73 lines
2.6 KiB
C++
73 lines
2.6 KiB
C++
//===- UniformSupport.cpp - Support utilities for uniform quant -----------===//
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//
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// Copyright 2019 The MLIR Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// =============================================================================
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#include "mlir/Dialect/QuantOps/UniformSupport.h"
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#include "mlir/IR/StandardTypes.h"
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using namespace mlir;
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using namespace mlir::quant;
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static bool isQuantizablePrimitiveType(Type inputType) {
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return inputType.isa<FloatType>();
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}
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const ExpressedToQuantizedConverter
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ExpressedToQuantizedConverter::forInputType(Type inputType) {
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switch (inputType.getKind()) {
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default:
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if (isQuantizablePrimitiveType(inputType)) {
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// Supported primitive type (which just is the expressed type).
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return ExpressedToQuantizedConverter{inputType, inputType};
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}
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// Unsupported.
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return ExpressedToQuantizedConverter{inputType, nullptr};
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case StandardTypes::RankedTensor:
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case StandardTypes::UnrankedTensor:
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case StandardTypes::Vector: {
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Type elementType = inputType.cast<ShapedType>().getElementType();
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if (!isQuantizablePrimitiveType(elementType)) {
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// Unsupported.
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return ExpressedToQuantizedConverter{inputType, nullptr};
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}
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return ExpressedToQuantizedConverter{
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inputType, inputType.cast<ShapedType>().getElementType()};
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}
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}
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}
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Type ExpressedToQuantizedConverter::convert(QuantizedType elementalType) const {
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assert(expressedType && "convert() on unsupported conversion");
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switch (inputType.getKind()) {
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default:
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if (isQuantizablePrimitiveType(elementalType)) {
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// For primitives, just use the new elemental type.
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return elementalType;
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}
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// Unsupported.
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return nullptr;
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case StandardTypes::RankedTensor:
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return RankedTensorType::get(inputType.cast<RankedTensorType>().getShape(),
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elementalType);
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case StandardTypes::UnrankedTensor:
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return UnrankedTensorType::get(elementalType);
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case StandardTypes::Vector:
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return VectorType::get(inputType.cast<VectorType>().getShape(),
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elementalType);
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}
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}
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