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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/40284 Adds graph mode handling for inplace hardswish, and test coverage for functional hardswish. Test Plan: ``` python test/test_quantization.py TestQuantizeScriptPTSQOps.test_hardswish ``` Imported from OSS Differential Revision: D22140628 fbshipit-source-id: 55a514f7dc1130d510f69ee4e611d7cb5e08d02e |
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| docs | ||
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| python | ||
| runtime | ||
| serialization | ||
| tensorexpr | ||
| testing | ||
| jit_log.cpp | ||
| jit_log.h | ||
| OVERVIEW.md | ||
| 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.)