tensorflow/models

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official/projects/nhnet/input_pipeline.py

Summary

Maintainability
C
1 day
Test Coverage

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

def create_dataset(file_paths,
                   batch_size,
                   params,
                   is_training=True,
                   input_pipeline_context=None):
Severity: Minor
Found in official/projects/nhnet/input_pipeline.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 get_input_dataset has 5 arguments (exceeds 4 allowed). Consider refactoring.
Open

def get_input_dataset(input_file_pattern,
Severity: Minor
Found in official/projects/nhnet/input_pipeline.py - About 35 mins to fix

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

    def create_dataset(file_paths,
    Severity: Minor
    Found in official/projects/nhnet/input_pipeline.py - About 35 mins to fix

      Function get_input_dataset has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.
      Open

      def get_input_dataset(input_file_pattern,
                            batch_size,
                            params,
                            is_training,
                            strategy=None):
      Severity: Minor
      Found in official/projects/nhnet/input_pipeline.py - About 35 mins to fix

      Cognitive Complexity

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

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

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

      Further reading

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

      def decode_record(record, name_to_features):
        """Decodes a record to a TensorFlow example."""
        example = tf.io.parse_single_example(record, name_to_features)
      
        # tf.Example only supports tf.int64, but the TPU only supports tf.int32.
      Severity: Major
      Found in official/projects/nhnet/input_pipeline.py and 2 other locations - About 5 hrs to fix
      official/legacy/bert/input_pipeline.py on lines 20..32
      official/legacy/xlnet/data_utils.py on lines 61..73

      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 91.

      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

        if use_dataset_fn:
          if batch_size % strategy.num_replicas_in_sync != 0:
            raise ValueError(
                "Batch size must be divisible by number of replicas : {}".format(
                    strategy.num_replicas_in_sync))
      Severity: Major
      Found in official/projects/nhnet/input_pipeline.py and 3 other locations - About 2 hrs to fix
      official/legacy/xlnet/data_utils.py on lines 179..189
      official/legacy/xlnet/data_utils.py on lines 212..222
      official/legacy/xlnet/data_utils.py on lines 614..624

      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 54.

      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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