mirror of https://github.com/llvm/torch-mlir
41 lines
1.4 KiB
TableGen
41 lines
1.4 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 TCP_BASE
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#define TCP_BASE
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include "mlir/IR/OpBase.td"
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def TCP_Dialect : Dialect {
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let name = "tcp";
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let cppNamespace = "::mlir::NPCOMP::tcp";
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let description = [{
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The `tcp` dialect is the gateway to MLIR's code generation infrastructure.
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It is also a great place to do algebraic transformations making use of
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semantically-charged named ops.
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Features:
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- Requires ranked tensors (except for a handful of special ops).
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- No implicit broadcasting.
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- Performance-critical parameters like convolution window sizes are represented
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with attributes.
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- Attention to detail modeling ops that are logically "pure" but have
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preconditions.
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Together these features allow a relatively large class of "common-sense"
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optimizations to be done with only modestly complex considerations.
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// TODO: consider having these ops take a "witness" argument
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// that makes them truly NoSideEffect?
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// Or have a totally pure "tcp.island" op?
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// Figure it out when doing the tcf to tcp lowering.
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}];
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}
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#endif // TCP_BASE
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