Files

.ci
.circleci
.ctags.d
.devcontainer
.github
.vscode
android
aten
benchmarks
binaries
c10
caffe2
cmake
docs
- caffe2
- cpp
- source
  - _static
  - _templates
  - community
  - elastic
  - notes
  - rpc
  - scripts
  - amp.rst
  - autograd.rst
  - backends.rst
  - benchmark_utils.rst
  - bottleneck.rst
  - checkpoint.rst
  - complex_numbers.rst
  - cond.rst
  - conf.py
  - config_mod.rst
  - cpp_extension.rst
  - cpp_index.rst
  - cpu.rst
  - cuda._sanitizer.rst
  - cuda.rst
  - cudnn_persistent_rnn.rst
  - cudnn_rnn_determinism.rst
  - data.rst
  - ddp_comm_hooks.rst
  - deploy.rst
  - deterministic.rst
  - distributed.algorithms.join.rst
  - distributed.checkpoint.rst
  - distributed.elastic.rst
  - distributed.optim.rst
  - distributed.rst
  - distributed.tensor.parallel.rst
  - distributions.rst
  - dlpack.rst
  - docutils.conf
  - export.ir_spec.rst
  - export.rst
  - fft.rst
  - fsdp.rst
  - func.api.rst
  - func.batch_norm.rst
  - func.migrating.rst
  - func.rst
  - func.ux_limitations.rst
  - func.whirlwind_tour.rst
  - futures.rst
  - fx.rst
  - hub.rst
  - index.rst
  - jit.rst
  - jit_builtin_functions.rst
  - jit_language_reference.rst
  - jit_language_reference_v2.rst
  - jit_python_reference.rst
  - jit_unsupported.rst
  - jit_utils.rst
  - library.rst
  - linalg.rst
  - logging.rst
  - masked.rst
  - math-quantizer-equation.png
  - mobile_optimizer.rst
  - model_zoo.rst
  - monitor.rst
  - mps.rst
  - multiprocessing.rst
  - name_inference.rst
  - named_tensor.rst
  - nested.rst
  - nn.functional.rst
  - nn.init.rst
  - nn.rst
  - onnx.rst
  - onnx_dynamo.rst
  - onnx_dynamo_onnxruntime_backend.rst
  - onnx_torchscript.rst
  - onnx_torchscript_supported_aten_ops.rst
  - optim.rst
  - package.rst
  - pipeline.rst
  - profiler.rst
  - quantization-accuracy-debugging.rst
  - quantization-backend-configuration.rst
  - quantization-support.rst
  - quantization.rst
  - random.rst
  - rpc.rst
  - signal.rst
  - sparse.rst
  - special.rst
  - storage.rst
  - tensor_attributes.rst
  - tensor_view.rst
  - tensorboard.rst
  - tensors.rst
  - testing.rst
  - torch.ao.ns._numeric_suite.rst
  - torch.ao.ns._numeric_suite_fx.rst
  - torch.compiler.rst
  - torch.compiler_aot_inductor.rst
  - torch.compiler_api.rst
  - torch.compiler_best_practices_for_backends.rst
  - torch.compiler_cudagraph_trees.rst
  - torch.compiler_custom_backends.rst
  - torch.compiler_deepdive.rst
  - torch.compiler_dynamic_shapes.rst
  - torch.compiler_fake_tensor.rst
  - torch.compiler_faq.rst
  - torch.compiler_fine_grain_apis.rst
  - torch.compiler_get_started.rst
  - torch.compiler_guards_overview.rst
  - torch.compiler_inductor_profiling.rst
  - torch.compiler_ir.rst
  - torch.compiler_nn_module.rst
  - torch.compiler_performance_dashboard.rst
  - torch.compiler_profiling_torch_compile.rst
  - torch.compiler_transformations.rst
  - torch.compiler_troubleshooting.rst
  - torch.overrides.rst
  - torch.rst
  - torch_cuda_memory.rst
  - type_info.rst
  - utils.rst
- .gitignore
- Makefile
- README.md
- libtorch.rst
- make.bat
- requirements.txt
functorch
ios
modules
mypy_plugins
scripts
test
third_party
tools
torch
torchgen
.bazelignore
.bazelrc
.bazelversion
.buckconfig.oss
.clang-format
.clang-tidy
.cmakelintrc
.coveragerc
.dockerignore
.flake8
.gdbinit
.git-blame-ignore-revs
.gitattributes
.gitignore
.gitmodules
.isort.cfg
.lintrunner.toml
.lldbinit
.watchman
BUCK.oss
BUILD.bazel
CITATION.cff
CMakeLists.txt
CODEOWNERS
CODE_OF_CONDUCT.md
CONTRIBUTING.md
Dockerfile
GLOSSARY.md
LICENSE
MANIFEST.in
Makefile
NOTICE
README.md
RELEASE.md
SECURITY.md
WORKSPACE
aten.bzl
buckbuild.bzl
build.bzl
build_variables.bzl
c2_defs.bzl
c2_test_defs.bzl
defs.bzl
docker.Makefile
mypy-inductor.ini
mypy-strict.ini
mypy.ini
pt_ops.bzl
pt_template_srcs.bzl
pyproject.toml
pytest.ini
requirements-flake8.txt
requirements.txt
setup.py
ubsan.supp
ufunc_defs.bzl
version.txt

jit_builtin_functions.rst

and

facebook-github-bot

Lint trailing newlines (pytorch#54737 )

Mar 30, 2021

5bcbbf5 · Mar 30, 2021

TorchScript Builtins

This is a full reference of functions and Tensor methods accessible in TorchScript

.. automodule:: torch.jit.supported_ops