117 lines
3.8 KiB
C++
117 lines
3.8 KiB
C++
/* Copyright 2018 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 <functional>
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#include <memory>
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#include <vector>
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#include <gtest/gtest.h>
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#include "flatbuffers/flexbuffers.h" // TF:flatbuffers
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#include "tensorflow/lite/interpreter.h"
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#include "tensorflow/lite/kernels/register.h"
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#include "tensorflow/lite/kernels/test_util.h"
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#include "tensorflow/lite/model.h"
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namespace tflite {
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namespace ops {
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namespace custom {
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TfLiteRegistration* Register_AUDIO_SPECTROGRAM();
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namespace {
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using ::testing::ElementsAre;
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using ::testing::ElementsAreArray;
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class BaseAudioSpectrogramOpModel : public SingleOpModel {
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public:
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BaseAudioSpectrogramOpModel(const TensorData& input1,
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const TensorData& output, int window_size,
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int stride, bool magnitude_squared) {
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input1_ = AddInput(input1);
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output_ = AddOutput(output);
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flexbuffers::Builder fbb;
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fbb.Map([&]() {
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fbb.Int("window_size", window_size);
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fbb.Int("stride", stride);
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fbb.Bool("magnitude_squared", magnitude_squared);
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});
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fbb.Finish();
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SetCustomOp("AudioSpectrogram", fbb.GetBuffer(),
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Register_AUDIO_SPECTROGRAM);
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BuildInterpreter({GetShape(input1_)});
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}
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int input1() { return input1_; }
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std::vector<float> GetOutput() { return ExtractVector<float>(output_); }
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std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
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protected:
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int input1_;
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int output_;
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};
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TEST(BaseAudioSpectrogramOpModel, NonSquaredTest) {
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BaseAudioSpectrogramOpModel m({TensorType_FLOAT32, {8, 1}},
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{TensorType_FLOAT32, {}}, 8, 1, false);
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m.PopulateTensor<float>(m.input1(),
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{-1.0f, 0.0f, 1.0f, 0.0f, -1.0f, 0.0f, 1.0f, 0.0f});
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m.Invoke();
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std::vector<int> output_shape = m.GetOutputShape();
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EXPECT_EQ(3, output_shape.size());
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EXPECT_THAT(output_shape, ElementsAre(1, 1, 5));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray(ArrayFloatNear(
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{0.0f, 1.0f, 2.0f, 1.0f, 0.0f}, 1e-3)));
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}
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TEST(SpectrogramOpTest, SquaredTest) {
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BaseAudioSpectrogramOpModel m({TensorType_FLOAT32, {8, 1}},
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{TensorType_FLOAT32, {}}, 8, 1, true);
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m.PopulateTensor<float>(m.input1(),
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{-1.0f, 0.0f, 1.0f, 0.0f, -1.0f, 0.0f, 1.0f, 0.0f});
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m.Invoke();
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std::vector<int> output_shape = m.GetOutputShape();
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EXPECT_EQ(3, output_shape.size());
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EXPECT_THAT(output_shape, ElementsAre(1, 1, 5));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray(ArrayFloatNear(
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{0.f, 1.f, 4.f, 1.f, 0.f}, 1e-3)));
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}
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TEST(SpectrogramOpTest, StrideTest) {
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BaseAudioSpectrogramOpModel m({TensorType_FLOAT32, {10, 1}},
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{TensorType_FLOAT32, {}}, 8, 2, true);
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m.PopulateTensor<float>(m.input1(), {-1.0f, 0.0f, 1.0f, 0.0f, -1.0f, 0.0f,
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1.0f, 0.0f, 1.0f, 0.0f});
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m.Invoke();
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std::vector<int> output_shape = m.GetOutputShape();
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EXPECT_THAT(output_shape, ElementsAre(1, 2, 5));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray(ArrayFloatNear(
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{0, 1, 4, 1, 0, 1, 2, 1, 2, 1}, 1e-3)));
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}
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} // namespace
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} // namespace custom
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} // namespace ops
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} // namespace tflite
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