mirror of https://github.com/llvm/torch-mlir
107 lines
3.9 KiB
C++
107 lines
3.9 KiB
C++
//===------------------------------------------------------------*- C++ -*-===//
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//
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// This file is licensed 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 NPCOMP_DIALECT_TORCH_IR_TORCHOPS_H
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#define NPCOMP_DIALECT_TORCH_IR_TORCHOPS_H
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#include "mlir/IR/BuiltinTypes.h"
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#include "mlir/IR/OpDefinition.h"
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#include "mlir/IR/OpImplementation.h"
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#include "mlir/IR/SymbolTable.h"
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#include "mlir/Interfaces/CastInterfaces.h"
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#include "mlir/Interfaces/ControlFlowInterfaces.h"
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#include "mlir/Interfaces/InferTypeOpInterface.h"
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#include "mlir/Interfaces/SideEffectInterfaces.h"
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#include "npcomp/Dialect/Torch/IR/TorchTraits.h"
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#include "npcomp/Dialect/Torch/IR/TorchTypes.h"
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#include "npcomp/Interfaces/Traits.h"
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#define GET_OP_CLASSES
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#include "npcomp/Dialect/Torch/IR/TorchOps.h.inc"
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namespace mlir {
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namespace NPCOMP {
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namespace Torch {
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/// Create code to copy `tensor` to type `newType`.
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///
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/// This involves two independent steps, which we keep orthogonal in our
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/// IR representation.
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/// 1. Adding/removing static information about sizes/dtype.
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/// 2. Performing the copy, which allows us to add/remove value semantics.
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Value copyTensorToType(OpBuilder &builder, Location loc, BaseTensorType newType,
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Value tensor);
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} // namespace Torch
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} // namespace NPCOMP
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} // namespace mlir
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template <> struct llvm::DenseMapInfo<::mlir::NPCOMP::Torch::SlotOp> {
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using SlotOp = ::mlir::NPCOMP::Torch::SlotOp;
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static SlotOp getEmptyKey() {
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auto *pointer = llvm::DenseMapInfo<void *>::getEmptyKey();
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return SlotOp::getFromOpaquePointer(pointer);
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}
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static SlotOp getTombstoneKey() {
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auto *pointer = llvm::DenseMapInfo<void *>::getTombstoneKey();
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return SlotOp::getFromOpaquePointer(pointer);
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}
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static unsigned getHashValue(SlotOp val) {
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return hash_value(val.getAsOpaquePointer());
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}
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static bool isEqual(SlotOp lhs, SlotOp rhs) { return lhs == rhs; }
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};
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template <> struct llvm::DenseMapInfo<::mlir::NPCOMP::Torch::NnModuleOp> {
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using NnModuleOp = ::mlir::NPCOMP::Torch::NnModuleOp;
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static NnModuleOp getEmptyKey() {
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auto *pointer = llvm::DenseMapInfo<void *>::getEmptyKey();
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return NnModuleOp::getFromOpaquePointer(pointer);
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}
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static NnModuleOp getTombstoneKey() {
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auto *pointer = llvm::DenseMapInfo<void *>::getTombstoneKey();
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return NnModuleOp::getFromOpaquePointer(pointer);
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}
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static unsigned getHashValue(NnModuleOp val) {
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return hash_value(val.getAsOpaquePointer());
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}
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static bool isEqual(NnModuleOp lhs, NnModuleOp rhs) { return lhs == rhs; }
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};
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template <> struct llvm::DenseMapInfo<::mlir::NPCOMP::Torch::ClassTypeOp> {
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using ClassTypeOp = ::mlir::NPCOMP::Torch::ClassTypeOp;
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static ClassTypeOp getEmptyKey() {
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auto *pointer = llvm::DenseMapInfo<void *>::getEmptyKey();
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return ClassTypeOp::getFromOpaquePointer(pointer);
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}
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static ClassTypeOp getTombstoneKey() {
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auto *pointer = llvm::DenseMapInfo<void *>::getTombstoneKey();
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return ClassTypeOp::getFromOpaquePointer(pointer);
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}
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static unsigned getHashValue(ClassTypeOp val) {
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return hash_value(val.getAsOpaquePointer());
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}
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static bool isEqual(ClassTypeOp lhs, ClassTypeOp rhs) { return lhs == rhs; }
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};
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template <> struct llvm::DenseMapInfo<::mlir::NPCOMP::Torch::GlobalSlotOp> {
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using OpTy = ::mlir::NPCOMP::Torch::GlobalSlotOp;
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static OpTy getEmptyKey() {
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auto *pointer = llvm::DenseMapInfo<void *>::getEmptyKey();
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return OpTy::getFromOpaquePointer(pointer);
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}
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static OpTy getTombstoneKey() {
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auto *pointer = llvm::DenseMapInfo<void *>::getTombstoneKey();
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return OpTy::getFromOpaquePointer(pointer);
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}
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static unsigned getHashValue(OpTy val) {
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return hash_value(val.getAsOpaquePointer());
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}
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static bool isEqual(OpTy lhs, OpTy rhs) { return lhs == rhs; }
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};
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#endif // NPCOMP_DIALECT_TORCH_IR_TORCHOPS_H
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