Web Reference: It is useful when training a classification problem with C classes. If provided, the optional argument weight should be a 1D Tensor assigning weight to each of the classes. This is particularly useful when you have an unbalanced training set. Learn how to fix the common `TypeError` when using `cross_entropy_loss` in PyTorch by correctly handling your target tensor.---This video is based on the que... May 7, 2022 · There is a typo, I think you need out = self.l3(out) in def forward(). The issue is with the NeuralNet code specifically in the line: You are setting out to be the Linear layer instead of calling the linear layer on the data. Change it to out = self.l3(out) and it will work.
YouTube Excerpt: This guide provides insights into troubleshooting a common PyTorch error. Learn how to fix the `
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