mirror of
https://github.com/zebrajr/pytorch.git
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bfe1abd3b5
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/69567 This exposes torch.monitor events and stats via pybind11 to the underlying C++ implementation. * The registration interface is a tad different since it takes a lambda function in Python where as in C++ it's a full class. * This has a small amount of changes to the counter interfaces since there's no way to create an initializer list at runtime so they now also take a vector. * Only double based stats are provided in Python since it's intended more for high level stats where float imprecision shouldn't be an issue. This can be changed down the line if need arises. ``` events = [] def handler(event): events.append(event) handle = register_event_handler(handler) log_event(Event(type="torch.monitor.TestEvent", timestamp=datetime.now(), metadata={"foo": 1.0})) ``` D32969391 is now included in this diff. This cleans up the naming for events. type is now name, message is gone, and metadata is renamed data. Test Plan: buck test //caffe2/test:monitor //caffe2/test/cpp/monitor:monitor Reviewed By: kiukchung Differential Revision: D32924141 fbshipit-source-id: 563304c2e3261a4754e40cca39fc64c5a04b43e8
125 lines
3.2 KiB
ReStructuredText
125 lines
3.2 KiB
ReStructuredText
.. PyTorch documentation master file, created by
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sphinx-quickstart on Fri Dec 23 13:31:47 2016.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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:github_url: https://github.com/pytorch/pytorch
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PyTorch documentation
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===================================
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PyTorch is an optimized tensor library for deep learning using GPUs and CPUs.
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Features described in this documentation are classified by release status:
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*Stable:* These features will be maintained long-term and there should generally
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be no major performance limitations or gaps in documentation.
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We also expect to maintain backwards compatibility (although
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breaking changes can happen and notice will be given one release ahead
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of time).
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*Beta:* These features are tagged as Beta because the API may change based on
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user feedback, because the performance needs to improve, or because
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coverage across operators is not yet complete. For Beta features, we are
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committing to seeing the feature through to the Stable classification.
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We are not, however, committing to backwards compatibility.
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*Prototype:* These features are typically not available as part of
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binary distributions like PyPI or Conda, except sometimes behind run-time
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flags, and are at an early stage for feedback and testing.
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.. toctree::
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:glob:
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:maxdepth: 1
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:caption: Notes
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notes/*
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.. toctree::
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:maxdepth: 1
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:caption: Language Bindings
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cpp_index
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Javadoc <https://pytorch.org/javadoc/>
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torch::deploy <deploy>
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.. toctree::
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:maxdepth: 1
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:caption: Python API
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torch
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nn
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nn.functional
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tensors
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tensor_attributes
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tensor_view
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torch.autograd <autograd>
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cuda
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torch.cuda.amp <amp>
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torch.backends <backends>
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torch.distributed <distributed>
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torch.distributed.algorithms.join <distributed.algorithms.join>
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torch.distributed.elastic <distributed.elastic>
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torch.distributed.optim <distributed.optim>
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torch.distributions <distributions>
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torch.fft <fft>
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futures
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fx
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torch.hub <hub>
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torch.jit <jit>
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torch.linalg <linalg>
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torch.monitor <monitor>
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torch.special <special>
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torch.overrides
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torch.package <package>
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profiler
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nn.init
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onnx
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optim
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complex_numbers
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ddp_comm_hooks
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pipeline
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quantization
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rpc
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torch.random <random>
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sparse
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storage
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torch.testing <testing>
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torch.utils.benchmark <benchmark_utils>
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torch.utils.bottleneck <bottleneck>
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torch.utils.checkpoint <checkpoint>
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torch.utils.cpp_extension <cpp_extension>
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torch.utils.data <data>
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torch.utils.dlpack <dlpack>
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torch.utils.mobile_optimizer <mobile_optimizer>
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torch.utils.model_zoo <model_zoo>
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torch.utils.tensorboard <tensorboard>
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type_info
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named_tensor
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name_inference
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torch.__config__ <__config__>
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.. toctree::
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:maxdepth: 1
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:caption: Libraries
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torchaudio <https://pytorch.org/audio/stable>
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torchtext <https://pytorch.org/text/stable>
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torchvision <https://pytorch.org/vision/stable>
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TorchServe <https://pytorch.org/serve>
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PyTorch on XLA Devices <http://pytorch.org/xla/>
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.. toctree::
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:glob:
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:maxdepth: 1
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:caption: Community
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community/*
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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