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torch-mlir/include/npcomp/E2E/Passes.td

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Initial TCF/TCP E2E seed. Very much WIP. This is enough to get tcf.add down to approximately the "linalg.generic on buffers" level of abstraction. (but there are nuances)
2020-05-07 09:41:54 +08:00
//===-- Passes.td - Pass definition file -------------------*- tablegen -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#ifndef NPCOMP_E2E_PASSES
#define NPCOMP_E2E_PASSES
include "mlir/Pass/PassBase.td"
def LowerLinalgOnTensorToLinalgOnMemref :
Pass<"lower-linalg-tensor-to-memref", "FuncOp"> {
let summary = "Lowers linalg on tensors to linalg on memrefs";
let constructor = "mlir::NPCOMP::createLowerLinalgOnTensorToLinalgOnMemrefPass()";
}
def LowerBroadcastToToLoops :
Pass<"lower-broadcast-to-to-loops", "FuncOp"> {
let summary = "Lower tcp::BroadcastTo to loops.";
let constructor = "mlir::NPCOMP::createLowerBroadcastToToLoopsPass()";
}
def ResolveShapeOfOps : Pass<"resolve-shape-of-ops", "FuncOp"> {
let summary = "Resolve shape.shape_of ops to other shapes.";
let constructor = "mlir::NPCOMP::createResolveShapeOfOpsPass()";
}
"Finish" tensor -> memref conversion. There's a lot of details to flesh out here, but the basic approach seems promising (see comments in createE2ELoweringPipeline). This approach will be put to the test when we try to do our first fusions since that tickles some of the nasty phase ordering issues involved here. But we're not there yet.
2020-05-12 05:24:57 +08:00
def ResolveTensorLoadStoreOps : Pass<"resolve-tensor-load-store-ops", "FuncOp"> {
let summary = "Resolve tensor_load/tensor_store ops";
let constructor = "mlir::NPCOMP::createResolveTensorLoadStoreOpsPass()";
}
Add lowering from linalg to loops. This also adds a small pass to clean up the `dim` ops that linalg introduces. For now, it only has a trivial pattern that looks for a `tcp.alloc_memref(%shape)` op to get the shape as we currently have an invariant that all memrefs are the result of such ops. But eventually this will need to look through view ops and any other shape-ish stuff that linalg introduces as it lowers to loops, along with any slicing ops introduced by buffer allocation.
2020-05-12 09:50:51 +08:00
def LowerLinalgLoopDimOps : Pass<"lower-linalg-loop-dim-ops", "FuncOp"> {
let summary = "Lower dim ops introduced by linalg to loops lowering";
let constructor = "mlir::NPCOMP::createLowerLinalgLoopDimOpsPass();";
}
Initial TCF/TCP E2E seed. Very much WIP. This is enough to get tcf.add down to approximately the "linalg.generic on buffers" level of abstraction. (but there are nuances)
2020-05-07 09:41:54 +08:00
#endif // NPCOMP_E2E_PASSES