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Given transposed=1, weight of size [256, 128, 2, 2], expected input[1, 64, 128, 128] to have 256 channels, but got 64 channels instead ` network = Generic_UNetPlusPlus(num_input_channels, base_num_features, num_classes, len(net_num_pool_op_kernel_sizes), 2, 2, nn.Conv2d, nn.InstanceNorm2d, norm_op_kwargs, nn.Dropout2d, dropout_op_kwargs, net_nonlin, net_nonlin_kwargs, True, False, lambda x: x, InitWeights_He(1e-2), net_num_pool_op_kernel_sizes, net_conv_kernel_sizes, False, True, True)
a = torch.randn(1, 1, 256, 256)
b = network(a) `
The text was updated successfully, but these errors were encountered:
Hi, friend! : ) i meet the same problem. Are you have solution of this issue?
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Given transposed=1, weight of size [256, 128, 2, 2], expected input[1, 64, 128, 128] to have 256 channels, but got 64 channels instead
`
network = Generic_UNetPlusPlus(num_input_channels, base_num_features, num_classes, len(net_num_pool_op_kernel_sizes), 2, 2,
nn.Conv2d, nn.InstanceNorm2d, norm_op_kwargs, nn.Dropout2d,
dropout_op_kwargs, net_nonlin, net_nonlin_kwargs, True, False, lambda x: x, InitWeights_He(1e-2),
net_num_pool_op_kernel_sizes, net_conv_kernel_sizes, False, True, True)
a = torch.randn(1, 1, 256, 256)
b = network(a)
`
The text was updated successfully, but these errors were encountered: