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official/nlp/modeling/networks/xlnet_base_test.py

Summary

Maintainability
F
5 days
Test Coverage

File xlnet_base_test.py has 377 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/networks/xlnet_base_test.py - About 5 hrs to fix

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

      def test_compute_attention_mask_smoke(self,
                                        use_input_mask,
                                        use_permutation_mask,
                                        attention_type,
                                        memory_length):
    Severity: Minor
    Found in official/nlp/modeling/networks/xlnet_base_test.py - About 25 mins to fix

    Cognitive Complexity

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

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

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

    Further reading

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

      def test_permutation_input_uni_mask(self):
    """Tests if an input, permutation and causal mask are provided."""
    seq_length = 4
    batch_size = 1
    memory_length = 0
    Severity: Major
    Found in official/nlp/modeling/networks/xlnet_base_test.py and 1 other location - About 1 day to fix
    official/nlp/modeling/networks/xlnet_base_test.py on lines 230..264

    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 216.

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

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

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

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

    Refactorings

    Further Reading

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

      def test_permutation_and_input_mask(self):
    """Tests if both an input and permutation mask are provided."""
    seq_length = 4
    batch_size = 1
    memory_length = 0
    Severity: Major
    Found in official/nlp/modeling/networks/xlnet_base_test.py and 1 other location - About 1 day to fix
    official/nlp/modeling/networks/xlnet_base_test.py on lines 266..300

    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 216.

    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_segment_matrix = np.array([[
        [False, False, True, False],
        [False, False, True, False],
        [True, True, False, True],
        [False, False, True, False]
    Severity: Minor
    Found in official/nlp/modeling/networks/xlnet_base_test.py and 1 other location - About 40 mins to fix
    official/nlp/modeling/networks/xlnet_base_test.py on lines 359..363

    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

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

        expected_segment_matrix = np.array([[
        [False, False, True, False],
        [False, False, True, False],
        [True, True, False, True],
        [False, False, True, False]
    Severity: Minor
    Found in official/nlp/modeling/networks/xlnet_base_test.py and 1 other location - About 40 mins to fix
    official/nlp/modeling/networks/xlnet_base_test.py on lines 319..323

    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

        segment_matrix = tf.cast(xlnet_base._compute_segment_matrix(
        segment_ids=segment_ids,
        memory_length=memory_length,
        batch_size=batch_size,
        use_cls_mask=False), dtype=tf.uint8)
    Severity: Minor
    Found in official/nlp/modeling/networks/xlnet_base_test.py and 1 other location - About 40 mins to fix
    official/nlp/modeling/networks/xlnet_base_test.py on lines 365..369

    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

        segment_matrix = tf.cast(xlnet_base._compute_segment_matrix(
        segment_ids=segment_ids,
        memory_length=memory_length,
        batch_size=batch_size,
        use_cls_mask=True), dtype=tf.uint8)
    Severity: Minor
    Found in official/nlp/modeling/networks/xlnet_base_test.py and 1 other location - About 40 mins to fix
    official/nlp/modeling/networks/xlnet_base_test.py on lines 344..348

    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 5 locations. Consider refactoring.
    Open

        expected_output = np.array([[1, 1, 1, 0, 0],
                                [0, 1, 1, 1, 0],
                                [0, 0, 1, 1, 1]])
    Severity: Major
    Found in official/nlp/modeling/networks/xlnet_base_test.py and 4 other locations - About 35 mins to fix
    official/legacy/transformer/model_utils_test.py on lines 27..27
    official/legacy/transformer/model_utils_test.py on lines 34..34
    official/nlp/modeling/networks/xlnet_base_test.py on lines 96..98
    research/delf/delf/python/datasets/revisited_op/dataset_test.py on lines 159..160

    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 5 locations. Consider refactoring.
    Open

        expected_output = np.array([[1, 1, 1, 0, 0],
                                [1, 1, 1, 1, 0],
                                [1, 1, 1, 1, 1]])
    Severity: Major
    Found in official/nlp/modeling/networks/xlnet_base_test.py and 4 other locations - About 35 mins to fix
    official/legacy/transformer/model_utils_test.py on lines 27..27
    official/legacy/transformer/model_utils_test.py on lines 34..34
    official/nlp/modeling/networks/xlnet_base_test.py on lines 108..110
    research/delf/delf/python/datasets/revisited_op/dataset_test.py on lines 159..160

    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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