PyTorch - Packages in torch & torchvision
Packages in torch
PyTorch Documentation: https://pytorch.org/docs/stable/index.html
To learn how to use PyTorch, we can start from knowing what does it contain.
Here we list out modules in torch package and torchvision package.
torch package contain data structure and mathematical operations for multi-dimensional tensors. Some useful utilities are also included (random & sampling, serialization, get/set basic config in parallelism, disable/enable gradient computation).
Tensor
Multi-dimensional matrix containing elements of a single data type.(It contains not only data structure for tensor but also many tensor attributes and type information)
sparse (experimental API)
Spare tensor in Coordinate Format (COO).https://scipy-lectures.org/advanced/scipy_sparse/coo_matrix.html
cuda
Support for CUDA tensor typesStorage
Contiguous 1D array of single data type.nn
Neural network modules (parameters, containers, layers, utilities).nn.functional
Common used functions in neural network.nn.init
Common functions to initialize tensor.optim
Common optimization algorithms.autograd
Classes and functinos implementing automatic differentiation of arbitrary scalar valued functions.distributed
Distributed communication backend.distributions
Parameterizable probability distributions and sampling functions.hub
Pre-trained model repository.jit
PyTorch JIT compiler support. (create serializable and optimizable models from PyTorch code by TorchScript)multiprocessing
A wrapper around the native Python multiprocessing module. (manage multiple process and shared memory)random
Config random number generator.utils.bottleneck
Tool to summarize runs of your script with Python profiler and PyTorch's autograd profiler.utils.checkpoint
Modules to trade compute for memory (to save memory).https://blog.csdn.net/ONE_SIX_MIX/article/details/93937091
utils.cpp_extension
Build and distribute Python (PyTorch) package to C++ or CUDA extension.https://pytorch.org/tutorials/advanced/cpp_extension.html
utils.data
Data loading utility.utils.dlpack
Convert between dlpack (standard to store tensor) and tensor.utils.model_zoo
Moved to torch.hub.utils.tensorboard
Visualize PyTorch models and metrics within TensorBoard UI.utils.onnx
Export PyTorch model to ONNX.For import, https://github.com/pytorch/pytorch/issues/21683