File assemblenet_plus.py has 592 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 __init__ has a Cognitive Complexity of 34 (exceeds 5 allowed). Consider refactoring.

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  def __init__(self,
               block_fn,
               num_blocks: List[int],
               num_frames: int,
               model_structure: List[Any],

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Function fusion_with_peer_attention has a Cognitive Complexity of 27 (exceeds 5 allowed). Consider refactoring.

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def fusion_with_peer_attention(inputs: List[tf.Tensor],
                               index: Optional[int] = None,
                               attention_mode: Optional[str] = None,
                               attention_in: Optional[List[tf.Tensor]] = None,
                               use_5d_mode: bool = False,

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

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  def call(self,
           inputs: List[tf.Tensor],
           training: Optional[bool] = None) -> Mapping[Any, List[tf.Tensor]]:
    use_5d_mode = self._use_5d_mode
    dtype = inputs[0].dtype

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

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  def __init__(self,

Function assemblenet_plus has 10 arguments (exceeds 4 allowed). Consider refactoring.

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def assemblenet_plus(assemblenet_depth: int,

Function __init__ has 8 arguments (exceeds 4 allowed). Consider refactoring.

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  def __init__(self,

Function fusion_with_peer_attention has 7 arguments (exceeds 4 allowed). Consider refactoring.

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def fusion_with_peer_attention(inputs: List[tf.Tensor],

Avoid deeply nested control flow statements.

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            for k in nodes_below:
              logging.info(streams[k].shape)
              lg_channel = max(streams[k].shape[3], lg_channel)

Avoid deeply nested control flow statements.

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            for node_index in nodes_below:
              attn = tf.reduce_mean(streams[node_index], [1, 2])

              attn = tf_keras.layers.Dense(
                  units=lg_channel,

Function __init__ has 6 arguments (exceeds 4 allowed). Consider refactoring.

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  def __init__(self,