official/projects/qat/vision/modeling/heads/dense_prediction_heads.py
Function build has a Cognitive Complexity of 41 (exceeds 5 allowed). Consider refactoring. Open
Open
def build(self, input_shape: Union[tf.TensorShape, List[tf.TensorShape]]):
"""Creates the variables of the head."""
if self._config_dict['use_separable_conv']:
conv_op = helper.SeparableConv2DQuantized
else:- Read upRead up
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 call has a Cognitive Complexity of 27 (exceeds 5 allowed). Consider refactoring. Open
Open
def call(self, features: Mapping[str, tf.Tensor]):
"""Forward pass of the RetinaNet quantized head.
Args:
features: A `dict` of `tf.Tensor` where- Read upRead up
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
File dense_prediction_heads.py has 325 lines of code (exceeds 250 allowed). Consider refactoring. Open
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 atFunction __init__ has 18 arguments (exceeds 4 allowed). Consider refactoring. Open
Open
def __init__(Avoid deeply nested control flow statements. Open
Open
if prediction_tower_name not in prediction_tower_output:
prediction_tower_output[
prediction_tower_name] = build_prediction_tower(
att_name, this_level_features, i)
attributes[att_name][str(level)] = self._att_predictors[att_name](Avoid deeply nested control flow statements. Open
Open
if level == self._config_dict['min_level']:
att_conv_name = '{}-conv_{}'.format(att_name, i)
att_convs_i.append(conv_op(name=att_conv_name, **conv_kwargs))
att_norm_name = '{}-conv-norm_{}_{}'.format(att_name, level, i)