| /* Copyright 2019 The TensorFlow Authors. All Rights Reserved. |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
| ==============================================================================*/ |
| |
| // This file defines the operations used in the standard MLIR TensorFlow dialect |
| // after control dependences are raise to the standard form. |
| |
| #ifndef TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_OPS_H_ |
| #define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_OPS_H_ |
| |
| #include "mlir/Dialect/Traits.h" // TF:local_config_mlir |
| #include "mlir/IR/Attributes.h" // TF:local_config_mlir |
| #include "mlir/IR/Builders.h" // TF:local_config_mlir |
| #include "mlir/IR/Dialect.h" // TF:local_config_mlir |
| #include "mlir/IR/Matchers.h" // TF:local_config_mlir |
| #include "mlir/IR/Module.h" // TF:local_config_mlir |
| #include "mlir/IR/OpDefinition.h" // TF:local_config_mlir |
| #include "mlir/IR/StandardTypes.h" // TF:local_config_mlir |
| #include "mlir/IR/TypeUtilities.h" // TF:local_config_mlir |
| #include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h" |
| |
| namespace mlir { |
| namespace TF { |
| |
| class TensorFlowDialect : public Dialect { |
| public: |
| TensorFlowDialect(MLIRContext *context); |
| |
| // Gradient attribute ("tf.gradient") in the list of NamedAttibutes in a |
| // function references to its gradient function. This attribute in TensorFlow |
| // Dialect is used to model TF GradientDef. GetGradientAttrName() returns the |
| // string description of gradient attribute. |
| static StringRef GetGradientAttrName() { return "tf.gradient"; } |
| |
| // This attribute marks if a function is stateful. |
| // Returns the string description of stateful attribute. |
| static StringRef GetStatefulAttrName() { return "tf.signature.is_stateful"; } |
| |
| // Parse a type registered to this dialect. |
| Type parseType(StringRef data, Location loc) const override; |
| |
| // Prints a type registered to this dialect. |
| void printType(Type ty, raw_ostream &os) const override; |
| |
| // Parse and print variant type. It may have subtypes inferred using shape |
| // inference. |
| Type ParseVariantType(StringRef spec, Location loc) const; |
| void PrintVariantType(VariantType ty, raw_ostream &os) const; |
| |
| // Registered hook to materialize a constant operation from a given attribute |
| // value with the desired resultant type. |
| Operation *materializeConstant(OpBuilder &builder, Attribute value, Type type, |
| Location loc) override; |
| }; |
| |
| // TODO(b/131258166): TensorFlow's mutex.h defines a `mutex_lock` macro, whose |
| // purpose is to catch bug on `tensorflow::mutex_lock`. We don't use |
| // `tensorflow::mutex_lock` here but we have ops (`tf.MutexLock` and |
| // `tf.ConsumeMutexLock`) with getter methods named as `mutex_lock()`. Need to |
| // undefine here to avoid expanding the getter symbol as macro when including |
| // both mutex.h and this header file. |
| #undef mutex_lock |
| |
| #define GET_OP_CLASSES |
| #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h.inc" |
| |
| } // namespace TF |
| } // namespace mlir |
| |
| #endif // TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_OPS_H_ |