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official/nlp/modeling/layers/transformer_xl.py

Summary

Maintainability
F
3 days
Test Coverage

File transformer_xl.py has 489 lines of code (exceeds 250 allowed). Consider refactoring.
Open

# Copyright 2024 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 official/nlp/modeling/layers/transformer_xl.py - About 7 hrs to fix

    Function call has a Cognitive Complexity of 17 (exceeds 5 allowed). Consider refactoring.
    Open

      def call(self,
           content_stream,
           relative_position_encoding,
           segment_matrix=None,
           segment_embedding=None,
    Severity: Minor
    Found in official/nlp/modeling/layers/transformer_xl.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 __init__ has 15 arguments (exceeds 4 allowed). Consider refactoring.
    Open

      def __init__(self,
    Severity: Major
    Found in official/nlp/modeling/layers/transformer_xl.py - About 1 hr to fix

      Function __init__ has 13 arguments (exceeds 4 allowed). Consider refactoring.
      Open

        def __init__(self,
      Severity: Major
      Found in official/nlp/modeling/layers/transformer_xl.py - About 1 hr to fix

        Function call has 12 arguments (exceeds 4 allowed). Consider refactoring.
        Open

          def call(self,
        Severity: Major
        Found in official/nlp/modeling/layers/transformer_xl.py - About 1 hr to fix

          Function call has 9 arguments (exceeds 4 allowed). Consider refactoring.
          Open

            def call(self,
          Severity: Major
          Found in official/nlp/modeling/layers/transformer_xl.py - About 1 hr to fix

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

            def _cache_memory(current_state, previous_state, memory_length, reuse_length=0):
  """Caches hidden states into memory.

  Args:
    current_state: `Tensor`, the current state.
            Severity: Minor
            Found in official/nlp/modeling/layers/transformer_xl.py - About 45 mins to fix

            Cognitive Complexity

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

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

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

            Further reading

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

              def call(self,
           content_stream,
           content_attention_bias,
           positional_attention_bias,
           relative_position_encoding=None,
            Severity: Minor
            Found in official/nlp/modeling/layers/transformer_xl.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

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

              def build(self, input_shape):
    input_tensor = input_shape[0] if len(input_shape) == 2 else input_shape
    input_tensor_shape = tf.TensorShape(input_tensor)
    if len(input_tensor_shape.as_list()) != 3:
      raise ValueError("TransformerLayer expects a three-dimensional input of "
            Severity: Minor
            Found in official/nlp/modeling/layers/transformer_xl.py - About 25 mins to fix

            Cognitive Complexity

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

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

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

            Further reading

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

                if len(input_shape) == 2:
      mask_tensor_shape = tf.TensorShape(input_shape[1])
      expected_mask_tensor_shape = tf.TensorShape(
          [batch_size, sequence_length, sequence_length])
      if not expected_mask_tensor_shape.is_compatible_with(mask_tensor_shape):
            Severity: Major
            Found in official/nlp/modeling/layers/transformer_xl.py and 1 other location - About 4 hrs to fix
            official/nlp/modeling/layers/tn_transformer_expand_condense.py on lines 116..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 76.

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

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

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

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

            Refactorings

            Further Reading

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

                config = {
        "vocab_size":
            self._vocab_size,
        "num_layers":
            self._num_layers,
            Severity: Major
            Found in official/nlp/modeling/layers/transformer_xl.py and 3 other locations - About 3 hrs to fix
            official/projects/pix2seq/modeling/transformer.py on lines 519..533
            official/vision/modeling/layers/nn_blocks_3d.py on lines 236..250
            research/object_detection/builders/model_builder.py on lines 149..177

            Duplicated Code

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

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

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

            Tuning

            This issue has a mass of 63.

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

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

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

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

            Refactorings

            Further Reading

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

                config = {
        "vocab_size":
            self._vocab_size,
        "hidden_size":
            self._hidden_size,
            Severity: Major
            Found in official/nlp/modeling/layers/transformer_xl.py and 2 other locations - About 2 hrs to fix
            official/nlp/modeling/models/seq2seq_transformer.py on lines 572..584
            official/projects/yolo/modeling/layers/nn_blocks.py on lines 912..924

            Duplicated Code

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

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

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

            Tuning

            This issue has a mass of 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

            Similar blocks of code found in 7 locations. Consider refactoring.
            Open

                if hidden_size % self._num_heads != 0:
      raise ValueError(
          "The input size (%d) is not a multiple of the number of attention "
          "heads (%d)" % (hidden_size, self._num_heads))
            Severity: Major
            Found in official/nlp/modeling/layers/transformer_xl.py and 6 other locations - About 50 mins to fix
            official/nlp/modeling/layers/reuse_transformer.py on lines 154..157
            official/nlp/modeling/layers/tn_transformer_expand_condense.py on lines 127..130
            official/nlp/modeling/layers/transformer.py on lines 260..263
            official/nlp/modeling/layers/transformer_scaffold.py on lines 142..145
            official/projects/detr/modeling/transformer.py on lines 256..259
            official/projects/detr/modeling/transformer.py on lines 670..673

            Duplicated Code

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

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

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

            Tuning

            This issue has a mass of 36.

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

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

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

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

            Refactorings

            Further Reading

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

                self.content_attention_bias = self.add_weight(
        "content_attention_bias",
        shape=attention_bias_shape,
        dtype=tf.float32,
        initializer=tf_utils.clone_initializer(self._initializer))
            Severity: Minor
            Found in official/nlp/modeling/layers/transformer_xl.py and 2 other locations - About 35 mins to fix
            official/nlp/modeling/layers/transformer_xl.py on lines 403..407
            official/nlp/modeling/layers/transformer_xl.py on lines 408..412

            Duplicated Code

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

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

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

            Tuning

            This issue has a mass of 33.

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

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

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

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

            Refactorings

            Further Reading

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

                self.segment_attention_bias = self.add_weight(
        "segment_attention_bias",
        shape=attention_bias_shape,
        dtype=tf.float32,
        initializer=tf_utils.clone_initializer(self._initializer))
            Severity: Minor
            Found in official/nlp/modeling/layers/transformer_xl.py and 2 other locations - About 35 mins to fix
            official/nlp/modeling/layers/transformer_xl.py on lines 398..402
            official/nlp/modeling/layers/transformer_xl.py on lines 403..407

            Duplicated Code

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

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

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

            Tuning

            This issue has a mass of 33.

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

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

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

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

            Refactorings

            Further Reading

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

                self.positional_attention_bias = self.add_weight(
        "positional_attention_bias",
        shape=attention_bias_shape,
        dtype=tf.float32,
        initializer=tf_utils.clone_initializer(self._initializer))
            Severity: Minor
            Found in official/nlp/modeling/layers/transformer_xl.py and 2 other locations - About 35 mins to fix
            official/nlp/modeling/layers/transformer_xl.py on lines 398..402
            official/nlp/modeling/layers/transformer_xl.py on lines 408..412

            Duplicated Code

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

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

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

            Tuning

            This issue has a mass of 33.

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

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

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

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

            Refactorings

            Further Reading

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