PyTorch Article FEATURED Free Cheat Sheet. Over the past months, I have been gathering all the cheat sheets for Python, Machine Learning, and Data Science. Keras is an easy-to-use and powerful library for Theano and TensorFlow that provides a high-level neural networks API to develop and evaluate deep learning models. We recently launched one of the first online interactive deep learning course using Keras 2.0, called 'Deep Learning in Python'.Now, DataCamp has created a Keras cheat sheet for those who have already taken the course and that. A cheat sheet for porting batch normalization from TF model to Pytorch Param Mapping bn/gamma → bn.weight bn/beta → bn.bias bn/movingmean → bn.runningmean bn/movingvariance → bn.runningvar mean and variance are not trainable params, we will need to read them in for inference. Eps Also set eps explicitly to 1e-3 if you are using tf default as default in pytorch is 1e-5.
Imports¶
General¶
Neural Network API¶
See autograd,nn,functionaland optim
Torchscript and JIT¶
See Torchscript App remote control for mac.
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ONNX¶
Forklift. See onnx
Vision¶
Seetorchvision
Distributed Training¶
Pytorch Documentation Pdf
See distributedandmultiprocessing
Tensors¶
Creation¶
See tensor
Dimensionality¶
See tensor
Algebra¶
See mathoperations
GPU Usage¶
See cuda
Deep Learning¶
See nn
Loss Functions¶
Pytorch Cheat Sheet Online
See lossfunctions
Activation Functions¶
See activationfunctions
Optimizers¶
See optimizers
Learning rate scheduling¶
Pytorch Cheat Sheet Pdf
See learning ratescheduler
Data Utilities¶
Datasets¶
Seedatasets
Dataloaders and DataSamplers¶
Seedataloader
Also see¶
Pytorch Cheat Sheet 2019
Deep Learning with PyTorch: A 60 MinuteBlitz(pytorch.org)
PyTorch Forums(discuss.pytorch.org)
PyTorch for Numpyusers(github.com/wkentaro/pytorch-for-numpy-users)