1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
|
/*
* Copyright (C) 2020 The Android Open Source Project
*
* 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 "CommonUtils.h"
#include <android-base/logging.h>
#include <nnapi/Result.h>
#include <nnapi/SharedMemory.h>
#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/Validation.h>
#include <algorithm>
#include <any>
#include <functional>
#include <optional>
#include <variant>
#include <vector>
namespace android::hardware::neuralnetworks::utils {
nn::Capabilities::OperandPerformanceTable makeQuantized8PerformanceConsistentWithP(
const nn::Capabilities::PerformanceInfo& float32Performance,
const nn::Capabilities::PerformanceInfo& quantized8Performance) {
// In Android P, most data types are treated as having the same performance as
// TENSOR_QUANT8_ASYMM. This collection must be in sorted order.
std::vector<nn::Capabilities::OperandPerformance> operandPerformances = {
{.type = nn::OperandType::FLOAT32, .info = float32Performance},
{.type = nn::OperandType::INT32, .info = quantized8Performance},
{.type = nn::OperandType::UINT32, .info = quantized8Performance},
{.type = nn::OperandType::TENSOR_FLOAT32, .info = float32Performance},
{.type = nn::OperandType::TENSOR_INT32, .info = quantized8Performance},
{.type = nn::OperandType::TENSOR_QUANT8_ASYMM, .info = quantized8Performance},
{.type = nn::OperandType::OEM, .info = quantized8Performance},
{.type = nn::OperandType::TENSOR_OEM_BYTE, .info = quantized8Performance},
};
return nn::Capabilities::OperandPerformanceTable::create(std::move(operandPerformances))
.value();
}
} // namespace android::hardware::neuralnetworks::utils
|
