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Writing custom loss function in pytorch

Click here to download the full example code. When training neural networks, the most frequently used algorithm is back propagation. In this algorithm, parameters model weights are adjusted according to the gradient of the loss function with respect to the given parameter. To compute those gradients, PyTorch has a built-in differentiation engine called torch.
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