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Runtime error
Runtime error
| import torch | |
| import torch.nn as nn | |
| ## *************************** my functions **************************** | |
| def predict_param(in_planes, channel=3): | |
| return nn.Conv2d(in_planes, channel, kernel_size=3, stride=1, padding=1, bias=True) | |
| def predict_mask(in_planes, channel=9): | |
| return nn.Conv2d(in_planes, channel, kernel_size=3, stride=1, padding=1, bias=True) | |
| def predict_feat(in_planes, channel=20, stride=1): | |
| return nn.Conv2d(in_planes, channel, kernel_size=3, stride=stride, padding=1, bias=True) | |
| def predict_prob(in_planes, channel=9): | |
| return nn.Sequential( | |
| nn.Conv2d(in_planes, channel, kernel_size=3, stride=1, padding=1, bias=True), | |
| nn.Softmax(1) | |
| ) | |
| #*********************************************************************** | |
| def conv(batchNorm, in_planes, out_planes, kernel_size=3, stride=1): | |
| if batchNorm: | |
| return nn.Sequential( | |
| nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, stride=stride, padding=(kernel_size-1)//2, bias=False), | |
| nn.BatchNorm2d(out_planes), | |
| nn.LeakyReLU(0.1) | |
| ) | |
| else: | |
| return nn.Sequential( | |
| nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, stride=stride, padding=(kernel_size-1)//2, bias=True), | |
| nn.LeakyReLU(0.1) | |
| ) | |
| def deconv(in_planes, out_planes): | |
| return nn.Sequential( | |
| nn.ConvTranspose2d(in_planes, out_planes, kernel_size=4, stride=2, padding=1, bias=True), | |
| nn.LeakyReLU(0.1) | |
| ) | |