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	| # Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved. | |
| # This program is free software; you can redistribute it and/or modify | |
| # it under the terms of the MIT License. | |
| # This program is distributed in the hope that it will be useful, | |
| # but WITHOUT ANY WARRANTY; without even the implied warranty of | |
| # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
| # MIT License for more details. | |
| import numpy as np | |
| import torch | |
| class BaseModule(torch.nn.Module): | |
| def __init__(self): | |
| super(BaseModule, self).__init__() | |
| def nparams(self): | |
| """ | |
| Returns number of trainable parameters of the module. | |
| """ | |
| num_params = 0 | |
| for name, param in self.named_parameters(): | |
| if param.requires_grad: | |
| num_params += np.prod(param.detach().cpu().numpy().shape) | |
| return num_params | |
| def relocate_input(self, x: list): | |
| """ | |
| Relocates provided tensors to the same device set for the module. | |
| """ | |
| device = next(self.parameters()).device | |
| for i in range(len(x)): | |
| if isinstance(x[i], torch.Tensor) and x[i].device != device: | |
| x[i] = x[i].to(device) | |
| return x | |
