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official/legacy/xlnet/training_utils.py

Summary

Maintainability
D
1 day
Test Coverage

Function train has a Cognitive Complexity of 76 (exceeds 5 allowed). Consider refactoring.
Open

def train(
    strategy: tf.distribute.Strategy,
    model_fn: Callable,
    input_meta_data: Dict,
    train_input_fn: Callable,
Severity: Minor
Found in official/legacy/xlnet/training_utils.py - About 1 day 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 train has 15 arguments (exceeds 4 allowed). Consider refactoring.
Open

def train(
Severity: Major
Found in official/legacy/xlnet/training_utils.py - About 1 hr to fix

    Avoid deeply nested control flow statements.
    Open

              if train_metric:
            tf.summary.scalar(
                train_metric.name,
                _float_metric_value(train_metric),
                step=current_step)
    Severity: Major
    Found in official/legacy/xlnet/training_utils.py - About 45 mins to fix

      Avoid deeply nested control flow statements.
      Open

                  if "model/transformer/layer_{}/".format(l) in tvars[i].name:
              abs_rate = input_meta_data["lr_layer_decay_rate"]**(
                  n_layer - 1 - l)
              clipped[i] *= abs_rate
              logging.info("Apply mult {:.4f} to layer-{} grad of {}".format(
      Severity: Major
      Found in official/legacy/xlnet/training_utils.py - About 45 mins to fix

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