This is so frustrating…
I’m still getting an error, which doesn’t make a whole lot of sense considering the fact I turned the colored image into Grayscale.
Traceback (most recent call last):
  File "/Users/Josh/Desktop/convolutional_neural_networks/pytorch_convolutional_neural_network_mnist.py", line 243, in <module>
    check_image(transformed_image, model)
  File "/Users/Josh/Desktop/convolutional_neural_networks/pytorch_convolutional_neural_network_mnist.py", line 210, in check_image
    scores = model(image)
  File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
  File "/Users/Josh/Desktop/convolutional_neural_networks/pytorch_convolutional_neural_network_mnist.py", line 55, in forward
    x = activation_functions.relu(self.convolutional_input_layer(x))
  File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
  File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 349, in forward
    return self._conv_forward(input, self.weight)
  File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 345, in _conv_forward
    return F.conv2d(input, weight, self.bias, self.stride,
RuntimeError: Given groups=1, weight of size [8, 1, 3, 3], expected input[1, 3, 28, 28] to have 1 channels, but got 3 channels instead

Any help appreciated!