3d42bdcff7
- Add new method for GenerateTestSpec to generate testspec from TFLite. PiperOrigin-RevId: 285884997 Change-Id: I803bd619013f7410bd56283a715e46c8719d4810
75 lines
2.9 KiB
C++
75 lines
2.9 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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#ifndef TENSORFLOW_LITE_TESTING_GENERATE_TESTSPEC_H_
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#define TENSORFLOW_LITE_TESTING_GENERATE_TESTSPEC_H_
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#include <algorithm>
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#include <functional>
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#include <iostream>
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#include <vector>
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#include "tensorflow/lite/string_type.h"
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namespace tflite {
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namespace testing {
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// Generate test spec by executing TensorFlow model on random inputs.
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// The test spec can be consumed by ParseAndRunTests.
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// See test spec format in parse_testdata.h
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//
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// Inputs:
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// stream: mutable iostream that contains the contents of test spec.
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// tensorflow_model_path: path to TensorFlow model.
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// tflite_model_path: path to tflite_model_path that the test spec runs
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// num_invocations: how many pairs of inputs and outputs will be generated.
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// against. input_layer: names of input tensors. Example: input1
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// input_layer_type: datatypes of input tensors. Example: float
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// input_layer_shape: shapes of input tensors, separated by comma. example:
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// 1,3,4 output_layer: names of output tensors. Example: output
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bool GenerateTestSpecFromTensorflowModel(
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std::iostream& stream, const string& tensorflow_model_path,
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const string& tflite_model_path, int num_invocations,
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const std::vector<string>& input_layer,
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const std::vector<string>& input_layer_type,
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const std::vector<string>& input_layer_shape,
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const std::vector<string>& output_layer);
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// Generate test spec by executing TFLite model on random inputs.
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bool GenerateTestSpecFromTFLiteModel(
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std::iostream& stream, const string& tflite_model_path, int num_invocations,
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const std::vector<string>& input_layer,
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const std::vector<string>& input_layer_type,
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const std::vector<string>& input_layer_shape,
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const std::vector<string>& output_layer);
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// Generates random values that are filled into the tensor.
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template <typename T, typename RandomFunction>
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std::vector<T> GenerateRandomTensor(const std::vector<int>& shape,
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RandomFunction random_func) {
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int64_t num_elements = 1;
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for (const int dim : shape) {
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num_elements *= dim;
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}
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std::vector<T> result(num_elements);
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std::generate_n(result.data(), num_elements, random_func);
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return result;
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}
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} // namespace testing
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} // namespace tflite
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#endif // TENSORFLOW_LITE_TESTING_GENERATE_TESTSPEC_H_
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