This is my implementation of mini-pytorch from scratch.
I followed tutorial in Cornell CS5781: Machine Learning Engineering to finish this project.
- tensor
- tuple index
- auto broadcast
- reshape, view, permute
- auto-diff and backpropagation
- various operators and tensor functions
- nn
- conv1d
- conv2d
- dropout
- pooling
- Linear
- various nonlinear activations
- module
- parameter
- tensor ops
- map
- zip
- reduce
- acceleration
- cpu: fast ops-parallel computation
- gpu: cuda ops
1.train process
2.loss change
3.tensor graph
