116 lines
4.3 KiB
C++
116 lines
4.3 KiB
C++
/* Copyright 2021 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/c/builtin_op_data.h"
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/micro/kernels/kernel_runner.h"
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#include "tensorflow/lite/micro/test_helpers.h"
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#include "tensorflow/lite/micro/testing/micro_test.h"
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namespace tflite {
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namespace testing {
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namespace {
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template <typename T>
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void ValidateDequantizeGoldens(TfLiteTensor* tensors, int tensors_size,
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const T* expected_output_data, T* output_data,
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int output_length, float tolerance = 1e-5) {
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int inputs_array_data[] = {1, 0};
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TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
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int outputs_array_data[] = {1, 1};
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TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);
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const TFLMRegistration registration = tflite::Register_DEQUANTIZE();
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micro::KernelRunner runner(registration, tensors, tensors_size, inputs_array,
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outputs_array,
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/*builtin_data=*/nullptr);
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TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.InitAndPrepare());
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TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.Invoke());
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for (int i = 0; i < output_length; ++i) {
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TF_LITE_MICRO_EXPECT_NEAR(expected_output_data[i], output_data[i], 0.001f);
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}
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}
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template <typename T>
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void TestDequantizeToFloat(int* input_dims_data, const float* input_data,
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T* input_data_quantized, float scale, int zero_point,
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int* output_dims_data,
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const float* expected_output_data,
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float* output_data) {
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TfLiteIntArray* input_dims = IntArrayFromInts(input_dims_data);
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TfLiteIntArray* output_dims = IntArrayFromInts(output_dims_data);
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const int output_length = ElementCount(*output_dims);
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// 1 input, 1 output.
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const int tensors_size = 2;
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TfLiteTensor tensors[tensors_size] = {
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CreateQuantizedTensor(input_data, input_data_quantized, input_dims, scale,
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zero_point),
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CreateTensor(output_data, output_dims),
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};
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ValidateDequantizeGoldens(tensors, tensors_size, expected_output_data,
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output_data, output_length);
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}
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} // namespace
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} // namespace testing
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} // namespace tflite
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TF_LITE_MICRO_TESTS_BEGIN
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TF_LITE_MICRO_TEST(DequantizeOpTestInt8) {
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const int length = 10;
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int dims[] = {2, 5, 2};
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const float values[] = {-63.5, -63, -62.5, -62, -61.5,
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62, 62.5, 63, 63.5, 64};
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const float scale = 0.5;
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const int zero_point = -1;
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int8_t input_quantized[length];
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float output[length];
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tflite::testing::TestDequantizeToFloat(dims, values, input_quantized, scale,
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zero_point, dims, values, output);
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}
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TF_LITE_MICRO_TEST(DequantizeOpTestInt16) {
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const int length = 10;
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int dims[] = {2, 5, 2};
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const float values[] = {-63.5, -63, -62.5, -62, -61.5,
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62, 62.5, 63, 63.5, 64};
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const float scale = 0.5;
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const int zero_point = -1;
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int16_t input_quantized[length];
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float output[length];
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tflite::testing::TestDequantizeToFloat(dims, values, input_quantized, scale,
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zero_point, dims, values, output);
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}
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TF_LITE_MICRO_TEST(DequantizeOpTestUint8) {
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const int length = 10;
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int dims[] = {2, 5, 2};
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const float values[] = {-63.5, -63, -62.5, -62, -61.5,
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62, 62.5, 63, 63.5, 64};
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const float scale = 0.5;
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const int zero_point = 127;
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uint8_t input_quantized[length];
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float output[length];
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tflite::testing::TestDequantizeToFloat(dims, values, input_quantized, scale,
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zero_point, dims, values, output);
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}
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TF_LITE_MICRO_TESTS_END
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