143 lines
5.0 KiB
C++
143 lines
5.0 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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// This file defines the operations used in the LMHLO dialect.
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#include "mlir-hlo/Dialect/mhlo/IR/lhlo_ops.h"
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#include <assert.h>
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#include <stddef.h>
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#include <stdint.h>
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#include "llvm/ADT/APFloat.h"
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#include "llvm/ADT/APInt.h"
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#include "llvm/ADT/ArrayRef.h"
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#include "llvm/ADT/STLExtras.h"
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#include "llvm/ADT/SmallVector.h"
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#include "llvm/ADT/StringRef.h"
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#include "llvm/Support/FormatVariadic.h"
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#include "mlir-hlo/Dialect/mhlo/IR/lhlo_ops.h.inc"
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#include "mlir/IR/Attributes.h"
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#include "mlir/IR/Builders.h"
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#include "mlir/IR/Dialect.h"
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#include "mlir/IR/Location.h"
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#include "mlir/IR/MLIRContext.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/Operation.h"
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#include "mlir/IR/OperationSupport.h"
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#include "mlir/IR/PatternMatch.h"
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#include "mlir/IR/StandardTypes.h"
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#include "mlir/IR/TypeUtilities.h"
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#include "mlir/IR/Types.h"
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#include "mlir/IR/Value.h"
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namespace mlir {
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#include "mlir-hlo/Dialect/mhlo/IR/lhlo_ops_structs.cc.inc"
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namespace lmhlo {
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LmhloDialect::LmhloDialect(MLIRContext *context)
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: Dialect(getDialectNamespace(), context, TypeID::get<LmhloDialect>()) {
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addOperations<
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#define GET_OP_LIST
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#include "mlir-hlo/Dialect/mhlo/IR/lhlo_ops.cc.inc"
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>();
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}
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//===----------------------------------------------------------------------===//
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// StaticMemRefCastOp
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//===----------------------------------------------------------------------===//
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Value StaticMemRefCastOp::getViewSource() { return *getODSOperands(0).begin(); }
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static LogicalResult Verify(StaticMemRefCastOp op) {
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if (!op.operand().getType().cast<ShapedType>().hasStaticShape())
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return op.emitOpError("operand must have static shape");
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if (!op.getType().hasStaticShape())
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return op.emitOpError("result must have static shape");
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return success();
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}
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//===----------------------------------------------------------------------===//
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// DynamicMemRefCastOp
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//===----------------------------------------------------------------------===//
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Value DynamicMemRefCastOp::getViewSource() {
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return *getODSOperands(0).begin();
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}
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static LogicalResult Verify(DynamicMemRefCastOp op) {
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// Check if `sizes` and `strides` args are compatible with the result type.
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if (op.sizes().size() != op.getType().getRank())
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return op.emitOpError(
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"`sizes` args count must be equal to the rank of the output memref");
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return success();
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}
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//===----------------------------------------------------------------------===//
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// ReshapeMemrefCastOp
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//===----------------------------------------------------------------------===//
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Value ReshapeMemRefCastOp::getViewSource() { return operand(); }
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static LogicalResult Verify(ReshapeMemRefCastOp op) {
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Type operandType = op.operand().getType();
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Type resultType = op.result().getType();
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Type operandElementType = operandType.cast<ShapedType>().getElementType();
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Type resultElementType = resultType.cast<ShapedType>().getElementType();
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if (operandElementType != resultElementType)
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return op.emitOpError(
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"element types of source and destination memref "
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"types should be the same");
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if (auto operandMemRefType = operandType.dyn_cast<MemRefType>())
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if (!operandMemRefType.getAffineMaps().empty())
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return op.emitOpError(
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"operand memref type should have identity affine map");
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int64_t shapeSize = op.shape().getType().cast<MemRefType>().getDimSize(0);
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auto resultMemRefType = resultType.dyn_cast<MemRefType>();
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if (resultMemRefType) {
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if (shapeSize == ShapedType::kDynamicSize)
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return op.emitOpError(
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"cannot use shape operand with dynamic length to "
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"cast statically-ranked memref type");
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if (shapeSize != resultMemRefType.getRank())
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return op.emitOpError(
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"length of shape operand differs from the result's memref rank");
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if (!resultMemRefType.getAffineMaps().empty())
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return op.emitOpError(
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"result memref type should have identity affine map");
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}
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return success();
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}
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#define GET_OP_CLASSES
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#include "mlir-hlo/Dialect/mhlo/IR/lhlo_ops.cc.inc"
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// TODO(cheshire): Support folding, reuse code from hlo_ops.cc.
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void FusionOp::build(OpBuilder &builder, OperationState &result,
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ArrayRef<NamedAttribute> attributes) {
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result.addAttributes(attributes);
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Region *bodyRegion = result.addRegion();
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FusionOp::ensureTerminator(*bodyRegion, builder, result.location);
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}
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} // namespace lmhlo
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} // namespace mlir
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