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bullet3/examples/pybullet/gym/pybullet_envs/agents/tools/count_weights.py
Erwin Coumans ef9570c315 add yapf style and apply yapf to format all Python files
This recreates pull request #2192
2019-04-27 07:31:15 -07:00

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Python

# Copyright 2017 The TensorFlow Agents Authors.
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Count learnable parameters."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import re
import numpy as np
import tensorflow as tf
def count_weights(scope=None, exclude=None, graph=None):
"""Count learnable parameters.
Args:
scope: Resrict the count to a variable scope.
exclude: Regex to match variable names to exclude.
graph: Operate on a graph other than the current default graph.
Returns:
Number of learnable parameters as integer.
"""
if scope:
scope = scope if scope.endswith('/') else scope + '/'
graph = graph or tf.get_default_graph()
vars_ = graph.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES)
if scope:
vars_ = [var for var in vars_ if var.name.startswith(scope)]
if exclude:
exclude = re.compile(exclude)
vars_ = [var for var in vars_ if not exclude.match(var.name)]
shapes = [var.get_shape().as_list() for var in vars_]
return int(sum(np.prod(shape) for shape in shapes))