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tensorflow/python/distribute/distributed_table_test.py

Summary

Maintainability
F
4 days
Test Coverage

File distributed_table_test.py has 498 lines of code (exceeds 250 allowed). Consider refactoring.
Open

# Copyright 2021 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: Minor
Found in tensorflow/python/distribute/distributed_table_test.py - About 7 hrs to fix

    Function testCreateTableInDatasetCombo has a Cognitive Complexity of 21 (exceeds 5 allowed). Consider refactoring.
    Open

      def testCreateTableInDatasetCombo(self, source, create_datasets_under_scope,
                                    using_dataset_instance_not_function,
                                    create_per_worker_dataset_takes_instance):

    if using_dataset_instance_not_function and (
    Severity: Minor
    Found in tensorflow/python/distribute/distributed_table_test.py - About 2 hrs to fix

    Cognitive Complexity

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

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

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

    Further reading

    Function testCreateTableUnderScopeCombo has a Cognitive Complexity of 12 (exceeds 5 allowed). Consider refactoring.
    Open

      def testCreateTableUnderScopeCombo(self, source,
                                     create_datasets_under_scope,
                                     using_dataset_instance_not_function,
                                     create_per_worker_dataset_takes_instance):
    strategy = parameter_server_strategy_v2.ParameterServerStrategyV2(
    Severity: Minor
    Found in tensorflow/python/distribute/distributed_table_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 testLookupInNestedTFWhileLoop has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.
    Open

      def testLookupInNestedTFWhileLoop(self, source):
    strategy = parameter_server_strategy_v2.ParameterServerStrategyV2(
        self.cluster_resolver)
    coordinator = coordinator_lib.ClusterCoordinator(strategy=strategy)
    Severity: Minor
    Found in tensorflow/python/distribute/distributed_table_test.py - About 25 mins to fix

    Cognitive Complexity

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

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

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

    Further reading

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

        if create_datasets_under_scope:
      with strategy.scope():
        if create_per_worker_dataset_takes_instance:
          per_worker_dataset = coordinator.create_per_worker_dataset(
              per_worker_dataset_fn())
    Severity: Major
    Found in tensorflow/python/distribute/distributed_table_test.py and 1 other location - About 5 hrs to fix
    tensorflow/python/distribute/distributed_table_test.py on lines 381..398

    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 89.

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

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

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

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

    Refactorings

    Further Reading

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

        if create_datasets_under_scope:
      with strategy.scope():
        if create_per_worker_dataset_takes_instance:
          per_worker_dataset = coordinator.create_per_worker_dataset(
              per_worker_dataset_fn())
    Severity: Major
    Found in tensorflow/python/distribute/distributed_table_test.py and 1 other location - About 5 hrs to fix
    tensorflow/python/distribute/distributed_table_test.py on lines 270..287

    Duplicated Code

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

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

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

    Tuning

    This issue has a mass of 89.

    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

      @classmethod
  def setUpClass(cls):
    super(DistributedTableTest, cls).setUpClass()
    cls.cluster = multi_worker_test_base.create_multi_process_cluster(
        num_workers=2, num_ps=3, rpc_layer="grpc")
    Severity: Major
    Found in tensorflow/python/distribute/distributed_table_test.py and 2 other locations - About 2 hrs to fix
    tensorflow/python/distribute/parameter_server_strategy_v2_test.py on lines 59..64
    tensorflow/python/distribute/parameter_server_strategy_v2_test.py on lines 298..303

    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

        dataset = (
        dataset_ops.DatasetV2.from_tensors(
            constant_op.constant([0, 1, 3], dtype=dtypes.int64)).repeat().batch(
    Severity: Major
    Found in tensorflow/python/distribute/distributed_table_test.py and 1 other location - About 1 hr to fix
    tensorflow/python/distribute/distributed_table_test.py on lines 423..425

    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

        dataset = (
        dataset_ops.DatasetV2.from_tensors(
            constant_op.constant([0, 1, 3], dtype=dtypes.int64)).repeat().batch(
    Severity: Major
    Found in tensorflow/python/distribute/distributed_table_test.py and 1 other location - About 1 hr to fix
    tensorflow/python/distribute/distributed_table_test.py on lines 598..600

    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

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

          with open(file, "w") as f:
        f.write("\n".join(str(v) for v in vals) + "\n")
    Severity: Major
    Found in tensorflow/python/distribute/distributed_table_test.py and 2 other locations - About 1 hr to fix
    tensorflow/python/data/kernel_tests/test_base.py on lines 336..337
    tensorflow/python/distribute/distributed_table_test.py on lines 506..507

    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

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

            with open(filepath, "w") as f:
          f.write("\n".join(str(v) for v in vals) + "\n")
    Severity: Major
    Found in tensorflow/python/distribute/distributed_table_test.py and 2 other locations - About 1 hr to fix
    tensorflow/python/data/kernel_tests/test_base.py on lines 336..337
    tensorflow/python/distribute/distributed_table_test.py on lines 65..66

    Duplicated Code

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

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

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

    Tuning

    This issue has a mass of 44.

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

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

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

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

    Refactorings

    Further Reading

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

      @combinations.generate(
      combinations.combine(
          source=["textfile", "keyvaluetensor"],
          create_datasets_under_scope=[True, False],
          using_dataset_instance_not_function=[True, False],
    Severity: Minor
    Found in tensorflow/python/distribute/distributed_table_test.py and 1 other location - About 50 mins to fix
    tensorflow/python/distribute/distributed_table_test.py on lines 302..307

    Duplicated Code

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

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

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

    Tuning

    This issue has a mass of 36.

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

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

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

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

    Refactorings

    Further Reading

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

      @combinations.generate(
      combinations.combine(
          source=["textfile", "keyvaluetensor"],
          create_datasets_under_scope=[True, False],
          using_dataset_instance_not_function=[True, False],
    Severity: Minor
    Found in tensorflow/python/distribute/distributed_table_test.py and 1 other location - About 50 mins to fix
    tensorflow/python/distribute/distributed_table_test.py on lines 226..231

    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

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