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- # 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.
- # ============================================================================
- """utils script"""
-
- def _load_param_into_net(model, params_dict):
- """
- load fp32 model parameters to quantization model.
-
- Args:
- model: quantization model
- params_dict: f32 param
-
- Returns:
- None
- """
- iterable_dict = {
- 'weight': iter([item for item in params_dict.items() if item[0].endswith('weight')]),
- 'bias': iter([item for item in params_dict.items() if item[0].endswith('bias')]),
- 'gamma': iter([item for item in params_dict.items() if item[0].endswith('gamma')]),
- 'beta': iter([item for item in params_dict.items() if item[0].endswith('beta')]),
- 'moving_mean': iter([item for item in params_dict.items() if item[0].endswith('moving_mean')]),
- 'moving_variance': iter(
- [item for item in params_dict.items() if item[0].endswith('moving_variance')]),
- 'minq': iter([item for item in params_dict.items() if item[0].endswith('minq')]),
- 'maxq': iter([item for item in params_dict.items() if item[0].endswith('maxq')])
- }
- for name, param in model.parameters_and_names():
- key_name = name.split(".")[-1]
- if key_name not in iterable_dict.keys():
- continue
- value_param = next(iterable_dict[key_name], None)
- if value_param is not None:
- param.set_parameter_data(value_param[1].data)
- print(f'init model param {name} with checkpoint param {value_param[0]}')
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