PyTorch: 100 Tips and Techniques to Master Deep Learning in Python

Photo by Solen Feyissa on Unsplash

Here are 100 tips for working with PyTorch, a popular deep learning framework in Python:

1. Basics of PyTorch:

1. Import PyTorch with import torch.
2. Install PyTorch using pip install torch.
3. Create a tensor using torch.tensor().
4. Convert a NumPy array to a PyTorch tensor with torch.from_numpy().
5. Check the size of a tensor with tensor.size().
6. Access the shape of a tensor with tensor.shape.
7. Perform element-wise operations with tensors.
8. Use torch.cuda.is_available() to check for GPU availability.
9. Move tensors to the GPU using tensor.to('cuda').

2. Tensor Operations:

1. Use torch.add() for element-wise addition.
2. Perform matrix multiplication with torch.mm() or @ operator.
3. Transpose a matrix with tensor.t() or tensor.transpose().
4. Reshape a tensor with tensor.view().
5. Use torch.unsqueeze() to add a new dimension to a tensor.
6. Flatten a tensor with torch.flatten() or tensor.view(-1).