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image_transpose_test.cpp
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#include "gtest/gtest.h"
extern "C" {
#include "src/new_ops1/image_transpose.h"
// #include "src/tool/tool.h"
}
void image_transpose_assign_float(Tensor t) {
int64_t size = aitisa_tensor_size(t);
float* data = (float*)aitisa_tensor_data(t);
float value = 0;
for (int i = 0; i < size; ++i) {
value = i * 0.1 - 0.3;
data[i] = value;
}
}
namespace aitisa_api {
namespace {
TEST(ImageTranspose, Float2d) {
Tensor input;
DataType dtype = kFloat;
Device device = {DEVICE_CPU, 0};
int64_t dims[2] = {2, 3};
aitisa_create(dtype, device, dims, 2, NULL, 0, &input);
image_transpose_assign_float(input);
// tensor_printer2d(input);
Tensor output;
aitisa_image_transpose(input, &output);
// tensor_printer2d(output);
float* out_data = (float*)aitisa_tensor_data(output);
float test_data[] = {-0.3, 0, -0.2, 0.1, -0.1, 0.2};
int64_t size = aitisa_tensor_size(input);
for (int64_t i = 0; i < size; i++) {
/* Due to the problem of precision, consider the two numbers
are equal when their difference is less than 0.000001*/
EXPECT_TRUE(abs(out_data[i] - test_data[i]) < 0.000001);
}
aitisa_destroy(&input);
aitisa_destroy(&output);
}
TEST(ImageTranspose, Float3d) {
Tensor input;
DataType dtype = kFloat;
Device device = {DEVICE_CPU, 0};
int64_t dims[3] = {2, 2, 3};
aitisa_create(dtype, device, dims, 3, NULL, 0, &input);
image_transpose_assign_float(input);
// tensor_printer2d(input);
Tensor output;
aitisa_image_transpose(input, &output);
// tensor_printer2d(output);
float* out_data = (float*)aitisa_tensor_data(output);
float test_data[] = {-0.3, 0, -0.2, 0.1, -0.1, 0.2,
0.3, 0.6, 0.4, 0.7, 0.5, 0.8};
int64_t size = aitisa_tensor_size(input);
for (int64_t i = 0; i < size; i++) {
/* Due to the problem of precision, consider the two numbers
are equal when their difference is less than 0.000001*/
EXPECT_TRUE(abs(out_data[i] - test_data[i]) < 0.000001);
}
aitisa_destroy(&input);
aitisa_destroy(&output);
}
TEST(ImageTranspose, Float4d) {
Tensor input;
DataType dtype = kFloat;
Device device = {DEVICE_CPU, 0};
int64_t dims[4] = {2, 2, 2, 3};
aitisa_create(dtype, device, dims, 4, NULL, 0, &input);
image_transpose_assign_float(input);
// tensor_printer2d(input);
Tensor output;
aitisa_image_transpose(input, &output);
// tensor_printer2d(output);
float* out_data = (float*)aitisa_tensor_data(output);
float test_data[] = {-0.3, 0, -0.2, 0.1, -0.1, 0.2, 0.3, 0.6,
0.4, 0.7, 0.5, 0.8, 0.9, 1.2, 1., 1.3,
1.1, 1.4, 1.5, 1.8, 1.6, 1.9, 1.7, 2.};
int64_t size = aitisa_tensor_size(input);
for (int64_t i = 0; i < size; i++) {
/* Due to the problem of precision, consider the two numbers
are equal when their difference is less than 0.000001*/
EXPECT_TRUE(abs(out_data[i] - test_data[i]) < 0.000001);
}
aitisa_destroy(&input);
aitisa_destroy(&output);
}
} // namespace
} // namespace aitisa_api