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
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
|
/*
* Copyright (C) 2021 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 "PreparedModel.h"
#include "Burst.h"
#include "Callbacks.h"
#include "Conversions.h"
#include "Execution.h"
#include "ProtectCallback.h"
#include "Utils.h"
#include <aidl/android/hardware/neuralnetworks/Request.h>
#include <android/binder_auto_utils.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/Result.h>
#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/hal/CommonUtils.h>
#include <nnapi/hal/HandleError.h>
#include <memory>
#include <tuple>
#include <utility>
#include <vector>
// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface
// lifetimes across processes and for protecting asynchronous calls across AIDL.
namespace aidl::android::hardware::neuralnetworks::utils {
namespace {
nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> convertExecutionResults(
const std::vector<OutputShape>& outputShapes, const Timing& timing) {
return std::make_pair(NN_TRY(nn::convert(outputShapes)), NN_TRY(nn::convert(timing)));
}
nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> convertFencedExecutionResults(
ErrorStatus status, const aidl_hal::Timing& timingLaunched,
const aidl_hal::Timing& timingFenced) {
HANDLE_HAL_STATUS(status) << "fenced execution callback info failed with " << toString(status);
return std::make_pair(NN_TRY(nn::convert(timingLaunched)), NN_TRY(nn::convert(timingFenced)));
}
} // namespace
nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
std::shared_ptr<aidl_hal::IPreparedModel> preparedModel) {
if (preparedModel == nullptr) {
return NN_ERROR()
<< "aidl_hal::utils::PreparedModel::create must have non-null preparedModel";
}
return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel));
}
PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/,
std::shared_ptr<aidl_hal::IPreparedModel> preparedModel)
: kPreparedModel(std::move(preparedModel)) {}
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
const nn::Request& request, nn::MeasureTiming measure,
const nn::OptionalTimePoint& deadline,
const nn::OptionalDuration& loopTimeoutDuration) const {
// Ensure that request is ready for IPC.
std::optional<nn::Request> maybeRequestInShared;
hal::utils::RequestRelocation relocation;
const nn::Request& requestInShared =
NN_TRY(hal::utils::makeExecutionFailure(hal::utils::convertRequestFromPointerToShared(
&request, nn::kDefaultRequestMemoryAlignment, nn::kDefaultRequestMemoryPadding,
&maybeRequestInShared, &relocation)));
const auto aidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
const auto aidlMeasure = NN_TRY(hal::utils::makeExecutionFailure(convert(measure)));
const auto aidlDeadline = NN_TRY(hal::utils::makeExecutionFailure(convert(deadline)));
const auto aidlLoopTimeoutDuration =
NN_TRY(hal::utils::makeExecutionFailure(convert(loopTimeoutDuration)));
return executeInternal(aidlRequest, aidlMeasure, aidlDeadline, aidlLoopTimeoutDuration,
relocation);
}
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
PreparedModel::executeInternal(const Request& request, bool measure, int64_t deadline,
int64_t loopTimeoutDuration,
const hal::utils::RequestRelocation& relocation) const {
if (relocation.input) {
relocation.input->flush();
}
ExecutionResult executionResult;
const auto ret = kPreparedModel->executeSynchronously(request, measure, deadline,
loopTimeoutDuration, &executionResult);
HANDLE_ASTATUS(ret) << "executeSynchronously failed";
if (!executionResult.outputSufficientSize) {
auto canonicalOutputShapes =
nn::convert(executionResult.outputShapes).value_or(std::vector<nn::OutputShape>{});
return NN_ERROR(nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, std::move(canonicalOutputShapes))
<< "execution failed with " << nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE;
}
auto [outputShapes, timing] = NN_TRY(hal::utils::makeExecutionFailure(
convertExecutionResults(executionResult.outputShapes, executionResult.timing)));
if (relocation.output) {
relocation.output->flush();
}
return std::make_pair(std::move(outputShapes), timing);
}
nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
PreparedModel::executeFenced(const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
const nn::OptionalDuration& loopTimeoutDuration,
const nn::OptionalDuration& timeoutDurationAfterFence) const {
// Ensure that request is ready for IPC.
std::optional<nn::Request> maybeRequestInShared;
hal::utils::RequestRelocation relocation;
const nn::Request& requestInShared = NN_TRY(hal::utils::convertRequestFromPointerToShared(
&request, nn::kDefaultRequestMemoryAlignment, nn::kDefaultRequestMemoryPadding,
&maybeRequestInShared, &relocation));
const auto aidlRequest = NN_TRY(convert(requestInShared));
const auto aidlWaitFor = NN_TRY(convert(waitFor));
const auto aidlMeasure = NN_TRY(convert(measure));
const auto aidlDeadline = NN_TRY(convert(deadline));
const auto aidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
const auto aidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
return executeFencedInternal(aidlRequest, aidlWaitFor, aidlMeasure, aidlDeadline,
aidlLoopTimeoutDuration, aidlTimeoutDurationAfterFence,
relocation);
}
nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
PreparedModel::executeFencedInternal(const Request& request,
const std::vector<ndk::ScopedFileDescriptor>& waitFor,
bool measure, int64_t deadline, int64_t loopTimeoutDuration,
int64_t timeoutDurationAfterFence,
const hal::utils::RequestRelocation& relocation) const {
if (relocation.input) {
relocation.input->flush();
}
FencedExecutionResult result;
const auto ret =
kPreparedModel->executeFenced(request, waitFor, measure, deadline, loopTimeoutDuration,
timeoutDurationAfterFence, &result);
HANDLE_ASTATUS(ret) << "executeFenced failed";
auto resultSyncFence = nn::SyncFence::createAsSignaled();
if (result.syncFence.get() != -1) {
resultSyncFence = NN_TRY(nn::convert(result.syncFence));
}
auto callback = result.callback;
if (callback == nullptr) {
return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "callback is null";
}
// If executeFenced required the request memory to be moved into shared memory, block here until
// the fenced execution has completed and flush the memory back.
if (relocation.output) {
const auto state = resultSyncFence.syncWait({});
if (state != nn::SyncFence::FenceState::SIGNALED) {
return NN_ERROR() << "syncWait failed with " << state;
}
relocation.output->flush();
}
// Create callback which can be used to retrieve the execution error status and timings.
nn::ExecuteFencedInfoCallback resultCallback =
[callback]() -> nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> {
ErrorStatus errorStatus;
Timing timingLaunched;
Timing timingFenced;
const auto ret = callback->getExecutionInfo(&timingLaunched, &timingFenced, &errorStatus);
HANDLE_ASTATUS(ret) << "fenced execution callback getExecutionInfo failed";
return convertFencedExecutionResults(errorStatus, timingLaunched, timingFenced);
};
return std::make_pair(std::move(resultSyncFence), std::move(resultCallback));
}
nn::GeneralResult<nn::SharedExecution> PreparedModel::createReusableExecution(
const nn::Request& request, nn::MeasureTiming measure,
const nn::OptionalDuration& loopTimeoutDuration) const {
// Ensure that request is ready for IPC.
std::optional<nn::Request> maybeRequestInShared;
hal::utils::RequestRelocation relocation;
const nn::Request& requestInShared = NN_TRY(hal::utils::convertRequestFromPointerToShared(
&request, nn::kDefaultRequestMemoryAlignment, nn::kDefaultRequestMemoryPadding,
&maybeRequestInShared, &relocation));
auto aidlRequest = NN_TRY(convert(requestInShared));
auto aidlMeasure = NN_TRY(convert(measure));
auto aidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
return Execution::create(shared_from_this(), std::move(aidlRequest), std::move(relocation),
aidlMeasure, aidlLoopTimeoutDuration);
}
nn::GeneralResult<nn::SharedBurst> PreparedModel::configureExecutionBurst() const {
std::shared_ptr<IBurst> burst;
const auto ret = kPreparedModel->configureExecutionBurst(&burst);
HANDLE_ASTATUS(ret) << "configureExecutionBurst failed";
return Burst::create(std::move(burst));
}
std::any PreparedModel::getUnderlyingResource() const {
std::shared_ptr<aidl_hal::IPreparedModel> resource = kPreparedModel;
return resource;
}
} // namespace aidl::android::hardware::neuralnetworks::utils
|
