mirror of
https://github.com/Evolution-X/hardware_interfaces
synced 2026-02-03 03:14:17 +00:00
6b0905cb69
This CL relocates utility code that transfers data between pointer-based memory and shared memory for Request objects and Model objects, moving it from nnapi/hal/CommonUtils.h (hal utilities) to nnapi/SharedMemory.h (canonical library). This change also adds a check for whether Model and Requests have pointer-based data in neuralnetworks/aidl/utils/src/Conversions.cpp to make it consistent with the HIDL utility conversions. Bug: 217217023 Test: mma Test: presubmit Change-Id: I55a0fea186708d806bc709681e10027a9e4b0ffb
55 lines
2.2 KiB
C++
55 lines
2.2 KiB
C++
/*
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* Copyright (C) 2020 The Android Open Source Project
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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 "CommonUtils.h"
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#include <android-base/logging.h>
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#include <nnapi/Result.h>
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#include <nnapi/SharedMemory.h>
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#include <nnapi/TypeUtils.h>
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#include <nnapi/Types.h>
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#include <nnapi/Validation.h>
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#include <algorithm>
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#include <any>
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#include <functional>
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#include <optional>
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#include <variant>
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#include <vector>
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namespace android::hardware::neuralnetworks::utils {
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nn::Capabilities::OperandPerformanceTable makeQuantized8PerformanceConsistentWithP(
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const nn::Capabilities::PerformanceInfo& float32Performance,
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const nn::Capabilities::PerformanceInfo& quantized8Performance) {
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// In Android P, most data types are treated as having the same performance as
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// TENSOR_QUANT8_ASYMM. This collection must be in sorted order.
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std::vector<nn::Capabilities::OperandPerformance> operandPerformances = {
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{.type = nn::OperandType::FLOAT32, .info = float32Performance},
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{.type = nn::OperandType::INT32, .info = quantized8Performance},
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{.type = nn::OperandType::UINT32, .info = quantized8Performance},
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{.type = nn::OperandType::TENSOR_FLOAT32, .info = float32Performance},
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{.type = nn::OperandType::TENSOR_INT32, .info = quantized8Performance},
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{.type = nn::OperandType::TENSOR_QUANT8_ASYMM, .info = quantized8Performance},
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{.type = nn::OperandType::OEM, .info = quantized8Performance},
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{.type = nn::OperandType::TENSOR_OEM_BYTE, .info = quantized8Performance},
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};
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return nn::Capabilities::OperandPerformanceTable::create(std::move(operandPerformances))
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.value();
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}
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} // namespace android::hardware::neuralnetworks::utils
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