Given groups=1, weight of size [64, 1, 3, 3], expected input[1, 4, 215, 696] to have 1 channels, but got 4 channels instead

Question

Getting this error. Not able to understand what the error is. How should reshape my tensor? I'm having a coloured image of dimensions 215 * 696 with 4 channels. what is that 1?

if __name__== '__main__':
    model= UNet()
    x= model(tensor[None,...])

"""RuntimeError                              Traceback (most recent call last)
<ipython-input-13-f52a795a466e> in <module>
      4     #Image= image.imread('Image_test2.png')
      5     model= UNet()
----> 6     x= model(tensor[None,...])

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
   1100         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1101                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1102             return forward_call(*input, **kwargs)
   1103         # Do not call functions when jit is used
   1104         full_backward_hooks, non_full_backward_hooks = [], []

<ipython-input-5-c83597cc9747> in forward(self, image)
     56 
     57         #encoder
---> 58         x1= self.dconv1(image)
     59         x2= self.maxpool_2x2(x1)
     60         x3= self.dconv2(x2)

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
   1100         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1101                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1102             return forward_call(*input, **kwargs)
   1103         # Do not call functions when jit is used
   1104         full_backward_hooks, non_full_backward_hooks = [], []

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\container.py in forward(self, input)
    139     def forward(self, input):
    140         for module in self:
--> 141             input = module(input)
    142         return input
    143 

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
   1100         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1101                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1102             return forward_call(*input, **kwargs)
   1103         # Do not call functions when jit is used
   1104         full_backward_hooks, non_full_backward_hooks = [], []

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\conv.py in forward(self, input)
    444 
    445     def forward(self, input: Tensor) -> Tensor:
--> 446         return self._conv_forward(input, self.weight, self.bias)
    447 
    448 class Conv3d(_ConvNd):

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\conv.py in _conv_forward(self, input, weight, bias)
    440                             weight, bias, self.stride,
    441                             _pair(0), self.dilation, self.groups)
--> 442         return F.conv2d(input, weight, bias, self.stride,
    443                         self.padding, self.dilation, self.groups)
    444 

RuntimeError: Given groups=1, weight of size [64, 1, 3, 3], expected input[1, 4, 215, 696] to have 1 channels, but got 4 channels instead"""

Getting this error. Not able to understand what the error is. How should reshape my tensor?