298ec44da3
This test runs an automated diff comparison of TF vs TFLite for a given source model. It can also be used to run comparisons on-device with delegates. Also fix the tf_driver/tflite_diff tool to allow execution on mobile devices. PiperOrigin-RevId: 284293992 Change-Id: Ia64927b4d76a195924e5dc2f16b7f4aa53481c0e
106 lines
4.3 KiB
C++
106 lines
4.3 KiB
C++
/* Copyright 2017 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.
|
|
==============================================================================*/
|
|
#ifndef TENSORFLOW_LITE_TESTING_TFLITE_DIFF_FLAGS_H_
|
|
#define TENSORFLOW_LITE_TESTING_TFLITE_DIFF_FLAGS_H_
|
|
|
|
#include <cstring>
|
|
|
|
#include "absl/strings/match.h"
|
|
#include "tensorflow/core/util/command_line_flags.h"
|
|
#include "tensorflow/lite/testing/split.h"
|
|
#include "tensorflow/lite/testing/tflite_diff_util.h"
|
|
#include "tensorflow/lite/testing/tflite_driver.h"
|
|
|
|
namespace tflite {
|
|
namespace testing {
|
|
|
|
DiffOptions ParseTfliteDiffFlags(int* argc, char** argv) {
|
|
struct {
|
|
string tensorflow_model;
|
|
string tflite_model;
|
|
string input_layer;
|
|
string input_layer_type;
|
|
string input_layer_shape;
|
|
string output_layer;
|
|
int32_t num_runs_per_pass = 100;
|
|
string delegate_name;
|
|
} values;
|
|
|
|
std::string delegate_name;
|
|
std::vector<tensorflow::Flag> flags = {
|
|
tensorflow::Flag("tensorflow_model", &values.tensorflow_model,
|
|
"Path of tensorflow model."),
|
|
tensorflow::Flag("tflite_model", &values.tflite_model,
|
|
"Path of tensorflow lite model."),
|
|
tensorflow::Flag("input_layer", &values.input_layer,
|
|
"Names of input tensors, separated by comma. Example: "
|
|
"input_1,input_2."),
|
|
tensorflow::Flag("input_layer_type", &values.input_layer_type,
|
|
"Data types of input tensors, separated by comma. "
|
|
"Example: float,int."),
|
|
tensorflow::Flag(
|
|
"input_layer_shape", &values.input_layer_shape,
|
|
"Shapes of input tensors, separated by colon. Example: 1,3,4,1:2."),
|
|
tensorflow::Flag("output_layer", &values.output_layer,
|
|
"Names of output tensors, separated by comma. Example: "
|
|
"output_1,output_2."),
|
|
tensorflow::Flag("num_runs_per_pass", &values.num_runs_per_pass,
|
|
"[optional] Number of full runs in each pass."),
|
|
tensorflow::Flag("delegate", &values.delegate_name,
|
|
"[optional] Delegate to use for executing ops. Must be "
|
|
"`{\"\", NNAPI, GPU, FLEX}`"),
|
|
};
|
|
|
|
bool no_inputs = *argc == 1;
|
|
bool success = tensorflow::Flags::Parse(argc, argv, flags);
|
|
if (!success || no_inputs || (*argc == 2 && !strcmp(argv[1], "--helpfull"))) {
|
|
fprintf(stderr, "%s", tensorflow::Flags::Usage(argv[0], flags).c_str());
|
|
return {};
|
|
} else if (values.tensorflow_model.empty() || values.tflite_model.empty() ||
|
|
values.input_layer.empty() || values.input_layer_type.empty() ||
|
|
values.input_layer_shape.empty() || values.output_layer.empty()) {
|
|
fprintf(stderr, "%s", tensorflow::Flags::Usage(argv[0], flags).c_str());
|
|
return {};
|
|
}
|
|
|
|
TfLiteDriver::DelegateType delegate = TfLiteDriver::DelegateType::kNone;
|
|
if (!values.delegate_name.empty()) {
|
|
if (absl::EqualsIgnoreCase(values.delegate_name, "nnapi")) {
|
|
delegate = TfLiteDriver::DelegateType::kNnapi;
|
|
} else if (absl::EqualsIgnoreCase(values.delegate_name, "gpu")) {
|
|
delegate = TfLiteDriver::DelegateType::kGpu;
|
|
} else if (absl::EqualsIgnoreCase(values.delegate_name, "flex")) {
|
|
delegate = TfLiteDriver::DelegateType::kFlex;
|
|
} else {
|
|
fprintf(stderr, "%s", tensorflow::Flags::Usage(argv[0], flags).c_str());
|
|
return {};
|
|
}
|
|
}
|
|
|
|
return {values.tensorflow_model,
|
|
values.tflite_model,
|
|
Split<string>(values.input_layer, ","),
|
|
Split<string>(values.input_layer_type, ","),
|
|
Split<string>(values.input_layer_shape, ":"),
|
|
Split<string>(values.output_layer, ","),
|
|
values.num_runs_per_pass,
|
|
delegate};
|
|
}
|
|
|
|
} // namespace testing
|
|
} // namespace tflite
|
|
|
|
#endif // TENSORFLOW_LITE_TESTING_TFLITE_DIFF_FLAGS_H_
|