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tensorflow/compiler/mlir/quantization/tensorflow/passes/propagate_quantize_type.cc
if (failed(applyPatternsAndFoldGreedily(func, frozen_patterns))) { func.emitError() << "quant-propagate-quantize-type failed."; signalPassFailure(); } } } } // namespace // Creates an instance of the TensorFlow dialect PropagateQuantizeType pass. std::unique_ptr<OperationPass<ModuleOp>> CreatePropagateQuantizeTypePass() { return std::make_unique<PropagateQuantizeType>(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize_batch_matmul.cc
if (constant.getType().getRank() != 2) return failure(); // Create a tfl.transpose op that performs ZX transpose on `input`. auto create_z_x_transpose_op = [&](Value input) -> Value { RankedTensorType input_type = mlir::cast<RankedTensorType>(input.getType()); const int input_rank = input_type.getRank(); // Create a 1D I32 tensor for representing the dimension permutation.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 9.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/nchw_convolution_to_nhwc.cc
Value input = op->getOperand(0); const TensorType new_input_tensor_type = GetTransposedTensorType( mlir::cast<TensorType>(input.getType()), kNchwToNhwcPermutation); auto input_transpose_op = rewriter.create<mlir::stablehlo::TransposeOp>( op.getLoc(), /*resultType0=*/new_input_tensor_type, /*operand=*/input, rewriter.getDenseI64ArrayAttr(kNchwToNhwcPermutation));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/decompose_hybrid_quantization.cc
if (QuantizedType::getQuantizedElementType(operand.getType())) { auto newTy = QuantizedType::castToExpressedType(operand.getType()); newOperands.push_back( rewriter.create<TFL::DequantizeOp>(loc, newTy, operand)); continue; } newOperands.push_back(operand); } SmallVector<Type> newResultTys; for (auto result : op->getResults()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_globals_to_ml_program.cc
if (globalTensor.getValue()) { initial_value = *globalTensor.getValue(); } else { initial_value = mlir::Attribute(); } opToName[globalTensor] = name; auto variableOp = globalBuilder.create<ml_program::GlobalOp>( globalTensor.getLoc(), name, globalTensor.getType(), globalTensor.getIsMutable(), initial_value, /*visibility=*/globalBuilder.getStringAttr("private"));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/debug/debug_test.cc
return registry; }()) { context_.loadAllAvailableDialects(); mlir::OpBuilder builder(&context_); module_ = builder.create<mlir::ModuleOp>(builder.getUnknownLoc()); builder.setInsertionPointToStart(module_->getBody()); auto func = builder.create<mlir::func::FuncOp>( // builder.getUnknownLoc(), "main", builder.getFunctionType({}, {})); func->setAttr("tfl.func", builder.getUnitAttr());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 17 11:15:16 UTC 2024 - 9.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/odml_converter/folders.cc
namespace { // Helper class for parsing operands to a foldable operation. class FoldAdaptor { public: // Returns std::nullopt if the operation cannot be folded. static std::optional<FoldAdaptor> Create(Operation* operation) { auto foldable_opr = [](Value val) -> bool { return !llvm::isa<BlockArgument>(val) && llvm::isa<stablehlo::ConstantOp>(val.getDefiningOp()); };
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 06:11:55 UTC 2024 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_lowering_pass.cc
std::move(patterns)))) { getOperation().emitError("Composite lowering pass failed."); signalPassFailure(); } } } // namespace // Creates an instance of the pass. std::unique_ptr<OperationPass<ModuleOp>> CreateCompositeLoweringPass() { return std::make_unique<CompositeLoweringPass>(); } // Registers the pass implementation
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:16:05 UTC 2024 - 3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_stablehlo_custom_call_to_composite.cc
return op->emitError("expected exactly one called_computation"); auto decomposition = mlir::cast<FlatSymbolRefAttr>(calledComputations[0]); auto composite = rewriter.create<mlir::stablehlo::CompositeOp>( op.getLoc(), op.getResultTypes(), op.getOperands(), name.str(), attrs, decomposition.getValue()); rewriter.replaceOp(op, composite.getResults()); return success(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize_op_order.cc
auto* ctx = func.getContext(); patterns.add<PushDownDequantize>(ctx); if (failed(applyPatternsAndFoldGreedily(func, std::move(patterns)))) { signalPassFailure(); } } } // namespace // Creates an instance of the TensorFlow Lite optimize op order pass. std::unique_ptr<OperationPass<func::FuncOp>> CreateOptimizeOpOrderPass() { return std::make_unique<OptimizeOpOrderPass>(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.1K bytes - Viewed (0)