optimizers__init__.py

# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""
optimizer parameters.
"""
def get_param_groups(network):
    """get param groups"""
    decay_params = []
    no_decay_params = []
    for x in network.trainable_params():
        parameter_name = x.name
        if parameter_name.endswith('.bias'):
            # all bias not using weight decay
            # print('no decay:{}'.format(parameter_name))
            no_decay_params.append(x)
        elif parameter_name.endswith('.gamma'):
            # bn weight bias not using weight decay, be carefully for now x not include BN
            # print('no decay:{}'.format(parameter_name))
            no_decay_params.append(x)
        elif parameter_name.endswith('.beta'):
            # bn weight bias not using weight decay, be carefully for now x not include BN
            # print('no decay:{}'.format(parameter_name))
            no_decay_params.append(x)
        else:
            decay_params.append(x)

    return [{'params': no_decay_params, 'weight_decay': 0.0}, {'params': decay_params}]