How Can You Use Torch.Matmul to Achieve Convolution Backward Pass?
In the rapidly evolving field of deep learning, understanding the mechanics behind convolutional neural networks (CNNs) is crucial for both researchers and practitioners. One fundamental aspect of CNNs is the backward pass of convolution operations, which is essential for training models via gradient descent. Traditionally, convolution backward computations can be complex and computationally intensive, often…