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[IE TESTS] GatherTree single layer test has been created. (#2006)

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* [IE TESTS] GatherTree op ref function has been created.

* [IE TESTS] Added GatherTree single layer test

* [IE TESTS] Fixed code styles.

* [IE TESTS] GatherTree test FP32 precion was enabled.

* [IE TESTS] Refactoring of Builder::makeConstatn procedure

The refactoring is aimed at managing the range of random data for the constants initialization procedure.

* [IE TESTS] GatherTree test was extended with constants

* [IE TESTS] GatherTree ref rewritten to non-templated function.

* [IE TESTS] GatherTree test inp shape indx enum removed.

* Revert "[IE TESTS] Refactoring of Builder::makeConstatn procedure"

This reverts commit 2648172e00ccca266d39e8775b890b8a8395f57c.

* [IE TESTS] makeConstant was augmented with random data range parameters.

* [IE TESTS] GatherTree test was rewritten using makeConstant function.

* [IE TESTS] GaterTree test call templated makeConstant

* [IE TESTS] GaterTree test code style fix
This commit is contained in:
Maksim Kutakov
2020-09-07 17:17:14 +03:00
committed by GitHub
parent 52ebe68cc7
commit 2c7f06e08f
9 changed files with 367 additions and 10 deletions
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9
inference-engine/tests/ngraph_functions/include/ngraph_functions/builders.hpp
View File

@@ -24,27 +24,28 @@ makeParams(const element::Type &type, const std::vector<std::pair<std::string, s
template<typename T>
std::shared_ptr<Node> makeConstant(const element::Type &type, const std::vector<size_t> &shape,
const std::vector<T> &data, bool random = false) {
const std::vector<T> &data, bool random = false,
uint32_t upTo = 10, uint32_t startFrom = 1) {
std::shared_ptr<ngraph::Node> weightsNode;
#define makeNode(TYPE) \
case TYPE: \
weightsNode = std::make_shared<ngraph::opset1::Constant>( \
type, shape, \
random ? NGraphFunctions::Utils::generateVector<TYPE>(ngraph::shape_size(shape)) : \
random ? NGraphFunctions::Utils::generateVector<TYPE>(ngraph::shape_size(shape), upTo, startFrom) : \
NGraphFunctions::Utils::castVector<T, ngraph::helpers::nGraphTypesTrait<TYPE>::value_type >(data)); \
break;
switch (type) {
case ngraph::element::Type_t::bf16:
weightsNode = std::make_shared<ngraph::opset1::Constant>(
type, shape,
random ? NGraphFunctions::Utils::generateBF16Vector(ngraph::shape_size(shape)) :
random ? NGraphFunctions::Utils::generateBF16Vector(ngraph::shape_size(shape), upTo, startFrom) :
NGraphFunctions::Utils::castVector<T, ngraph::bfloat16>(data));
break;
case ngraph::element::Type_t::f16:
weightsNode = std::make_shared<ngraph::opset1::Constant>(
type, shape,
random ? NGraphFunctions::Utils::generateF16Vector(ngraph::shape_size(shape)) :
random ? NGraphFunctions::Utils::generateF16Vector(ngraph::shape_size(shape), upTo, startFrom) :
NGraphFunctions::Utils::castVector<T, ngraph::float16>(data));
break;
makeNode(ngraph::element::Type_t::f32);

12
inference-engine/tests/ngraph_functions/include/ngraph_functions/utils/data_utils.hpp
View File

@@ -17,13 +17,13 @@ namespace Utils {
template<ngraph::element::Type_t dType>
std::vector<typename ngraph::helpers::nGraphTypesTrait<dType>::value_type> inline
generateVector(size_t vec_len) {
generateVector(size_t vec_len, uint32_t upTo = 10, uint32_t startFrom = 1) {
std::vector<typename ngraph::helpers::nGraphTypesTrait<dType>::value_type> res;
std::mt19937 gen(
static_cast<unsigned long>(std::chrono::high_resolution_clock::now().time_since_epoch().count()));
// chose values between this range to avoid type overrun (e.g. in case of I8 precision)
std::uniform_int_distribution<unsigned long> dist(1, 10);
std::uniform_int_distribution<unsigned long> dist(startFrom, upTo);
for (int i = 0; i < vec_len; i++) {
res.push_back(
@@ -32,13 +32,13 @@ generateVector(size_t vec_len) {
return res;
}
std::vector<ngraph::float16> inline generateF16Vector(size_t vec_len) {
std::vector<ngraph::float16> inline generateF16Vector(size_t vec_len, uint32_t upTo = 10, uint32_t startFrom = 1) {
std::vector<ngraph::float16> res;
std::mt19937 gen(
static_cast<unsigned long>(std::chrono::high_resolution_clock::now().time_since_epoch().count()));
// chose values between this range to avoid type overrun (e.g. in case of I8 precision)
std::uniform_int_distribution<unsigned long> dist(1, 10);
std::uniform_int_distribution<unsigned long> dist(startFrom, upTo);
for (int i = 0; i < vec_len; i++) {
res.emplace_back(ngraph::float16(static_cast<float>(dist(gen))));
@@ -46,13 +46,13 @@ std::vector<ngraph::float16> inline generateF16Vector(size_t vec_len) {
return res;
}
std::vector<ngraph::bfloat16> inline generateBF16Vector(size_t vec_len) {
std::vector<ngraph::bfloat16> inline generateBF16Vector(size_t vec_len, uint32_t upTo = 10, uint32_t startFrom = 1) {
std::vector<ngraph::bfloat16> res;
std::mt19937 gen(
static_cast<unsigned long>(std::chrono::high_resolution_clock::now().time_since_epoch().count()));
// chose values between this range to avoid type overrun (e.g. in case of I8 precision)
std::uniform_int_distribution<unsigned long> dist(1, 10);
std::uniform_int_distribution<unsigned long> dist(startFrom, upTo);
for (int i = 0; i < vec_len; i++) {
res.emplace_back(ngraph::bfloat16(static_cast<float>(dist(gen))));