ema.py

# Copyright (c) MONAI Consortium
# 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.

import torch.nn as nn


class EMAHelper:
    def __init__(self, mu=0.999):
        self.mu = mu
        self.shadow = {}

    def register(self, module):
        if isinstance(module, nn.DataParallel):
            module = module.module
        for name, param in module.named_parameters():
            if param.requires_grad:
                self.shadow[name] = param.data.clone()

    def update(self, module):
        if isinstance(module, nn.DataParallel):
            module = module.module
        for name, param in module.named_parameters():
            if param.requires_grad:
                self.shadow[name].data = (1.0 - self.mu) * param.data + self.mu * self.shadow[name].data

    def ema(self, module):
        if isinstance(module, nn.DataParallel):
            module = module.module
        for name, param in module.named_parameters():
            if param.requires_grad:
                param.data.copy_(self.shadow[name].data)

    def ema_copy(self, module):
        if isinstance(module, nn.DataParallel):
            inner_module = module.module
            module_copy = type(inner_module)(inner_module.config).to(inner_module.config.device)
            module_copy.load_state_dict(inner_module.state_dict())
            module_copy = nn.DataParallel(module_copy)
        else:
            module_copy = type(module)(module.config).to(module.config.device)
            module_copy.load_state_dict(module.state_dict())
        # module_copy = copy.deepcopy(module)
        self.ema(module_copy)
        return module_copy

    def state_dict(self):
        return self.shadow

    def load_state_dict(self, state_dict):
        self.shadow = state_dict