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Convert following compiler rst files to md file. 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 Fixes #155039 Pull Request resolved: https://github.com/pytorch/pytorch/pull/155335 Approved by: https://github.com/svekars Co-authored-by: Svetlana Karslioglu <svekars@meta.com>
39 lines
1.3 KiB
Markdown
39 lines
1.3 KiB
Markdown
# IRs
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PyTorch 2.0 offers two set of IRs for backends to interface with: Core Aten IR and Prims IR.
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## Core Aten IR
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Core aten ops is the core subset of aten operators that can be used to compose other operators.
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Core aten IR is fully functional, and there is no `inplace` or `_out` variants in this opset.
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In contrast to Prims IR, core aten ops reuses the existing aten ops in "native_functions.yaml",
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and it doesn't further decompose ops into explicit type promotion and broadcasting ops.
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This opset is designed to serve as the functional IR to interface with backends.
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```{warning}
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This opset is still under active development, more ops will be added in the future.
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```
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```{csv-table}
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:file: ../build/ir/aten_ops.csv
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:widths: auto
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:header-rows: 1
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```
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## Prims IR
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Prims IR is a set of primitive operators that can be used to compose other operators.
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Prims IR is a lower level opset than core aten IR, and it further decomposes ops into explicit
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type promotion and broadcasting ops: prims.convert_element_type and prims.broadcast_in_dim.
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This opset is designed to interface with compiler backends.
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```{warning}
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This opset is still under active development, more ops will be added in the future.
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```
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```{csv-table}
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:file: ../build/ir/prims_ops.csv
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:widths: auto
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:header-rows: 1
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```
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