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research/slim/train_image_classifier.py

Summary

Maintainability
D
1 day
Test Coverage

File train_image_classifier.py has 411 lines of code (exceeds 250 allowed). Consider refactoring.
Open

# Copyright 2016 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 research/slim/train_image_classifier.py - About 5 hrs to fix

    Function main has a Cognitive Complexity of 13 (exceeds 5 allowed). Consider refactoring.
    Open

    def main(_):
  if not FLAGS.dataset_dir:
    raise ValueError('You must supply the dataset directory with --dataset_dir')

  tf.logging.set_verbosity(tf.logging.INFO)
    Severity: Minor
    Found in research/slim/train_image_classifier.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_init_fn has a Cognitive Complexity of 12 (exceeds 5 allowed). Consider refactoring.
    Open

    def _get_init_fn():
  """Returns a function run by the chief worker to warm-start the training.

  Note that the init_fn is only run when initializing the model during the very
  first global step.
    Severity: Minor
    Found in research/slim/train_image_classifier.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 _configure_optimizer has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.
    Open

    def _configure_optimizer(learning_rate):
  """Configures the optimizer used for training.

  Args:
    learning_rate: A scalar or `Tensor` learning rate.
    Severity: Minor
    Found in research/slim/train_image_classifier.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 _configure_learning_rate has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.
    Open

    def _configure_learning_rate(num_samples_per_epoch, global_step):
  """Configures the learning rate.

  Args:
    num_samples_per_epoch: The number of samples in each epoch of training.
    Severity: Minor
    Found in research/slim/train_image_classifier.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

        for loss in tf.get_collection(tf.GraphKeys.LOSSES, first_clone_scope):
      summaries.add(tf.summary.scalar('losses/%s' % loss.op.name, loss))
    Severity: Major
    Found in research/slim/train_image_classifier.py and 1 other location - About 1 hr to fix
    research/deeplab/train.py on lines 360..361

    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 2 locations. Consider refactoring.
    Open

          images, labels = tf.train.batch(
          [image, label],
          batch_size=FLAGS.batch_size,
          num_threads=FLAGS.num_preprocessing_threads,
          capacity=5 * FLAGS.batch_size)
    Severity: Major
    Found in research/slim/train_image_classifier.py and 1 other location - About 1 hr to fix
    research/slim/eval_image_classifier.py on lines 138..142

    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 41.

    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 tf.gfile.IsDirectory(FLAGS.checkpoint_path):
    checkpoint_path = tf.train.latest_checkpoint(FLAGS.checkpoint_path)
  else:
    checkpoint_path = FLAGS.checkpoint_path
    Severity: Minor
    Found in research/slim/train_image_classifier.py and 1 other location - About 55 mins to fix
    research/slim/eval_image_classifier.py on lines 185..188

    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 37.

    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 6 locations. Consider refactoring.
    Open

        deploy_config = model_deploy.DeploymentConfig(
        num_clones=FLAGS.num_clones,
        clone_on_cpu=FLAGS.clone_on_cpu,
        replica_id=FLAGS.task,
        num_replicas=FLAGS.worker_replicas,
    Severity: Major
    Found in research/slim/train_image_classifier.py and 5 other locations - About 45 mins to fix
    official/legacy/detection/main.py on lines 83..88
    official/legacy/image_classification/resnet/resnet_ctl_imagenet_main.py on lines 118..123
    official/legacy/xlnet/run_pretrain.py on lines 84..89
    research/attention_ocr/python/demo_inference.py on lines 60..65
    research/deeplab/train.py on lines 276..281

    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 3 locations. Consider refactoring.
    Open

        for variable in slim.get_model_variables():
      summaries.add(tf.summary.histogram(variable.op.name, variable))
    Severity: Minor
    Found in research/slim/train_image_classifier.py and 2 other locations - About 30 mins to fix
    research/deeplab/train.py on lines 332..333
    research/lstm_object_detection/trainer.py on lines 375..376

    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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