지속 가능한 꾸준함

import torch import torch.nn as nn class Model(nn.Module): def __init__(self): super(Model, self).__init__() self.conv1 = nn.Conv2d(3, 16, 3, 1, 1) self.bn1 = nn.BatchNorm2d(16) self.conv2 = nn.Conv2d(16, 16, 3, 1, 1) self.bn2 = nn.BatchNorm2d(16) def forward(self, x): x = torch.relu(self.bn1(self.conv1(x))) x = x + torch.relu(self.bn2(self.conv2(x))) return x input = torch.randn((1, 3, 736, 128..

github.com/pytorch/pytorch/blob/master/torch/nn/modules/conv.py pytorch/pytorch Tensors and Dynamic neural networks in Python with strong GPU acceleration - pytorch/pytorch github.com 위 파일에서 reset_parameters() 함수를 보면 됨.

from pathlib import Path p = Path('mysequence.fasta') p.with_suffix('.aln') # It returns 'mysequence.aln'