What is the relationship between PyTorch and Torch?

Here a short comparison on pytorch and torch. Torch: A Tensor library like numpy, unlike numpy it has strong GPU support.Lua is a wrapper for Torch (Yes! you need to have a good understanding of Lua), and for that you will need LuaRocks package manager. PyTorch: No need for the LuaRocks package manager, no need … Read more

How to initialize weights in PyTorch?

Single layer To initialize the weights of a single layer, use a function from torch.nn.init. For instance: Alternatively, you can modify the parameters by writing to conv1.weight.data (which is a torch.Tensor). Example: The same applies for biases: nn.Sequential or custom nn.Module Pass an initialization function to torch.nn.Module.apply. It will initialize the weights in the entire … Read more

No module named “Torch”

Try to install PyTorch using pip: First create a Conda environment using: Activate the environment using: Now install PyTorch using pip: Note: This will install both torch and torchvision. Now go to Python shell and import using the command:

Backward function in PyTorch

Please read carefully the documentation on backward() to better understand it. By default, pytorch expects backward() to be called for the last output of the network – the loss function. The loss function always outputs a scalar and therefore, the gradients of the scalar loss w.r.t all other variables/parameters is well defined (using the chain rule). Thus, by default, backward() is called on a scalar … Read more

Pytorch tensor to numpy array

There are 4 dimensions of the tensor you want to convert. : means that the first dimension should be copied as it is and converted, same goes for the third and fourth dimension. ::-1 means that for the second axes it reverses the the axes