xref: /aosp_15_r20/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.h (revision b6fb3261f9314811a0f4371741dbb8839866f948)
1 /* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
2 
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6 
7     http://www.apache.org/licenses/LICENSE-2.0
8 
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15 
16 // This file defines the operations used in the MHLO dialect.
17 
18 #ifndef MLIR_HLO_DIALECT_MHLO_IR_HLO_OPS_H
19 #define MLIR_HLO_DIALECT_MHLO_IR_HLO_OPS_H
20 
21 #include "llvm/ADT/StringRef.h"
22 #include "mlir-hlo/Dialect/mhlo/IR/hlo_ops_base.h"
23 #include "mlir/Dialect/Quant/QuantTypes.h"
24 #include "mlir/Dialect/Shape/IR/Shape.h"
25 #include "mlir/IR/Attributes.h"
26 #include "mlir/IR/BuiltinTypes.h"
27 #include "mlir/IR/Dialect.h"
28 #include "mlir/IR/DialectImplementation.h"
29 #include "mlir/IR/Location.h"
30 #include "mlir/IR/MLIRContext.h"
31 #include "mlir/IR/OpDefinition.h"
32 #include "mlir/IR/Operation.h"
33 #include "mlir/IR/TypeUtilities.h"
34 #include "mlir/IR/Types.h"
35 #include "mlir/Interfaces/InferTypeOpInterface.h"
36 #include "mlir/Interfaces/SideEffectInterfaces.h"
37 
38 namespace mlir {
39 class OpBuilder;
40 
41 namespace mhlo {
42 
43 class MhloDialect : public Dialect {
44  public:
45   explicit MhloDialect(MLIRContext *context);
getDialectNamespace()46   static StringRef getDialectNamespace() { return "mhlo"; }
47 
48   // Registered hook to materialize a constant operation from a given attribute
49   // value with the desired resultant type.
50   Operation *materializeConstant(OpBuilder &builder, Attribute value, Type type,
51                                  Location loc) override;
52 
53   // Registered hook to verify region arg attributes on operations.
54   LogicalResult verifyRegionArgAttribute(mlir::Operation *op,
55                                          unsigned regionIndex,
56                                          unsigned argIndex,
57                                          mlir::NamedAttribute attr) override;
58 
59   // Registered hook to verify an attribute from this dialect on operations.
60   LogicalResult verifyOperationAttribute(mlir::Operation *op,
61                                          mlir::NamedAttribute attr) override;
62 
63   // Parses a type registered to this dialect.
64   Type parseType(DialectAsmParser &parser) const override;
65 
66   // Prints a type registered to this dialect.
67   void printType(Type type, DialectAsmPrinter &os) const override;
68 
69   // Parses an attribute registered to this dialect.
70   Attribute parseAttribute(DialectAsmParser &parser, Type type) const override;
71 
72   // Prints an attribute registered to this dialect.
73   void printAttribute(Attribute attr, DialectAsmPrinter &os) const override;
74 };
75 
76 class TokenType : public Type::TypeBase<TokenType, Type, TypeStorage> {
77  public:
78   using Base::Base;
79 };
80 
81 // Returns true if the given types are the same for the purposes of MHLO type
82 // inference, accounting for special properties of quantization and sparsity.
83 bool isCompatibleForMhloTypeInference(Type tp1, Type tp2);
84 
85 // Shape derivation function that computes the shape of the result based on an
86 // operand. For a 2-dimensional input tensor, this produces IR of the form
87 //
88 //  %0 = dim %arg0, 0 : memref<?x?xf32>
89 //  %1 = index_cast %0 : index to i64
90 //  %2 = dim %arg0, 1 : memref<?x?xf32>
91 //  %3 = index_cast %2 : index to i64
92 //  %4 = "mhlo.scalars_to_dimension_tensor"(%1, %3)
93 //    : (i64, i64) -> tensor<2xi64>
94 //
95 // and returns %4 as the shape value.
96 LogicalResult deriveShapeFromOperand(
97     OpBuilder *builder, Operation *op, Value operand,
98     SmallVectorImpl<Value> *reifiedReturnShapes);
99 
100 // Type derivation function that returns a tensor type with a new element type.
101 TensorType getSameShapeTensorType(TensorType tensorType, Type elementType);
102 
103 void printConvolutionDimensions(AsmPrinter &p, ConvDimensionNumbersAttr dnums);
104 void printConvolutionDimensions(AsmPrinter &p, Operation *,
105                                 ConvDimensionNumbersAttr dnums);
106 ParseResult parseConvolutionDimensions(AsmParser &parser,
107                                        ConvDimensionNumbersAttr &dnums);
108 
109 }  // end namespace mhlo
110 }  // end namespace mlir
111 
112 #define GET_OP_CLASSES
113 #include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h.inc"
114 
115 namespace mlir {
116 namespace mhlo {
117 
118 SortOp createSortOp(PatternRewriter *rewriter, const Location &loc,
119                     const llvm::ArrayRef<Value> &operands,
120                     const llvm::ArrayRef<Type> &elementTypes, int64_t dimension,
121                     bool isStable, ComparisonDirection direction);
122 
123 }  // end namespace mhlo
124 }  // end namespace mlir
125 
126 #endif  // MLIR_HLO_DIALECT_MHLO_IR_HLO_OPS_H
127