title: RuntimeError: Given groups=1, weight of size [64, 3, 3, 3], expected input[4, 5000, 5000, 3] to have 3 channels, but got 5000 channels instead
body: <p>So, I have a U-Net model and I'm feeding images of 5000x5000x3 into the model and I and getting the error above.</p>
  
  <p>So here is my model.</p>
  
  <pre><code>import torch
  import torch.nn as nn
  
  
  def double_conv(in_channels, out_channels):
      return nn.Sequential(
          nn.Conv2d(in_channels, out_channels, 3, padding=1),
          nn.ReLU(inplace=True),
          nn.Conv2d(out_channels, out_channels, 3, padding=1),
          nn.ReLU(inplace=True)
      )
  
  
  class UNeT(nn.Module):
      def __init__(self, n_class):
          super().__init__()
          self.dconv_down1 = double_conv(3, 64)
          self.dconv_down2 = double_conv(64, 128)
          self.dconv_down3 = double_conv(128, 256)
          self.dconv_down4 = double_conv(256, 512)
          self.maxpool = nn.MaxPool2d(2)
          self.upsample = nn.Upsample(scale_factor=2, mode='bilinear',
                                      align_corners=True)
          self.dconv_up3 = double_conv(256 + 512, 256)
          self.dconv_up2 = double_conv(128 + 256, 128)
          self.dconv_up1 = double_conv(128 + 64, 64)
          self.conv_last = nn.Conv2d(64, n_class, 1)
  
      def forward(self, x):
          conv1 = self.dconv_down1(x)
          x = self.maxpool(conv1)
          conv2 = self.dconv_down2(x)
          x = self.maxpool(conv2)
          conv3 = self.dconv_down3(x)
          x = self.maxpool(conv3)
          x = self.dconv_down4(x)
          x = self.upsample(x)
          x = torch.cat([x, conv3], dim=1)
          x = self.dconv_up3(x)
          x = self.upsample(x)
          x = torch.cat([x, conv2], dim=1)
          x = self.dconv_up2(x)
          x = self.upsample(x)
          x = torch.cat([x, conv1], dim=1)
          x = self.dconv_up1(x)
          out = self.conv_last(x)
          return out
  
  
  </code></pre>
  
  <p>I tried to do model(inputs.unsqueeze_(0)) but I got a different error.</p>