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Fix fill_tensor_random for real values: (#19095)

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Oleg Pipikin 2023-08-11 22:26:17 +02:00 committed by GitHub
parent 545c5bbde1
commit 5379068610
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2 changed files with 6 additions and 10 deletions
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3
src/tests/test_utils/common_test_utils/include/common_test_utils/data_utils.hpp
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@ -266,8 +266,7 @@ void inline fill_random_unique_sequence(T* rawBlobDataPtr,
* - With k = 2 numbers resolution will 1/2 so outputs only .0 or .50 * - With k = 2 numbers resolution will 1/2 so outputs only .0 or .50
* - With k = 4 numbers resolution will 1/4 so outputs only .0 .25 .50 0.75 and etc. * - With k = 4 numbers resolution will 1/4 so outputs only .0 .25 .50 0.75 and etc.
*/ */
void fill_tensor_random(ov::Tensor& tensor, const uint32_t range = 10, int32_t start_from = 0, void fill_tensor_random(ov::Tensor& tensor, const double range = 10, const double start_from = 0, const int32_t k = 1, const int seed = 1);
const int32_t k = 1, const int seed = 1);
/** @brief Fill blob with random data. /** @brief Fill blob with random data.
* *

13
src/tests/test_utils/common_test_utils/src/data_utils.cpp
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@ -357,8 +357,7 @@ void fill_data_with_broadcast(ov::Tensor& tensor, size_t axis, std::vector<float
} }
template<ov::element::Type_t DT> template<ov::element::Type_t DT>
void fill_tensor_random(ov::Tensor& tensor, const uint32_t range = 10, int32_t start_from = 0, void fill_tensor_random(ov::Tensor& tensor, const uint32_t range, const int32_t start_from, const int32_t k, const int seed) {
const int32_t k = 1, const int seed = 1) {
using T = typename ov::element_type_traits<DT>::value_type; using T = typename ov::element_type_traits<DT>::value_type;
auto *rawBlobDataPtr = static_cast<T*>(tensor.data()); auto *rawBlobDataPtr = static_cast<T*>(tensor.data());
if (DT == ov::element::u4 || DT == ov::element::i4 || if (DT == ov::element::u4 || DT == ov::element::i4 ||
@ -370,12 +369,11 @@ void fill_tensor_random(ov::Tensor& tensor, const uint32_t range = 10, int32_t s
} }
template<ov::element::Type_t DT> template<ov::element::Type_t DT>
void fill_tensor_random_float(ov::Tensor& tensor, const uint32_t range, int32_t start_from, const int32_t k, void fill_tensor_random_float(ov::Tensor& tensor, const double range, const double start_from, const int32_t k, const int seed) {
const int seed = 1) {
using T = typename ov::element_type_traits<DT>::value_type; using T = typename ov::element_type_traits<DT>::value_type;
std::default_random_engine random(seed); std::default_random_engine random(seed);
// 1/k is the resolution of the floating point numbers // 1/k is the resolution of the floating point numbers
std::uniform_int_distribution<int32_t> distribution(k * start_from, k * (start_from + range)); std::uniform_real_distribution<double> distribution(k * start_from, k * (start_from + range));
auto *rawBlobDataPtr = static_cast<T*>(tensor.data()); auto *rawBlobDataPtr = static_cast<T*>(tensor.data());
for (size_t i = 0; i < tensor.get_size(); i++) { for (size_t i = 0; i < tensor.get_size(); i++) {
@ -391,11 +389,10 @@ void fill_tensor_random_float(ov::Tensor& tensor, const uint32_t range, int32_t
} }
} }
void fill_tensor_random(ov::Tensor& tensor, const uint32_t range, int32_t start_from, void fill_tensor_random(ov::Tensor& tensor, const double range, const double start_from, const int32_t k, const int seed) {
const int32_t k, const int seed) {
auto element_type = tensor.get_element_type(); auto element_type = tensor.get_element_type();
#define CASE(X) case X: fill_tensor_random<X>(tensor, range, start_from, k, seed); break; #define CASE(X) case X: fill_tensor_random<X>(tensor, static_cast<uint32_t>(range), static_cast<int32_t>(start_from), k, seed); break;
#define CASE_FLOAT(X) case X: fill_tensor_random_float<X>(tensor, range, start_from, k, seed); break; #define CASE_FLOAT(X) case X: fill_tensor_random_float<X>(tensor, range, start_from, k, seed); break;
switch (element_type) { switch (element_type) {