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Michael Butler3670c382020-08-06 23:22:35 -07001/*
2 * Copyright (C) 2020 The Android Open Source Project
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17#include "PreparedModel.h"
18
19#include "Callbacks.h"
20#include "Conversions.h"
21#include "Utils.h"
22
23#include <android/hardware/neuralnetworks/1.0/types.h>
24#include <android/hardware/neuralnetworks/1.1/types.h>
25#include <android/hardware/neuralnetworks/1.2/IPreparedModel.h>
26#include <android/hardware/neuralnetworks/1.2/types.h>
27#include <nnapi/IPreparedModel.h>
28#include <nnapi/Result.h>
29#include <nnapi/Types.h>
30#include <nnapi/hal/1.0/Conversions.h>
31#include <nnapi/hal/CommonUtils.h>
32#include <nnapi/hal/HandleError.h>
33#include <nnapi/hal/ProtectCallback.h>
34
35#include <memory>
36#include <tuple>
37#include <utility>
38#include <vector>
39
40namespace android::hardware::neuralnetworks::V1_2::utils {
41namespace {
42
43nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
44convertExecutionResultsHelper(const hidl_vec<OutputShape>& outputShapes, const Timing& timing) {
Michael Butler32acc062020-11-22 19:36:30 -080045 return std::make_pair(NN_TRY(nn::convert(outputShapes)), NN_TRY(nn::convert(timing)));
Michael Butler3670c382020-08-06 23:22:35 -070046}
47
48nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> convertExecutionResults(
49 const hidl_vec<OutputShape>& outputShapes, const Timing& timing) {
50 return hal::utils::makeExecutionFailure(convertExecutionResultsHelper(outputShapes, timing));
51}
52
53} // namespace
54
55nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
56 sp<V1_2::IPreparedModel> preparedModel) {
57 if (preparedModel == nullptr) {
58 return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
59 << "V1_2::utils::PreparedModel::create must have non-null preparedModel";
60 }
61
62 auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(preparedModel));
63 return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel),
64 std::move(deathHandler));
65}
66
67PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/, sp<V1_2::IPreparedModel> preparedModel,
68 hal::utils::DeathHandler deathHandler)
69 : kPreparedModel(std::move(preparedModel)), kDeathHandler(std::move(deathHandler)) {}
70
71nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
72PreparedModel::executeSynchronously(const V1_0::Request& request, MeasureTiming measure) const {
73 nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
74 NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
75 const auto cb = [&result](V1_0::ErrorStatus status, const hidl_vec<OutputShape>& outputShapes,
76 const Timing& timing) {
77 if (status != V1_0::ErrorStatus::NONE) {
Michael Butler32acc062020-11-22 19:36:30 -080078 const auto canonical = nn::convert(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
Michael Butler3670c382020-08-06 23:22:35 -070079 result = NN_ERROR(canonical) << "executeSynchronously failed with " << toString(status);
80 } else {
81 result = convertExecutionResults(outputShapes, timing);
82 }
83 };
84
85 const auto ret = kPreparedModel->executeSynchronously(request, measure, cb);
Michael Butler61f508e2020-11-22 20:25:34 -080086 HANDLE_TRANSPORT_FAILURE(ret);
Michael Butler3670c382020-08-06 23:22:35 -070087
88 return result;
89}
90
91nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
92PreparedModel::executeAsynchronously(const V1_0::Request& request, MeasureTiming measure) const {
93 const auto cb = sp<ExecutionCallback>::make();
94 const auto scoped = kDeathHandler.protectCallback(cb.get());
95
96 const auto ret = kPreparedModel->execute_1_2(request, measure, cb);
Michael Butler61f508e2020-11-22 20:25:34 -080097 const auto status = HANDLE_TRANSPORT_FAILURE(ret);
Michael Butler3670c382020-08-06 23:22:35 -070098 if (status != V1_0::ErrorStatus::NONE) {
Michael Butler32acc062020-11-22 19:36:30 -080099 const auto canonical = nn::convert(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
Michael Butler3670c382020-08-06 23:22:35 -0700100 return NN_ERROR(canonical) << "execute failed with " << toString(status);
101 }
102
103 return cb->get();
104}
105
106nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
107 const nn::Request& request, nn::MeasureTiming measure,
108 const nn::OptionalTimePoint& /*deadline*/,
Michael Butlerca114202020-12-04 17:38:20 -0800109 const nn::OptionalDuration& /*loopTimeoutDuration*/) const {
Michael Butler3670c382020-08-06 23:22:35 -0700110 // Ensure that request is ready for IPC.
111 std::optional<nn::Request> maybeRequestInShared;
112 const nn::Request& requestInShared = NN_TRY(hal::utils::makeExecutionFailure(
113 hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared)));
114
115 const auto hidlRequest =
116 NN_TRY(hal::utils::makeExecutionFailure(V1_0::utils::convert(requestInShared)));
117 const auto hidlMeasure = NN_TRY(hal::utils::makeExecutionFailure(convert(measure)));
118
119 nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
120 NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
121 const bool preferSynchronous = true;
122
123 // Execute synchronously if allowed.
124 if (preferSynchronous) {
125 result = executeSynchronously(hidlRequest, hidlMeasure);
126 }
127
128 // Run asymchronous execution if execution has not already completed.
129 if (!result.has_value()) {
130 result = executeAsynchronously(hidlRequest, hidlMeasure);
131 }
132
133 // Flush output buffers if suxcessful execution.
134 if (result.has_value()) {
135 NN_TRY(hal::utils::makeExecutionFailure(
136 hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
137 }
138
139 return result;
140}
141
142nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
Michael Butlerca114202020-12-04 17:38:20 -0800143PreparedModel::executeFenced(const nn::Request& /*request*/,
144 const std::vector<nn::SyncFence>& /*waitFor*/,
145 nn::MeasureTiming /*measure*/,
146 const nn::OptionalTimePoint& /*deadline*/,
147 const nn::OptionalDuration& /*loopTimeoutDuration*/,
148 const nn::OptionalDuration& /*timeoutDurationAfterFence*/) const {
Michael Butler3670c382020-08-06 23:22:35 -0700149 return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
150 << "IPreparedModel::executeFenced is not supported on 1.2 HAL service";
151}
152
153std::any PreparedModel::getUnderlyingResource() const {
154 sp<V1_0::IPreparedModel> resource = kPreparedModel;
155 return resource;
156}
157
158} // namespace android::hardware::neuralnetworks::V1_2::utils