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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 | |