| /* Copyright 2021 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. |
| ==============================================================================*/ |
| |
| #ifndef TENSORFLOW_COMPILER_MLIR_XLA_TRANSFORMS_XLA_LEGALIZE_TF_PASSES_DETAIL_H_ |
| #define TENSORFLOW_COMPILER_MLIR_XLA_TRANSFORMS_XLA_LEGALIZE_TF_PASSES_DETAIL_H_ |
| |
| #include "mlir/Dialect/Arithmetic/IR/Arithmetic.h" |
| #include "mlir/Dialect/Func/IR/FuncOps.h" |
| #include "mlir/Dialect/MemRef/IR/MemRef.h" |
| #include "mlir/Dialect/Shape/IR/Shape.h" |
| #include "mlir/IR/Dialect.h" |
| #include "mlir/Pass/Pass.h" |
| #include "tensorflow/compiler/xla/mlir_hlo/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.h" |
| |
| namespace mlir { |
| namespace mhlo { |
| |
| #define GEN_PASS_CLASSES |
| #include "tensorflow/compiler/mlir/xla/transforms/xla_legalize_tf_passes.h.inc" |
| |
| } // namespace mhlo |
| } // namespace mlir |
| |
| #endif // TENSORFLOW_COMPILER_MLIR_XLA_TRANSFORMS_XLA_LEGALIZE_TF_PASSES_DETAIL_H_ |