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Use TensorFlowLiteBenchmarkC framework to build iOS benchmark app

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PiperOrigin-RevId: 281849264
Change-Id: I83aa932c3bfd3922c1f9c4b8e33fcb99f1b954bd
This commit is contained in:
YoungSeok Yoon 2019-11-21 15:42:49 -08:00 committed by TensorFlower Gardener
parent fea0136cd5
commit dd9f5e27a8
7 changed files with 183 additions and 75 deletions
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37
tensorflow/lite/tools/benchmark/experimental/c/benchmark_c_api.cc
View File

@ -71,21 +71,21 @@ class BenchmarkListenerAdapter : public tflite::benchmark::BenchmarkListener {
void OnBenchmarkStart(
const tflite::benchmark::BenchmarkParams& params) override {
if (on_benchmark_start_fn_ != nullptr) {
on_benchmark_start_fn_();
on_benchmark_start_fn_(user_data_);
}
}
void OnSingleRunStart(tflite::benchmark::RunType runType) override {
if (on_single_run_start_fn_ != nullptr) {
on_single_run_start_fn_(runType == tflite::benchmark::WARMUP
? TfLiteBenchmarkWarmup
: TfLiteBenchmarkRegular);
on_single_run_start_fn_(user_data_, runType == tflite::benchmark::WARMUP
? TfLiteBenchmarkWarmup
: TfLiteBenchmarkRegular);
}
}
void OnSingleRunEnd() override {
if (on_single_run_end_fn_ != nullptr) {
on_single_run_end_fn_();
on_single_run_end_fn_(user_data_);
}
}
@ -93,17 +93,22 @@ class BenchmarkListenerAdapter : public tflite::benchmark::BenchmarkListener {
const tflite::benchmark::BenchmarkResults& results) override {
if (on_benchmark_end_fn_ != nullptr) {
TfLiteBenchmarkResults* wrapper = new TfLiteBenchmarkResults{&results};
on_benchmark_end_fn_(wrapper);
on_benchmark_end_fn_(user_data_, wrapper);
delete wrapper;
}
}
// Keep the user_data pointer provided when setting the callbacks.
void* user_data_;
// Function pointers set by the TfLiteBenchmarkListenerSetCallbacks call.
// Only non-null callbacks will be actually called.
void (*on_benchmark_start_fn_)();
void (*on_single_run_start_fn_)(TfLiteBenchmarkRunType runType);
void (*on_single_run_end_fn_)();
void (*on_benchmark_end_fn_)(TfLiteBenchmarkResults* results);
void (*on_benchmark_start_fn_)(void* user_data);
void (*on_single_run_start_fn_)(void* user_data,
TfLiteBenchmarkRunType runType);
void (*on_single_run_end_fn_)(void* user_data);
void (*on_benchmark_end_fn_)(void* user_data,
TfLiteBenchmarkResults* results);
};
struct TfLiteBenchmarkListener {
@ -121,10 +126,14 @@ void TfLiteBenchmarkListenerDelete(TfLiteBenchmarkListener* listener) {
}
void TfLiteBenchmarkListenerSetCallbacks(
TfLiteBenchmarkListener* listener, void (*on_benchmark_start_fn)(),
void (*on_single_run_start_fn)(TfLiteBenchmarkRunType runType),
void (*on_single_run_end_fn)(),
void (*on_benchmark_end_fn)(TfLiteBenchmarkResults* results)) {
TfLiteBenchmarkListener* listener, void* user_data,
void (*on_benchmark_start_fn)(void* user_data),
void (*on_single_run_start_fn)(void* user_data,
TfLiteBenchmarkRunType runType),
void (*on_single_run_end_fn)(void* user_data),
void (*on_benchmark_end_fn)(void* user_data,
TfLiteBenchmarkResults* results)) {
listener->adapter->user_data_ = user_data;
listener->adapter->on_benchmark_start_fn_ = on_benchmark_start_fn;
listener->adapter->on_single_run_start_fn_ = on_single_run_start_fn;
listener->adapter->on_single_run_end_fn_ = on_single_run_end_fn;

14
tensorflow/lite/tools/benchmark/experimental/c/benchmark_c_api.h
View File

@ -82,7 +82,8 @@ extern TfLiteBenchmarkListener* TfLiteBenchmarkListenerCreate();
extern void TfLiteBenchmarkListenerDelete(TfLiteBenchmarkListener* listener);
// Sets the listener callbacks. Only non-null callback functions will be called
// when the following events occur.
// when the following events occur. The user_data pointer provided by the caller
// will also be forwarded as a parameter of each callback function.
//
// - on_benchmark_start: Called before the (outer) inference loop begins. Note
// that this is called *after* the interpreter has been initialized, but
@ -95,10 +96,13 @@ extern void TfLiteBenchmarkListenerDelete(TfLiteBenchmarkListener* listener);
// only valid during the callback function execution, and will be destroyed
// afterwards.
extern void TfLiteBenchmarkListenerSetCallbacks(
TfLiteBenchmarkListener* listener, void (*on_benchmark_start_fn)(),
void (*on_single_run_start_fn)(TfLiteBenchmarkRunType runType),
void (*on_single_run_end_fn)(),
void (*on_benchmark_end_fn)(TfLiteBenchmarkResults* results));
TfLiteBenchmarkListener* listener, void* user_data,
void (*on_benchmark_start_fn)(void* user_data),
void (*on_single_run_start_fn)(void* user_data,
TfLiteBenchmarkRunType runType),
void (*on_single_run_end_fn)(void* user_data),
void (*on_benchmark_end_fn)(void* user_data,
TfLiteBenchmarkResults* results));
// -----------------------------------------------------------------------------
// C APIs corresponding to tflite::benchmark::BenchmarkTfLiteModel type.

61
tensorflow/lite/tools/benchmark/ios/README.md
View File

@ -4,52 +4,43 @@
An iOS app to benchmark TFLite models.
The app reads benchmark parameters from a JSON file named `benchmark_params.json`
in its `benchmark_data` directory. Any downloaded models for benchmarking should
also be placed in `benchmark_data` directory.
The app reads benchmark parameters from a JSON file named
`benchmark_params.json` in its `benchmark_data` directory. Any downloaded models
for benchmarking should also be placed in `benchmark_data` directory.
The JSON file specifies the name of the model file and other benchmarking
parameters like inputs to the model, type of inputs, number of iterations,
number of threads. The default values in the JSON file are for the
Mobilenet_1.0_224 model
([paper](https://arxiv.org/pdf/1704.04861.pdf),
[tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz))
Mobilenet_1.0_224 model ([paper][mobilenet-paper],
[tflite&pb][mobilenet-model]).
## To build/install/run
## Building / running the app
- Follow instructions at
[iOS build for TFLite](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/guide/build_ios.md)
to build TFLite.
* Follow the [iOS build instructions][build-ios] to configure the Bazel
workspace and `.bazelrc` file correctly.
Running
* Run `build_benchmark_framework.sh` script to build the benchmark framework.
This script will build the benchmark framework for iOS and put it under
`TFLiteBenchmark/TFLiteBenchmark/Frameworks` directory.
```bash
tensorflow/lite/tools/make/build_ios_universal_lib.sh
```
* If you want more detailed profiling, run the build script with `-p` option:
`build_benchmark_framework.sh -p`.
will also build `tensorflow/lite/tools/make/gen/lib/benchmark-lib.a` .
* Modify `benchmark_params.json` change the `input_layer`, `input_layer_shape`
and other benchmark parameters.
- Now copy the downloaded model file to `benchmark_data` directory.
* Change `Build Phases -> Copy Bundle Resources` and add the model file to the
resources that need to be copied.
- Modify `benchmark_params.json` change the `input_layer`, `input_layer_shape`
and other benchmark parameters.
* Ensure that `Build Phases -> Link Binary With Library` contains the
`Accelerate framework` and `TensorFlowLiteBenchmarkC.framework`.
- Change `Build Phases -> Copy Bundle Resources` and add the model file to the
resources that need to be copied.
* Now try running the app. The app has a single button that runs the benchmark
on the model and displays results in a text view below. You can also see the
console output section in your Xcode to see more detailed benchmark
information.
- Ensure that `Build Phases -> Link Binary With Library` contains the
`Accelerate framework` and `tensorflow/lite/tools/make/gen/lib/benchmark-lib.a`.
- Now try running the app. The app has a single button that runs the benchmark
on the model and displays results in a text view below.
## Profiling
If you want detailed profiling, use the following command:
```bash
tensorflow/lite/tools/make/build_ios_universal_lib.sh -p
```
Then following the same steps above and run the benchmark app. You will see the
detailed profiling results in the outputs.
[build-ios]: https://tensorflow.org/lite/guide/build_ios
[mobilenet-model]: https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz
[mobilenet-paper]: https://arxiv.org/pdf/1704.04861.pdf

30
tensorflow/lite/tools/benchmark/ios/TFLiteBenchmark/TFLiteBenchmark.xcodeproj/project.pbxproj
View File

@ -8,7 +8,6 @@
/* Begin PBXBuildFile section */
6FE7579A20D59CE500F01636 /* benchmark_params.json in Resources */ = {isa = PBXBuildFile; fileRef = 6FE7579920D59CE500F01636 /* benchmark_params.json */; };
6FE7579D20D5A5E000F01636 /* benchmark-lib.a in Frameworks */ = {isa = PBXBuildFile; fileRef = 6FE7579C20D5A5E000F01636 /* benchmark-lib.a */; };
6FE7579F20D5A6A700F01636 /* Accelerate.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = 6FE7579E20D5A6A700F01636 /* Accelerate.framework */; };
6FE757A120D5AB8100F01636 /* mobilenet_v1_1.0_224.tflite in Resources */ = {isa = PBXBuildFile; fileRef = 6FE757A020D5AB8000F01636 /* mobilenet_v1_1.0_224.tflite */; };
6FE93FFD20D592D8008C9FE4 /* AppDelegate.m in Sources */ = {isa = PBXBuildFile; fileRef = 6FE93FFC20D592D8008C9FE4 /* AppDelegate.m */; };
@ -16,8 +15,24 @@
6FE9400320D592D8008C9FE4 /* Main.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = 6FE9400120D592D8008C9FE4 /* Main.storyboard */; };
6FE9400520D592DA008C9FE4 /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = 6FE9400420D592DA008C9FE4 /* Assets.xcassets */; };
6FE9400B20D592DA008C9FE4 /* main.m in Sources */ = {isa = PBXBuildFile; fileRef = 6FE9400A20D592DA008C9FE4 /* main.m */; };
DC4D465D2373ECF400397CBD /* TensorFlowLiteBenchmarkC.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = DC4D465C2373ECF300397CBD /* TensorFlowLiteBenchmarkC.framework */; };
DC4D465E2373ECF400397CBD /* TensorFlowLiteBenchmarkC.framework in Embed Frameworks */ = {isa = PBXBuildFile; fileRef = DC4D465C2373ECF300397CBD /* TensorFlowLiteBenchmarkC.framework */; settings = {ATTRIBUTES = (CodeSignOnCopy, RemoveHeadersOnCopy, ); }; };
/* End PBXBuildFile section */
/* Begin PBXCopyFilesBuildPhase section */
DC4D465F2373ECF400397CBD /* Embed Frameworks */ = {
isa = PBXCopyFilesBuildPhase;
buildActionMask = 8;
dstPath = "";
dstSubfolderSpec = 10;
files = (
DC4D465E2373ECF400397CBD /* TensorFlowLiteBenchmarkC.framework in Embed Frameworks */,
);
name = "Embed Frameworks";
runOnlyForDeploymentPostprocessing = 1;
};
/* End PBXCopyFilesBuildPhase section */
/* Begin PBXFileReference section */
6FE7579920D59CE500F01636 /* benchmark_params.json */ = {isa = PBXFileReference; lastKnownFileType = text.json; path = benchmark_params.json; sourceTree = "<group>"; };
6FE7579C20D5A5E000F01636 /* benchmark-lib.a */ = {isa = PBXFileReference; lastKnownFileType = archive.ar; name = "benchmark-lib.a"; path = "$SRCROOT/../../../../../../tensorflow/lite/tools/make/gen/lib/benchmark-lib.a"; sourceTree = "<group>"; };
@ -32,6 +47,7 @@
6FE9400420D592DA008C9FE4 /* Assets.xcassets */ = {isa = PBXFileReference; lastKnownFileType = folder.assetcatalog; path = Assets.xcassets; sourceTree = "<group>"; };
6FE9400920D592DA008C9FE4 /* Info.plist */ = {isa = PBXFileReference; lastKnownFileType = text.plist.xml; path = Info.plist; sourceTree = "<group>"; };
6FE9400A20D592DA008C9FE4 /* main.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = main.m; sourceTree = "<group>"; };
DC4D465C2373ECF300397CBD /* TensorFlowLiteBenchmarkC.framework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.framework; name = TensorFlowLiteBenchmarkC.framework; path = TFLiteBenchmark/Frameworks/TensorFlowLiteBenchmarkC.framework; sourceTree = "<group>"; };
/* End PBXFileReference section */
/* Begin PBXFrameworksBuildPhase section */
@ -40,7 +56,7 @@
buildActionMask = 2147483647;
files = (
6FE7579F20D5A6A700F01636 /* Accelerate.framework in Frameworks */,
6FE7579D20D5A5E000F01636 /* benchmark-lib.a in Frameworks */,
DC4D465D2373ECF400397CBD /* TensorFlowLiteBenchmarkC.framework in Frameworks */,
);
runOnlyForDeploymentPostprocessing = 0;
};
@ -59,6 +75,7 @@
6FE7579B20D5A5E000F01636 /* Frameworks */ = {
isa = PBXGroup;
children = (
DC4D465C2373ECF300397CBD /* TensorFlowLiteBenchmarkC.framework */,
6FE7579E20D5A6A700F01636 /* Accelerate.framework */,
6FE7579C20D5A5E000F01636 /* benchmark-lib.a */,
);
@ -108,6 +125,7 @@
6FE93FF420D592D8008C9FE4 /* Sources */,
6FE93FF520D592D8008C9FE4 /* Frameworks */,
6FE93FF620D592D8008C9FE4 /* Resources */,
DC4D465F2373ECF400397CBD /* Embed Frameworks */,
);
buildRules = (
);
@ -308,6 +326,10 @@
buildSettings = {
ASSETCATALOG_COMPILER_APPICON_NAME = AppIcon;
CODE_SIGN_STYLE = Automatic;
FRAMEWORK_SEARCH_PATHS = (
"$(inherited)",
"$(PROJECT_DIR)/TFLiteBenchmark/Frameworks",
);
"HEADER_SEARCH_PATHS[arch=*]" = (
$SRCROOT/../../../../../../,
$SRCROOT/../../../../../../tensorflow/lite/tools/make/downloads/eigen,
@ -334,6 +356,10 @@
buildSettings = {
ASSETCATALOG_COMPILER_APPICON_NAME = AppIcon;
CODE_SIGN_STYLE = Automatic;
FRAMEWORK_SEARCH_PATHS = (
"$(inherited)",
"$(PROJECT_DIR)/TFLiteBenchmark/Frameworks",
);
"HEADER_SEARCH_PATHS[arch=*]" = (
$SRCROOT/../../../../../../,
$SRCROOT/../../../../../../tensorflow/lite/tools/make/downloads/eigen,

60
tensorflow/lite/tools/benchmark/ios/TFLiteBenchmark/TFLiteBenchmark/BenchmarkViewController.mm
View File

@ -18,8 +18,8 @@
#import <sstream>
#import <string>
#import <vector>
#import "tensorflow/lite/tools/benchmark/benchmark_tflite_model.h"
#import "tensorflow/lite/tools/benchmark/logging.h"
#import <TensorFlowLiteBenchmarkC/TensorFlowLiteBenchmarkC.h>
namespace {
NSString* FilePathForResourceName(NSString* filename) {
@ -64,42 +64,57 @@ std::vector<char*> StringVecToCharPtrVec(const std::vector<std::string>& str_vec
return charptr_vec;
}
class ResultsListener : public tflite::benchmark::BenchmarkListener {
class ResultsListener {
public:
void OnBenchmarkEnd(const tflite::benchmark::BenchmarkResults& results) override;
void OnBenchmarkEnd(TfLiteBenchmarkResults* results);
std::string Results() { return results_; }
private:
std::string results_;
};
void OutputMicrosecondsStatToStream(const tensorflow::Stat<int64_t>& time_us,
void OutputMicrosecondsStatToStream(const TfLiteBenchmarkInt64Stat& time_us,
const std::string& prefix, std::ostringstream* stream) {
*stream << prefix << "Num runs: " << time_us.count() << "\n";
*stream << prefix << "Num runs: " << time_us.count << "\n";
*stream << prefix << "Average: " << time_us.avg() / 1e3 << " ms\n";
*stream << prefix << "Min: " << time_us.min() / 1e3 << " ms \n";
*stream << prefix << "Max: " << time_us.max() / 1e3 << " ms \n";
*stream << prefix << "Std deviation: " << time_us.std_deviation() / 1e3 << " ms\n";
*stream << prefix << "Average: " << time_us.avg / 1e3 << " ms\n";
*stream << prefix << "Min: " << time_us.min / 1e3 << " ms \n";
*stream << prefix << "Max: " << time_us.max / 1e3 << " ms \n";
*stream << prefix << "Std deviation: " << time_us.std_deviation / 1e3 << " ms\n";
}
void ResultsListener::OnBenchmarkEnd(const tflite::benchmark::BenchmarkResults& results) {
void ResultsListener::OnBenchmarkEnd(TfLiteBenchmarkResults* results) {
std::ostringstream stream;
const std::string prefix = " - ";
TfLiteBenchmarkInt64Stat inference = TfLiteBenchmarkResultsGetInferenceTimeMicroseconds(results);
TfLiteBenchmarkInt64Stat warmup = TfLiteBenchmarkResultsGetWarmupTimeMicroseconds(results);
stream << "Startup latency: ";
stream << results.startup_latency_us() / 1e3 << " ms\n";
stream << TfLiteBenchmarkResultsGetStartupLatencyMicroseconds(results) / 1e3 << " ms\n";
stream << "\nInference:\n";
OutputMicrosecondsStatToStream(results.inference_time_us(), prefix, &stream);
OutputMicrosecondsStatToStream(inference, prefix, &stream);
stream << "\nWarmup:\n";
OutputMicrosecondsStatToStream(results.warmup_time_us(), prefix, &stream);
OutputMicrosecondsStatToStream(warmup, prefix, &stream);
results_ = stream.str();
}
void OnBenchmarkEnd(void* user_data, TfLiteBenchmarkResults* results) {
if (user_data != nullptr) {
reinterpret_cast<ResultsListener*>(user_data)->OnBenchmarkEnd(results);
}
}
std::string RunBenchmark() {
ResultsListener listener;
tflite::benchmark::BenchmarkTfLiteModel benchmark;
benchmark.AddListener(&listener);
ResultsListener results_listener;
TfLiteBenchmarkTfLiteModel* benchmark = TfLiteBenchmarkTfLiteModelCreate();
TfLiteBenchmarkListener* listener = TfLiteBenchmarkListenerCreate();
TfLiteBenchmarkListenerSetCallbacks(listener, &results_listener, nullptr, nullptr, nullptr,
OnBenchmarkEnd);
TfLiteBenchmarkTfLiteModelAddListener(benchmark, listener);
// TODO(shashishekhar): Passing arguments like this is brittle, refactor the BenchmarkParams
// so that it contains arguments for BenchmarkTfLiteModel and set parameters using BenchmarkParams
std::vector<std::string> command_line_params;
@ -109,8 +124,15 @@ std::string RunBenchmark() {
ReadCommandLineParameters(&command_line_params);
std::vector<char*> argv = StringVecToCharPtrVec(command_line_params);
int argc = static_cast<int>(argv.size());
benchmark.Run(argc, argv.data());
return listener.Results();
TfLiteBenchmarkTfLiteModelRunWithArgs(benchmark, argc, argv.data());
std::string results = results_listener.Results();
TfLiteBenchmarkListenerDelete(listener);
TfLiteBenchmarkTfLiteModelDelete(benchmark);
return results;
}
} // namespace

1
tensorflow/lite/tools/benchmark/ios/TFLiteBenchmark/TFLiteBenchmark/Frameworks/.gitignore vendored Normal file
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@ -0,0 +1 @@
*.framework/

55
tensorflow/lite/tools/benchmark/ios/build_benchmark_framework.sh Executable file
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@ -0,0 +1,55 @@
#!/bin/bash
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
set -e
set -x
WORKSPACE_ROOT=$(bazel info workspace)
BENCHMARK_DIR=tensorflow/lite/tools/benchmark
DEST_DIR="${BENCHMARK_DIR}/ios/TFLiteBenchmark/TFLiteBenchmark/Frameworks"
FRAMEWORK_TARGET=TensorFlowLiteBenchmarkC_framework
usage() {
echo "Usage: $(basename "$0") [-p]"
echo "-p enable profiling"
exit 1
}
PROFILING_ARGS=""
while getopts "p" opt_name; do
case "$opt_name" in
p) PROFILING_ARGS='--copt=-DGEMMLOWP_PROFILING';;
*) usage;;
esac
done
shift $(($OPTIND - 1))
pushd "${WORKSPACE_ROOT}"
# Build the framework.
bazel build --config=ios_fat -c opt ${PROFILING_ARGS} \
"//${BENCHMARK_DIR}/experimental/ios:${FRAMEWORK_TARGET}"
# Copy the framework into the destination and unzip.
mkdir -p "${DEST_DIR}"
cp -f "bazel-bin/${BENCHMARK_DIR}/experimental/ios/${FRAMEWORK_TARGET}.zip" \
"${DEST_DIR}"
pushd "${DEST_DIR}"
unzip -o "${FRAMEWORK_TARGET}.zip"
rm -f "${FRAMEWORK_TARGET}.zip"
popd
popd