pytorch/torch/csrc/jit
Meghan Lele 3039d24f4a [JIT] Fix clang-tidy warnings for jit/frontend (#47982)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/47982

Test Plan: Imported from OSS

Reviewed By: ZolotukhinM

Differential Revision: D25258640

Pulled By: SplitInfinity

fbshipit-source-id: e2cf27130311904aa5b18e3232349604d01701a0
2020-12-02 12:35:28 -08:00
..
api [JIT] Fix clang-tidy warnings for jit/api (#47981) 2020-12-02 12:30:39 -08:00
backends [JIT] Add selective backend lowering API (#43613) 2020-10-30 00:37:33 -07:00
codegen fix nvrtc PTX architecture cap for CUDA toolkit (#48455) 2020-12-02 11:50:22 -08:00
docs [jit] update to serialization doc (#39025) 2020-06-05 17:49:08 -07:00
frontend [JIT] Fix clang-tidy warnings for jit/frontend (#47982) 2020-12-02 12:35:28 -08:00
ir [TorchScript] Support user defined classes as constants (#5062) 2020-11-16 20:52:02 -08:00
mobile Fix lite interpreter record function issue. (#47457) 2020-12-02 11:24:45 -08:00
passes [ONNX] Support nonzero(*, as_tuple=True) export (#47421) 2020-11-30 21:27:43 -08:00
python [TorchScript] Support user defined classes as constants (#5062) 2020-11-16 20:52:02 -08:00
runtime [PyTorch] Lazily construct guts of RecordFunction (#47550) 2020-12-01 13:07:17 -08:00
serialization Let JIT unpickler to accept CUDA DataPtr from read_record_ (#46827) 2020-12-01 14:09:09 -08:00
tensorexpr [numpy] torch.sigmoid : promote integer inputs to float (#47551) 2020-12-01 23:28:57 -08:00
testing Fix check highlight in filecheck. (#42417) 2020-08-03 18:49:22 -07:00
jit_log.cpp [jit] Speed up saving in case of many classes (#44589) 2020-09-15 15:10:45 -07:00
jit_log.h [JIT] Update comment in jit_log.h. (#46301) 2020-10-13 23:42:28 -07:00
OVERVIEW.md Fix grammar and spelling errors (#46713) 2020-10-23 01:31:17 -07:00
README.md
resource_guard.h

PyTorch JIT

This folder contains (most of) the C++ code for the PyTorch JIT, a language and compiler stack for executing PyTorch models portably and efficiently. To learn more about the JIT from a user perspective, please consult our reference documentation and tutorials.

A brief summary of the source tree:

  • OVERVIEW.md: High-level technical overview of the JIT.
  • frontend/: Taking PyTorch modules in Python and translating them into the JIT IR.
  • ir/: Core IR abstractions.
  • runtime/: Interpreter, graph execution, and JIT operators.
  • codegen/: Generating efficient, hardware-specific code for JIT subgraphs.
  • serialization/: Saving and loading modules.
  • api/: Any user-facing C++ or Python interfaces.
  • python/: Binding stuff into Python or accessing information from the Python environment.
  • testing/: Utilities and helpers for testing.
  • mobile/: Mobile-specific implementations of runtime components.
  • passes/: IR-to-IR passes, generally for optimization and lowering.
  • generated/: This folder is generated by the PyTorch build, and contains bindings for native PyTorch operators into the JIT.

Refer to each folder for more in-depth documentation.

Other relevant parts of the codebase not contained here:

  • aten/src/ATen/core: contains JIT code re-used by other elements of the runtime system (eager, mobile, etc.)