| /* Copyright 2020 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_TFR_IR_TFR_PASSES_H_ |
| #define TENSORFLOW_COMPILER_MLIR_TFR_IR_TFR_PASSES_H_ |
| |
| #include "llvm/ADT/None.h" |
| #include "llvm/ADT/Optional.h" |
| #include "mlir/Dialect/Func/IR/FuncOps.h" // from @llvm-project |
| #include "mlir/IR/BuiltinOps.h" // from @llvm-project |
| #include "mlir/Pass/Pass.h" // from @llvm-project |
| #include "mlir/Support/LogicalResult.h" // from @llvm-project |
| |
| namespace mlir { |
| namespace TFR { |
| |
| // Scans the func op and adds all the canonicalization patterns of the ops |
| // except the tf ops, inside the function. |
| void populateCanonicalizationPatterns(func::FuncOp func, |
| RewritePatternSet &patterns); |
| |
| // Decompose ops. |
| std::unique_ptr<OperationPass<func::FuncOp>> CreateDecomposeTFOpsPass( |
| llvm::Optional<ModuleOp> tfr_module = llvm::None); |
| |
| // Rewrites quantized operands and results with their storage types. |
| // This pass should be run at module level after decomposition, if there are |
| // quantized operands or results. |
| std::unique_ptr<OperationPass<ModuleOp>> CreateRewriteQuantizedIOPass(); |
| |
| // Raise to TF ops. |
| std::unique_ptr<OperationPass<func::FuncOp>> CreateRaiseToTFOpsPass( |
| llvm::Optional<ModuleOp> tfr_module = llvm::None, |
| bool materialize_derived_attrs = false); |
| |
| } // namespace TFR |
| } // namespace mlir |
| |
| #endif // TENSORFLOW_COMPILER_MLIR_TFR_IR_TFR_PASSES_H_ |