File maskrcnn.py has 525 lines of code (exceeds 250 allowed). Consider refactoring.

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# 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

Function _reduce_instance_metrics has a Cognitive Complexity of 29 (exceeds 5 allowed). Consider refactoring.

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  def _reduce_instance_metrics(
      self, logs: Dict[str, Any], use_masks: bool = False
  ):
    """Updates the per class and mean instance metrics in the logs."""
    if use_masks:

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Function build_metrics has a Cognitive Complexity of 14 (exceeds 5 allowed). Consider refactoring.

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  def build_metrics(self, training: bool = True):
    """Builds detection metrics."""
    self.instance_box_perclass_metrics = None
    self.instance_mask_perclass_metrics = None
    if training:

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

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  def _build_frcnn_losses(
      self,
      outputs: Mapping[str, Any],
      labels: Mapping[str, Any],
  ) -> Tuple[tf.Tensor, tf.Tensor]:

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

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  def _build_coco_metrics(self):
    """Builds COCO metrics evaluator."""
    if (not self._task_config.model.include_mask
       ) or self._task_config.annotation_file:
      self.coco_metric = coco_evaluator.COCOEvaluator(

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Function aggregate_logs has a Cognitive Complexity of 11 (exceeds 5 allowed). Consider refactoring.

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  def aggregate_logs(
      self,
      state: Optional[Any] = None,
      step_outputs: Optional[Dict[str, Any]] = None,
  ) -> Optional[Any]:

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

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  def train_step(self,
                 inputs: Tuple[Any, Any],
                 model: tf_keras.Model,
                 optimizer: tf_keras.optimizers.Optimizer,
                 metrics: Optional[List[Any]] = None):

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

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  def initialize(self, model: tf_keras.Model):
    """Loads pretrained checkpoint."""

    if not self.task_config.init_checkpoint:
      return

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Avoid deeply nested control flow statements.

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            for j, iou in enumerate(iou_thresholds):
              if int(iou * 100) in {50, 75}:
                logs[f'{prefix}{ap_key}{int(iou * 100)} ByCategory/{k}'] = (
                    per_class_ap[j][k]
                )

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

Open

  def _update_metrics(self, labels, outputs, logs):
    instance_predictions = {
        'detection_boxes': outputs['detection_boxes'],
        'detection_scores': outputs['detection_scores'],
        'detection_classes': outputs['detection_classes'],

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

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  def reduce_aggregated_logs(
      self,
      aggregated_logs: Dict[str, Any],
      global_step: Optional[tf.Tensor] = None,
  ) -> Dict[str, tf.Tensor]:

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