//===----------------------------------------------------------------------===// // // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // Also available under a BSD-style license. See LICENSE. // //===----------------------------------------------------------------------===// #include "torch-mlir/Conversion/TorchToTosa/TosaLegalizeUtils.h" #include "mlir/Dialect/Tosa/IR/TosaOps.h" // from @llvm-project #include "mlir/Dialect/Tosa/Utils/QuantUtils.h" // from @llvm-project #include "torch-mlir/Conversion/TorchToTosa/TosaLegalizeCommon.h" namespace mlir { namespace tosa { // Create a TOSA rescale op from input framework tensor, zero points and // rounding mode Value buildRescale(PatternRewriter &rewriter, Operation *op, ShapedType output_type, Value input_val, double scale, int64_t input_zp, int64_t output_zp, bool double_round, bool scale32) { int32_t multiplier; int32_t shift; int32_t scale_width = scale32 ? 32 : 16; computeMultiplierAndShift(scale, multiplier, shift, scale_width); auto rescale_op = CreateOpAndInfer( rewriter, op->getLoc(), output_type, input_val, rewriter.getI32IntegerAttr(static_cast(input_zp)), rewriter.getI32IntegerAttr(static_cast(output_zp)), rewriter.getI32ArrayAttr({multiplier}), rewriter.getI32ArrayAttr({shift}), rewriter.getBoolAttr(scale32), rewriter.getBoolAttr(double_round), rewriter.getBoolAttr(false)); return rescale_op.getResult(); } // Creates TOSA rescale op with int32 output Value buildRescaleToInt32(PatternRewriter &rewriter, Operation *op, Value input_val, double input_scale, int64_t input_zp) { // Output is always int32 type auto input_type = input_val.getType().dyn_cast(); assert(input_type); auto output_type = input_type.clone(rewriter.getI32Type()); return buildRescale(rewriter, op, output_type, input_val, input_scale, input_zp, 0, false, true); } // Create a 32-bit float constant operator from a float Value getTosaConstTensorSingleF32(PatternRewriter &rewriter, Operation *op, float val) { auto const_type = RankedTensorType::get({}, rewriter.getF32Type()); auto const_attr = DenseElementsAttr::get(const_type, val); auto const_op = rewriter.create(op->getLoc(), const_type, const_attr); return const_op.getResult(); } } // namespace tosa } // namespace mlir