Pytorch – Inferring linear layer in_features

by

As of 1.8, PyTorch now has LazyLinear which infers the input dimension:

A torch.nn.Linear module where in_features is inferred.

More Related Contents:

  1. Best way to save a trained model in PyTorch? [closed]
  2. Why `torch.cuda.is_available()` returns False even after installing pytorch with cuda?
  3. How do I save a trained model in PyTorch?
  4. How to initialize weights in PyTorch?
  5. How do I initialize weights in PyTorch?
  6. Why do we need to call zero_grad() in PyTorch?
  7. What does model.train() do in PyTorch?
  8. How does Pytorch’s “Fold” and “Unfold” work?
  9. Heroku: slug size too large after installing Pytorch
  10. What does model.eval() do in pytorch?
  11. PyTorch NotImplementedError in forward
  12. PyTorch: How to use DataLoaders for custom Datasets
  13. Pytorch – RuntimeError: Trying to backward through the graph a second time, but the buffers have already been freed
  14. How do I print the model summary in PyTorch?
  15. What’s the difference between reshape and view in pytorch?
  16. ModuleNotFoundError: No module named ‘tools.nnwrap’
  17. How do I check if PyTorch is using the GPU?
  18. How do I visualize a net in Pytorch?
  19. Pytorch RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0
  20. Is .data still useful in pytorch?
  21. Pytorch: how to add L1 regularizer to activations?
  22. How to construct a network with two inputs in PyTorch
  23. RuntimeError: Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same
  24. How can I fix this strange error: “RuntimeError: CUDA error: out of memory”?
  25. Data Augmentation in PyTorch
  26. How do I split a custom dataset into training and test datasets?
  27. RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! when resuming training
  28. Install PyTorch from requirements.txt
  29. Pytorch ValueError: optimizer got an empty parameter list
  30. PyTorch Binary Classification – same network structure, ‘simpler’ data, but worse performance?

Leave a Comment