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hailin c8e8c1e9ff . 2025-09-20 16:09:34 +08:00
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api . 2025-09-20 16:09:34 +08:00
backends . 2025-09-20 16:09:34 +08:00
codegen . 2025-09-20 16:09:34 +08:00
cuda . 2025-09-20 16:09:34 +08:00
docs . 2025-09-20 16:09:34 +08:00
frontend . 2025-09-20 16:09:34 +08:00
ir . 2025-09-20 16:09:34 +08:00
mobile . 2025-09-20 16:09:34 +08:00
operator_upgraders . 2025-09-20 16:09:34 +08:00
passes . 2025-09-20 16:09:34 +08:00
python . 2025-09-20 16:09:34 +08:00
runtime . 2025-09-20 16:09:34 +08:00
serialization . 2025-09-20 16:09:34 +08:00
tensorexpr . 2025-09-20 16:09:34 +08:00
testing . 2025-09-20 16:09:34 +08:00
JIT-AUTOCAST.md . 2025-09-20 16:09:34 +08:00
OVERVIEW.md . 2025-09-20 16:09:34 +08:00
README.md . 2025-09-20 16:09:34 +08:00
jit_log.cpp . 2025-09-20 16:09:34 +08:00
jit_log.h . 2025-09-20 16:09:34 +08:00
jit_opt_limit.cpp . 2025-09-20 16:09:34 +08:00
jit_opt_limit.h . 2025-09-20 16:09:34 +08:00
resource_guard.h . 2025-09-20 16:09:34 +08:00

README.md

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.)