mirror of https://github.com/llvm/torch-mlir
42 lines
1.6 KiB
TableGen
42 lines
1.6 KiB
TableGen
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//===-------------------------------------------------------*- tablegen -*-===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#ifndef TORCH_BASE
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#define TORCH_BASE
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include "mlir/IR/OpBase.td"
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def Torch_Dialect : Dialect {
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let name = "torch";
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let cppNamespace = "::mlir::NPCOMP::Torch";
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let description = [{
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Top-level dialect for interfacing PyTorch and MLIR.
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This dialect contains types and structural ops that model enough of
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PyTorch's behavior to allow for easy import/call-out. While not aiming to
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be completely isomorphic, it is laid out to make conversion in/out
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systematic for the supported features (some of which are aspirational):
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- Transitions between mutable and immutable tensors.
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- Gradient associations and management.
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- Custom ops.
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- Types specific to PyTorch.
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- Module level constructs like quantization parameters, globals, etc.
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Where possible, this dialect composes with types and ops from the `Numpy`
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and `Basicpy` dialects, and those dialects should be considered "upstream"
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for basic Python and ND-Array based programming constructs.
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As a key point, this dialect does not contain any custom operations,
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including those that people would typically associate as core (see
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the `ATen` dialect for mathematical ops like add, conv, etc), instead
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modeling the open op-system that PyTorch reasons about natively.
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}];
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}
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#endif // TORCH_BASE
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