np.array([4, 13], dtype=np.int64))  # batch == 4, max_elems = 13
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 4 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 235..238

        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 79.

        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

            expected_rt = ragged_factory_ops.constant(
        [[[[[1]], [[2, 3], [4]]], [[], [[5, 6, 7]]]],
         [[[[1, 2, 3], [4]], [[5], [6], [7, 8]]]]],
        dtype=dtypes.float32,
        row_splits_dtype=dtypes.int64)
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 4 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 1177..1181

        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 77.

        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

                {
            "st_a":
                parsing_ops.VarLenFeature(dtypes.int64),
            "sp":
                parsing_ops.SparseFeature("idx", "val", dtypes.string, 13),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 4 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 639..653
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 634..647

        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 75.

        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

            original = [
        example(features=features({
            "val1": float_feature([3, 4]),
            "val2": float_feature([5, 6]),
            "idx": int64_feature([5, 10])
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 3 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 323..331
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 331..341

        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 71.

        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

            expected_output = {
        "a":
            np.array(  # pylint: disable=too-many-function-args
                [[1, 1], [3, -3], [3, -3]],
                dtype=np.float32).reshape(3, 1, 2, 1),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 3 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 565..573

        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

            original = [
        example(features=features({
            "val": bytes_feature([b"a", b"b"]),
            "idx": int64_feature([0, 3])
        })), example(features=features({
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 3 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 660..666
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 663..672

        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 68.

        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

            expected_output = {
        "st_a": expected_st_a,
        "sp": expected_sp,
        "a": np.array(2 * [[a_default]]),
        "b": np.array(2 * [b_default]),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 3 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 622..627

        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 68.

        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

                ops.convert_to_tensor(["", ""]), {
            sparse_name:
                parsing_ops.VarLenFeature(dtypes.int64),
            a_name:
                parsing_ops.FixedLenFeature(
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 3 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 145..156
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 142..153

        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

            original = [
        example(features=features({
            "a": float_feature([1, 1]),
        })),
        example(features=features({
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 3 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 536..544
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 552..559

        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

            original = [
        example(features=features({
            aname: float_feature([1, 1]),
            bname: bytes_feature([b"b0_str"]),
        })), example(features=features({
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 3 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 413..419
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 434..443

        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 4 locations. Consider refactoring.
        Open

            expected_output = {
        aname:
            np.array(  # pylint: disable=too-many-function-args
                [[1, 1], [-1, -1]],
                dtype=np.float32).reshape(2, 1, 2, 1),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 3 other locations - About 3 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 398..406
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 450..454
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 504..508

        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 64.

        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

            expected_output = {
        aname:
            np.array(  # pylint: disable=too-many-function-args
                [[1, 1], [-1, -1]],
                dtype=np.float32).reshape(2, 1, 2, 1),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 3 other locations - About 3 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 448..456
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 450..454
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 504..508

        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 64.

        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

            expected_sp1 = sparse_tensor.SparseTensorValue(  # indices, values, shape
        np.array([[0, 5], [0, 10]], dtype=np.int64),
        np.array([3.0, 4.0], dtype=np.float32),
        np.array([2, 13], dtype=np.int64))  # batch == 2, max_elems = 13
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 3 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 315..318

        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 64.

        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

            expected_sp2 = sparse_tensor.SparseTensorValue(  # indices, values, shape
        np.array([[0, 5], [0, 10]], dtype=np.int64),
        np.array([5.0, 6.0], dtype=np.float32),
        np.array([2, 7], dtype=np.int64))  # batch == 2, max_elems = 13
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 3 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 310..313

        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 64.

        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

            self._test(
        ops.convert_to_tensor(serialized), {
            aname:
                parsing_ops.FixedLenFeature((1, 2, 1), dtype=dtypes.float32),
            bname:
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 3 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 410..415

        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

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

            self._test(
        ops.convert_to_tensor(serialized), {
            aname:
                parsing_ops.FixedLenFeature((1, 2, 1), dtype=dtypes.float32),
            bname:
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 3 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 460..465

        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

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

            expected_output = {
        sparse_name: expected_st_a,
        a_name: np.array(2 * [[a_default]]),
        b_name: np.array(2 * [b_default]),
        c_name: np.array(2 * [c_default]),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 131..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 59.

        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 3 locations. Consider refactoring.
        Open

            test_features = {
        "rt1":
            parsing_ops.RaggedFeature(
                value_key="rt_values",
                partitions=[
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 2 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 1163..1173
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 2201..2211

        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 58.

        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

            expected_output_custom_padding[aname] = np.array(  # pylint: disable=too-many-function-args
        [
            [-2, -2, -2, -2],
            [1, 1, -2, -2],
            [-1, -1, 2, 2],
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 840..847

        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 57.

        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

            expected_st_a = sparse_tensor.SparseTensorValue(  # indices, values, shape
        np.empty((0, 2), dtype=np.int64),  # indices
        np.empty((0,), dtype=np.int64),  # sp_a is DT_INT64
        np.array([2, 0], dtype=np.int64))  # batch == 2, max_elems = 0
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 123..126

        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 57.

        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

            expected_st_a = sparse_tensor.SparseTensorValue(  # indices, values, shape
        np.empty((0, 2), dtype=np.int64),  # indices
        np.empty((0,), dtype=np.int64),  # sp_a is DT_INT64
        np.array([2, 0], dtype=np.int64))  # batch == 2, max_elems = 0
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 536..539

        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 57.

        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

            expected_uniform2 = ragged_factory_ops.constant(
        [[[[3], [4, 5, 6]]], [], [], [[[1, 2, -1], []], [[8, 9], [5]]]],
        dtype=dtypes.float32,
        row_splits_dtype=dtypes.int32)
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 1119..1122

        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 56.

        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

              self._test(
          ops.convert_to_tensor(serialized), {
              aname:
                  parsing_ops.FixedLenSequenceFeature((2, 1),
                                                      dtype=dtypes.float32,
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 719..728

        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 55.

        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

            original = [
        example(features=features(
            {"a": int64_feature([truth_int[i]]),
             "b": bytes_feature(truth_str[i])}))
        for i in range(batch_size)
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 731..736

        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 55.

        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

              self._test(
          ops.convert_to_tensor(serialized), {
              aname:
                  parsing_ops.FixedLenSequenceFeature((2, 1),
                                                      dtype=dtypes.float32,
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 733..742

        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 55.

        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

            expected_uniform1 = ragged_factory_ops.constant(
        [[[3, 4], [5, 6]], [], [], [[1, 2], [-1, 8], [9, 5]]],
        ragged_rank=1,
        dtype=dtypes.float32,
        row_splits_dtype=dtypes.int32)
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 1113..1117

        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 52.

        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

            original = [
        example(features=features({
            "a": float_feature([1, 1, 3]),
        })), example(features=features({
            "a": float_feature([-1, -1]),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 199..204

        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 51.

        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

            expected_rt = ragged_factory_ops.constant(
        [[[3], [4, 5, 6]], [], [], [[1, 2, -1], [], [8, 9], [5]]],
        dtype=dtypes.float32,
        row_splits_dtype=dtypes.int32)
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 2 hrs to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 1108..1111

        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 3 locations. Consider refactoring.
        Open

                ops.convert_to_tensor(serialized), {
            "a":
                parsing_ops.FixedLenFeature(
                    (1, 2, 1), dtype=dtypes.float32, default_value=[3.0, -3.0]),
            "b":
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 1 hr to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 577..586
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 580..587

        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 49.

        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

            expected_output = {
        # Batch size batch_size, 1 time step.
        "a": np.array(truth_int, dtype=np.int64).reshape(batch_size, 1),
        # Batch size batch_size, 2 time steps.
        "b": np.array(expected_str, dtype="|S").reshape(batch_size, 2),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 1 hr to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 724..728

        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 2 locations. Consider refactoring.
        Open

                ops.convert_to_tensor(serialized, dtype=dtypes.string), {
            "a":
                parsing_ops.FixedLenSequenceFeature(
                    shape=(),
                    dtype=dtypes.int64,
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 1 hr to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 745..755

        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 45.

        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

                ops.convert_to_tensor(serialized), {
            aname:
                parsing_ops.FixedLenSequenceFeature(
                    (2, 1), dtype=dtypes.float32, allow_missing=True),
            bname:
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 1 hr to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 803..809
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 878..884

        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

                ops.convert_to_tensor(serialized), {
            aname:
                parsing_ops.FixedLenFeature((None, 2, 1), dtype=dtypes.float32),
            bname:
                parsing_ops.FixedLenSequenceFeature(
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 1 hr to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 836..842
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 913..919

        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 2 locations. Consider refactoring.
        Open

            truth_str = [[("foo%d" % i).encode(), ("bar%d" % i).encode()]
                 for i in range(batch_size)]
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 1 hr to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 705..706

        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 3 locations. Consider refactoring.
        Open

                np.array([[0, 5, 0], [0, 10, 2], [3, 0, 1], [3, 3, 2], [3, 9, 0]],
                 dtype=np.int64),
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 1 hr to fix
        tensorflow/python/kernel_tests/array_ops/where_op_test.py on lines 86..87
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 410..411

        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 39.

        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

            original = [
        example(features=features({
            "a": float_feature([1]),
        })), example(features=features({}))
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 1 hr to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 513..516
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 527..531

        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 3 locations. Consider refactoring.
        Open

          @combinations.generate(
      combinations.times(
          test_base.default_test_combinations(),
          combinations.combine(
              local_determinism=[None, True, False],
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 50 mins to fix
        tensorflow/python/data/experimental/kernel_tests/optimization/make_deterministic_test.py on lines 316..321
        tensorflow/python/data/experimental/kernel_tests/parallel_interleave_test.py on lines 364..368

        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 3 locations. Consider refactoring.
        Open

                ops.convert_to_tensor(serialized), {
            "sp1":
                parsing_ops.SparseFeature("idx", "val1", dtypes.float32, 13),
            "sp2":
                parsing_ops.SparseFeature(
        Severity: Major
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 2 other locations - About 45 mins to fix
        tensorflow/python/kernel_tests/io_ops/parse_single_example_op_test.py on lines 350..357
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 365..373

        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

            batch_size = (
        self.evaluate(input_tensor).size
        if isinstance(input_tensor, tensor.Tensor)
        else np.asarray(input_tensor).size
        Severity: Minor
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 40 mins to fix
        tensorflow/python/kernel_tests/io_ops/parsing_ops_test.py on lines 99..102

        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

              elif isinstance(f, parsing_ops.VarLenFeature):
        self.assertEqual(
            dataset_ops.get_legacy_output_shapes(dataset)[k].as_list()[1], None)
        Severity: Minor
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 30 mins to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 105..108

        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

              if isinstance(f, parsing_ops.FixedLenFeature) and f.shape is not None:
        self.assertEqual(
            dataset_ops.get_legacy_output_shapes(dataset)[k].as_list()[0],
            batch_size)
        Severity: Minor
        Found in tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py and 1 other location - About 30 mins to fix
        tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py on lines 109..111

        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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