mirror of
https://github.com/vee1e/tflite-micro.git
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135 lines
4.7 KiB
C++
135 lines
4.7 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/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_v2.h"
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namespace tflite {
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namespace testing {
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namespace {
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void ValidateShape(TfLiteTensor* tensors, const int tensor_count,
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int32_t* output_data, const int32_t* expected_output,
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int output_dims_count) {
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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_SHAPE();
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micro::KernelRunner runner(registration, tensors, tensor_count, inputs_array,
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outputs_array, nullptr);
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EXPECT_EQ(kTfLiteOk, runner.InitAndPrepare());
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EXPECT_EQ(kTfLiteOk, runner.Invoke());
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for (int i = 0; i < output_dims_count; ++i) {
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EXPECT_EQ(expected_output[i], output_data[i]);
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}
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}
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void TestShape(int* input_dims_data, const float* input_data,
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int* output_dims_data, const int32_t* expected_output_data,
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int32_t* 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_dims_count = ElementCount(*output_dims);
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constexpr int inputs_size = 1;
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constexpr int outputs_size = 1;
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constexpr int tensors_size = inputs_size + outputs_size;
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TfLiteTensor tensors[tensors_size] = {
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CreateTensor(input_data, input_dims),
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CreateTensor(output_data, output_dims, true),
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};
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ValidateShape(tensors, tensors_size, output_data, expected_output_data,
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output_dims_count);
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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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TEST(ShapeTest, TestShape0) {
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int input_shape[] = {1, 5};
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float input_values[] = {1, 3, 1, 3, 5};
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int output_dims[] = {1, 1}; // this is actually input_shapes shape
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int32_t expected_output_data[] = {5};
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int32_t output_data[1];
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tflite::testing::TestShape(input_shape, input_values, output_dims,
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expected_output_data, output_data);
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}
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TEST(ShapeTest, TestShape1) {
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int input_shape[] = {2, 4, 3};
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float input_values[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
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int output_dims[] = {2, 1, 1};
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int32_t expected_output_data[] = {4, 3};
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int32_t output_data[2];
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tflite::testing::TestShape(input_shape, input_values, output_dims,
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expected_output_data, output_data);
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}
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TEST(ShapeTest, TestShape2) {
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int input_shape[] = {2, 12, 1};
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float input_values[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
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int output_dims[] = {2, 1, 1};
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int32_t expected_output_data[] = {12, 1};
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int32_t output_data[2];
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tflite::testing::TestShape(input_shape, input_values, output_dims,
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expected_output_data, output_data);
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}
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TEST(ShapeTest, TestShape3) {
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int input_shape[] = {2, 2, 6};
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float input_values[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
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int output_dims[] = {2, 1, 1};
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int32_t expected_output_data[] = {2, 6};
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int32_t output_data[2];
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tflite::testing::TestShape(input_shape, input_values, output_dims,
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expected_output_data, output_data);
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}
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TEST(ShapeTest, TestShape4) {
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int input_shape[] = {2, 2, 2, 3};
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float input_values[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
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int output_dims[] = {3, 1, 1, 1};
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int32_t expected_output_data[] = {2, 2, 3};
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int32_t output_data[3];
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tflite::testing::TestShape(input_shape, input_values, output_dims,
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expected_output_data, output_data);
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}
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TEST(ShapeTest, TestShape5) {
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int input_shape[] = {1, 1};
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float input_values[] = {1};
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int output_dims[] = {1, 1};
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int32_t expected_output_data[] = {1};
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int32_t output_data[1];
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tflite::testing::TestShape(input_shape, input_values, output_dims,
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expected_output_data, output_data);
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}
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TF_LITE_MICRO_TESTS_MAIN
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