| /* Copyright 2022 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. |
| ==============================================================================*/ |
| #include <algorithm> |
| #include <string> |
| #include <tuple> |
| #include <utility> |
| |
| #include "llvm/ADT/StringRef.h" |
| #include "llvm/Support/SourceMgr.h" |
| #include "mlir/Dialect/Quant/QuantOps.h" // from @llvm-project |
| #include "mlir/IR/Builders.h" // from @llvm-project |
| #include "mlir/IR/BuiltinAttributes.h" // from @llvm-project |
| #include "mlir/IR/BuiltinTypes.h" // from @llvm-project |
| #include "mlir/IR/PatternMatch.h" // from @llvm-project |
| #include "mlir/Pass/Pass.h" // from @llvm-project |
| #include "mlir/Support/LogicalResult.h" // from @llvm-project |
| #include "mlir/Transforms/GreedyPatternRewriteDriver.h" // from @llvm-project |
| #include "tensorflow/compiler/mlir/quantization/tensorflow/passes/passes.h" |
| #include "tensorflow/compiler/mlir/tensorflow/ir/tf_dialect.h" |
| #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h" |
| |
| namespace mlir { |
| namespace quant { |
| namespace { |
| |
| class ConvertCustomAggregationOpToQuantStatsPass |
| : public PassWrapper<ConvertCustomAggregationOpToQuantStatsPass, |
| OperationPass<func::FuncOp>> { |
| public: |
| MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID( |
| ConvertCustomAggregationOpToQuantStatsPass) |
| |
| StringRef getArgument() const final { |
| // This is the argument used to refer to the pass in the textual format (on |
| // the commandline for example). |
| return "quant-convert-tf-custom-aggregator-op-to-quant-stats"; |
| } |
| |
| StringRef getDescription() const final { |
| // This is a brief description of the pass. |
| return "Convert tf.CustomAggregator op to quant.Stats"; |
| } |
| |
| void getDependentDialects(DialectRegistry ®istry) const override { |
| registry.insert<TF::TensorFlowDialect>(); |
| registry.insert<QuantizationDialect>(); |
| } |
| |
| void runOnOperation() override; |
| }; |
| |
| class ConvertCustomAggregationOpToQuantStats : public RewritePattern { |
| public: |
| // Does not take ownership of context, which must refer to a valid value that |
| // outlives this object. |
| explicit ConvertCustomAggregationOpToQuantStats(MLIRContext *context) |
| : RewritePattern(MatchAnyOpTypeTag(), /*benefit=*/1, context) {} |
| |
| LogicalResult matchAndRewrite(Operation *op, |
| PatternRewriter &rewriter) const override { |
| // Return early if the given operator isn't the custom aggregator op. |
| if (op->getName().getStringRef() != "tf.CustomAggregator") return failure(); |
| |
| FloatAttr min = op->getAttr("min").dyn_cast_or_null<FloatAttr>(); |
| FloatAttr max = op->getAttr("max").dyn_cast_or_null<FloatAttr>(); |
| |
| // When there are no min and max attributes, remove op. |
| if (min == nullptr || max == nullptr) { |
| op->replaceAllUsesWith(op->getOperands()); |
| rewriter.eraseOp(op); |
| return success(); |
| } |
| |
| // The layer stats contain only the first min/max pairs. |
| ElementsAttr layer_stats = DenseFPElementsAttr::get( |
| RankedTensorType::get({2}, rewriter.getF32Type()), |
| {static_cast<float>(min.getValueAsDouble()), |
| static_cast<float>(max.getValueAsDouble())}); |
| ElementsAttr axis_stats; |
| IntegerAttr axis; |
| |
| rewriter.replaceOpWithNewOp<StatisticsOp>(op, op->getOperand(0), |
| layer_stats, axis_stats, axis); |
| return success(); |
| } |
| }; |
| |
| static PassRegistration<ConvertCustomAggregationOpToQuantStatsPass> pass; |
| |
| void ConvertCustomAggregationOpToQuantStatsPass::runOnOperation() { |
| MLIRContext *ctx = &getContext(); |
| RewritePatternSet patterns(ctx); |
| func::FuncOp func = getOperation(); |
| |
| patterns.add<ConvertCustomAggregationOpToQuantStats>(ctx); |
| if (failed(applyPatternsAndFoldGreedily(func, std::move(patterns)))) { |
| func.emitError() |
| << "quant-convert-tf-custom-aggregator-op-to-quant-stats failed."; |
| signalPassFailure(); |
| } |
| } |
| |
| } // namespace |
| |
| std::unique_ptr<OperationPass<func::FuncOp>> |
| CreateConvertCustomAggregationOpToQuantStatsPass() { |
| return std::make_unique<ConvertCustomAggregationOpToQuantStatsPass>(); |
| } |
| |
| } // namespace quant |
| } // namespace mlir |