| /* 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 "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 { |
| |
| constexpr char kCustomAggregatorOpName[] = "tf.CustomAggregator"; |
| |
| class InsertCustomAggregationOpsPass |
| : public PassWrapper<InsertCustomAggregationOpsPass, |
| OperationPass<func::FuncOp>> { |
| public: |
| MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(InsertCustomAggregationOpsPass) |
| |
| 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-insert-custom-aggregation-ops"; |
| } |
| |
| StringRef getDescription() const final { |
| // This is a brief description of the pass. |
| return "Insert custom aggregation ops for the calibration procedure"; |
| } |
| |
| void getDependentDialects(DialectRegistry ®istry) const override { |
| registry.insert<TF::TensorFlowDialect>(); |
| } |
| |
| void runOnOperation() override; |
| }; |
| |
| static PassRegistration<InsertCustomAggregationOpsPass> pass; |
| |
| class AddCustomAggregationOp : public RewritePattern { |
| public: |
| // Does not take ownership of context, which must refer to a valid value that |
| // outlives this object. |
| explicit AddCustomAggregationOp(MLIRContext *context) |
| : RewritePattern(MatchAnyOpTypeTag(), /*benefit=*/1, context) {} |
| |
| LogicalResult matchAndRewrite(Operation *op, |
| PatternRewriter &rewriter) const override { |
| // Return early if the given operator is the custom aggregator op. |
| if (op->getName().getStringRef() == kCustomAggregatorOpName) |
| return failure(); |
| |
| bool mutated = false; |
| for (Value input : op->getOperands()) { |
| Type element_type = getElementTypeOrSelf(input.getType()); |
| // Non-float cases won't be calibrated. |
| if (!element_type.isF32()) { |
| continue; |
| } |
| // Skip when there is any already existing StatisticsOp found. |
| Operation *defining_op = input.getDefiningOp(); |
| if (defining_op != nullptr && |
| defining_op->getName().getStringRef() == kCustomAggregatorOpName) { |
| continue; |
| } |
| |
| // Skip calibration when the given operand comes from a constant. |
| if (defining_op != nullptr && detail::isConstantLike(defining_op)) { |
| continue; |
| } |
| |
| SmallVector<NamedAttribute, 1> attributes{ |
| rewriter.getNamedAttr("id", rewriter.getStringAttr(""))}; |
| |
| // Insert custom aggregation op between operand and operator. |
| rewriter.setInsertionPointAfterValue(input); |
| // ID attribute will have empty value for now. |
| OperationState state( |
| op->getLoc(), kCustomAggregatorOpName, /*operands=*/ValueRange{input}, |
| /*types=*/TypeRange{input.getType()}, /*attributes=*/attributes); |
| Operation *aggregator_op = Operation::create(state); |
| rewriter.insert(aggregator_op); |
| Value aggregator_op_result = aggregator_op->getOpResult(0); |
| input.replaceAllUsesWith(aggregator_op_result); |
| aggregator_op->replaceUsesOfWith(aggregator_op_result, input); |
| |
| // Mark mutated. |
| mutated = true; |
| } |
| |
| // Return failure when there is no matching operand. |
| return mutated ? success() : failure(); |
| } |
| }; |
| |
| void InsertCustomAggregationOpsPass::runOnOperation() { |
| MLIRContext *ctx = &getContext(); |
| RewritePatternSet patterns(ctx); |
| func::FuncOp func = getOperation(); |
| |
| patterns.add<AddCustomAggregationOp>(ctx); |
| if (failed(applyPatternsAndFoldGreedily(func, std::move(patterns)))) { |
| func.emitError() << "quant-insert-custom-aggregation-ops failed."; |
| signalPassFailure(); |
| } |
| } |
| |
| } // namespace |
| |
| std::unique_ptr<OperationPass<func::FuncOp>> |
| CreateInsertCustomAggregationOpsPass() { |
| return std::make_unique<InsertCustomAggregationOpsPass>(); |
| } |
| |
| } // namespace quant |
| } // namespace mlir |