Linear() in PyTorch
Linear() can get the 1D or more D tensor of the zero or more values computed by Affine transformation from […]
pytorch
Added advanced debugging features to my machine learning library like pytorch.
Added debug mode, debugging plot parameters, debugging layer gradients, deploying, fixed submodules of the library for my machine learning library
The loss functions in PyTorch
Buy Me a Coffee☕ *My post explains optimizers in PyTorch. A loss function is the function which can get the
float_power() in PyTorch
*My post explains square() and pow(). float_power() can get the 0D or more D tensor of the zero or more
square() and pow() in PyTorch
*My post explains float_power(). square() can get the 0D or more D tensor of squared zero or more elements, getting
cat() in PyTorch
*Memos: cat() can get the 1D or more D concatenated tensor of zero or more elements without one additional dimension
stack() in PyTorch
*Memos: stack() can get the 1D or more D concatenated tensor of zero or more elements with one additional dimension
tile() in PyTorch
tile() can repeat the zero or more elements of a 0D or more D tensor as shown below: *Memos: tile()
Deep Learning Workflow in PyTorch
Prepare data. Prepare (untrained) model. Train model. Evaluate model. Save model. 1. Prepare data. Get data like images, video, sound,
min(), max(), argmin() and argmax() in PyTorch
*Memos: min() can get the one or more minimum values of a 0D or more D tensor as shown below: