f38c4d866b
This makes comparison between two tflite models possible. PiperOrigin-RevId: 349357549 Change-Id: Ibeb8e206be2a997be8974b4ec51eee21bcc45a24
96 lines
3.6 KiB
C++
96 lines
3.6 KiB
C++
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/lite/testing/tflite_diff_util.h"
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#include <cstdarg>
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#include <cstdio>
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#include <cstdlib>
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#include <sstream>
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#include "tensorflow/lite/testing/generate_testspec.h"
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#include "tensorflow/lite/testing/parse_testdata.h"
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#include "tensorflow/lite/testing/tflite_driver.h"
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namespace tflite {
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namespace testing {
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namespace {
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bool SingleRunDiffTestWithProvidedRunner(::tflite::testing::DiffOptions options,
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int num_invocations,
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TestRunner* (*runner_factory)()) {
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std::stringstream tflite_stream;
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std::string reference_tflite_model = options.reference_tflite_model.empty()
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? options.tflite_model
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: options.reference_tflite_model;
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if (!GenerateTestSpecFromTFLiteModel(
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tflite_stream, reference_tflite_model, num_invocations,
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options.input_layer, options.input_layer_type,
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options.input_layer_shape, options.output_layer)) {
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return false;
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}
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std::unique_ptr<TestRunner> runner(runner_factory());
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runner->LoadModel(options.tflite_model);
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return ParseAndRunTests(&tflite_stream, runner.get());
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}
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} // namespace
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bool RunDiffTest(const DiffOptions& options, int num_invocations) {
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std::stringstream tflite_stream;
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if (!GenerateTestSpecFromTensorflowModel(
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tflite_stream, options.tensorflow_model, options.tflite_model,
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num_invocations, options.input_layer, options.input_layer_type,
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options.input_layer_shape, options.output_layer)) {
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return false;
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}
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TfLiteDriver tflite_driver(options.delegate);
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tflite_driver.LoadModel(options.tflite_model);
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return ParseAndRunTests(&tflite_stream, &tflite_driver);
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}
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bool RunDiffTestWithProvidedRunner(const tflite::testing::DiffOptions& options,
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TestRunner* (*runner_factory)()) {
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int failure_count = 0;
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for (int i = 0; i < options.num_runs_per_pass; i++) {
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if (!SingleRunDiffTestWithProvidedRunner(options,
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/*num_invocations=*/1,
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runner_factory)) {
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++failure_count;
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}
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}
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int failures_in_first_pass = failure_count;
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if (failure_count == 0) {
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// Let's try again with num_invocations > 1 to make sure we can do multiple
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// invocations without resetting the interpreter.
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for (int i = 0; i < options.num_runs_per_pass; i++) {
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if (!SingleRunDiffTestWithProvidedRunner(options,
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/*num_invocations=*/2,
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runner_factory)) {
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++failure_count;
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}
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}
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}
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fprintf(stderr, "Num errors in single-inference pass: %d\n",
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failures_in_first_pass);
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fprintf(stderr, "Num errors in multi-inference pass : %d\n",
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failure_count - failures_in_first_pass);
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return failure_count == 0;
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}
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} // namespace testing
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} // namespace tflite
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