mirror of https://github.com/llvm/torch-mlir
119 lines
5.3 KiB
C++
119 lines
5.3 KiB
C++
//===----------------------------------------------------------------------===//
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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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// Also available under a BSD-style license. See LICENSE.
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//
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//===----------------------------------------------------------------------===//
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#include "torch-mlir/Dialect/TorchConversion/Transforms/Passes.h"
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#include "mlir/Conversion/Passes.h"
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#include "mlir/Dialect/Func/Transforms/Passes.h"
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#include "mlir/Dialect/Linalg/Passes.h"
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#include "mlir/Dialect/MemRef/Transforms/Passes.h"
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#include "mlir/Dialect/Tosa/Transforms/Passes.h"
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#include "mlir/Pass/PassManager.h"
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#include "mlir/Transforms/Passes.h"
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#include "torch-mlir/Conversion/TorchToLinalg/TorchToLinalg.h"
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#include "torch-mlir/Conversion/TorchToSCF/TorchToSCF.h"
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#include "torch-mlir/Conversion/TorchToStd/TorchToStd.h"
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#include "torch-mlir/Conversion/TorchToTMTensor/TorchToTMTensor.h"
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#include "torch-mlir/Conversion/TorchToTosa/TorchToTosa.h"
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#include "torch-mlir/Dialect/Torch/Transforms/Passes.h"
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using namespace mlir;
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using namespace mlir::torch;
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using namespace mlir::tosa;
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//===----------------------------------------------------------------------===//
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// Pass registration
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//===----------------------------------------------------------------------===//
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namespace {
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#define GEN_PASS_REGISTRATION
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#include "torch-mlir/Dialect/TorchConversion/Transforms/Passes.h.inc"
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} // end namespace
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void mlir::torch::registerTorchConversionPasses() {
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::registerPasses();
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mlir::PassPipelineRegistration<Torch::TorchLoweringPipelineOptions>(
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"torch-backend-to-linalg-on-tensors-backend-pipeline",
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"Pipeline lowering torch backend contract to linalg-on-tensors backend "
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"contract.",
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TorchConversion::createTorchBackendToLinalgOnTensorsBackendPipeline);
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mlir::PassPipelineRegistration<Torch::TorchLoweringPipelineOptions>(
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"torch-backend-to-tosa-backend-pipeline",
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"Pipeline lowering torch backend contract to TOSA backend "
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"contract.",
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TorchConversion::createTorchBackendToTosaBackendPipeline);
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}
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void TorchConversion::createTorchBackendToLinalgOnTensorsBackendPipeline(
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OpPassManager &pm, const Torch::TorchLoweringPipelineOptions &options) {
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// Check some invariants to catch errors in a clear way.
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pm.addPass(
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TorchConversion::createVerifyInvariantsBeforeBackendLoweringPass());
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// Lower to linalg + guards which is the input to codegen backends.
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// We do this first as it tends to involve pattern-matching against constants,
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// (e.g. dimensions which must be constant in a ranked programming model)
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// and those constants get somewhat obscured by TorchToStd.
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pm.addNestedPass<func::FuncOp>(createConvertTorchToTMTensorPass());
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pm.addNestedPass<func::FuncOp>(createConvertTorchToLinalgPass());
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pm.addNestedPass<func::FuncOp>(createConvertTorchToSCFPass());
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pm.addNestedPass<func::FuncOp>(createConvertTorchToStdPass());
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pm.addNestedPass<func::FuncOp>(memref::createExpandOpsPass());
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if (options.optimize) {
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// Clean up any non-canonical code introduced above..
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pm.addNestedPass<func::FuncOp>(createCanonicalizerPass());
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// Resolve `dim` ops on tensors (which currently live in the `memref`
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// dialect for some reason -- we don't have memrefs at this level).
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pm.addNestedPass<func::FuncOp>(
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memref::createResolveShapedTypeResultDimsPass());
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// The resolution of `dim` ops tends to create identical ops. CSE them.
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pm.addNestedPass<func::FuncOp>(createCSEPass());
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}
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// Finish the type conversion from `torch` types to the types of the
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// linalg-on-tensors backend contract.
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pm.addPass(TorchConversion::createFuncBackendTypeConversionPass());
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pm.addNestedPass<func::FuncOp>(
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TorchConversion::createFinalizingBackendTypeConversionPass());
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// Verify that we have lowered to the form that linalg on tensors backends
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// expect. This fails compilation (signalPassFailure) if the IR is not in the
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// correct form.
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pm.addPass(TorchConversion::createVerifyLinalgOnTensorsBackendContractPass());
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}
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void TorchConversion::createTorchBackendToTosaBackendPipeline(
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OpPassManager &pm, const Torch::TorchLoweringPipelineOptions &options) {
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// Check some invariants to catch errors in a clear way.
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pm.addPass(
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TorchConversion::createVerifyInvariantsBeforeBackendLoweringPass());
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pm.addNestedPass<func::FuncOp>(createConvertTorchToTosaPass());
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// Perform rank broadcasting so TosaToLinalg pass works
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pm.addNestedPass<func::FuncOp>(createTosaMakeBroadcastablePass());
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if (options.optimize) {
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// Clean up any non-canonical code introduced above..
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pm.addNestedPass<func::FuncOp>(createCanonicalizerPass());
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// The resolution of `dim` ops tends to create identical ops. CSE them.
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pm.addNestedPass<func::FuncOp>(createCSEPass());
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}
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// Finish the type conversion from `torch` types to the types of the
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// TOSA backend contract.
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pm.addPass(TorchConversion::createFuncBackendTypeConversionPass());
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pm.addNestedPass<func::FuncOp>(
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TorchConversion::createFinalizingBackendTypeConversionPass());
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// Verify that we have lowered to the form that TOSA backends
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// expect. This fails compilation (signalPassFailure) if the IR is not in the
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// correct form.
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pm.addPass(TorchConversion::createVerifyTosaBackendContractPass());
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}
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