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[core]Migrate Sqrt operator to new API (#20632)

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* Migrate Sqrt operator to new API

* Remove 'visit_attributes' is same as base
This commit is contained in:
Pawel Raasz 2023-10-31 09:34:49 +01:00 committed by Alexander Nesterov
parent f9b76024aa
commit 261e570a81
3 changed files with 66 additions and 71 deletions
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5
src/core/include/openvino/op/sqrt.hpp
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@ -35,11 +35,8 @@ public:
Sqrt(const Output<Node>& arg);
Sqrt() = default;
bool visit_attributes(AttributeVisitor& visitor) override;
std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
OPENVINO_SUPPRESS_DEPRECATED_START
bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
OPENVINO_SUPPRESS_DEPRECATED_END
bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
bool has_evaluate() const override;
};
} // namespace v0

32
src/core/reference/include/openvino/reference/sqrt.hpp
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@ -6,21 +6,33 @@
#include <cmath>
#include <cstddef>
#include <type_traits>
#include "openvino/reference/utils/type_util.hpp"
namespace ov {
namespace reference {
template <typename T>
typename std::enable_if<!std::is_integral<T>::value>::type sqrt(const T* arg, T* out, size_t count) {
for (size_t i = 0; i < count; i++) {
out[i] = std::sqrt(arg[i]);
namespace func {
template <class T, typename std::enable_if<ov::is_floating_point<T>()>::type* = nullptr>
T sqrt(const T in) {
return std::sqrt(in);
}
template <class T, typename std::enable_if<std::is_integral<T>::value>::type* = nullptr>
T sqrt(const T in) {
return static_cast<T>(std::round(std::sqrt(in)));
}
template <typename T>
typename std::enable_if<std::is_integral<T>::value>::type sqrt(const T* arg, T* out, size_t count) {
for (size_t i = 0; i < count; i++) {
out[i] = static_cast<T>(std::round(std::sqrt(arg[i])));
}
} // namespace func
/**
* @brief Reference implementation of Sqrt operator.
*
* @param arg Pointer to input data.
* @param out Pointer to output data.
* @param count Number of elements in input buffer.
*/
template <class T>
void sqrt(const T* arg, T* out, const size_t count) {
std::transform(arg, arg + count, out, func::sqrt<T>);
}
} // namespace reference
} // namespace ov

98
src/core/src/op/sqrt.cpp
View File

@ -2,80 +2,66 @@
// SPDX-License-Identifier: Apache-2.0
//
#include "ngraph/op/sqrt.hpp"
#include "openvino/op/sqrt.hpp"
#include "element_visitor.hpp"
#include "itt.hpp"
#include "ngraph/op/add.hpp"
#include "ngraph/op/divide.hpp"
#include "ngraph/runtime/host_tensor.hpp"
#include "openvino/reference/sqrt.hpp"
using namespace std;
using namespace ngraph;
namespace ov {
namespace op {
namespace sqrt {
struct Evaluate : element::NoAction<bool> {
using element::NoAction<bool>::visit;
op::Sqrt::Sqrt(const Output<Node>& arg) : UnaryElementwiseArithmetic(arg) {
template <element::Type_t ET, class T = fundamental_type_for<ET>>
static result_type visit(const Tensor& arg0, Tensor& out, const size_t count) {
reference::sqrt(arg0.data<const T>(), out.data<T>(), count);
return true;
}
};
} // namespace sqrt
namespace v0 {
Sqrt::Sqrt(const Output<Node>& arg) : UnaryElementwiseArithmetic(arg) {
constructor_validate_and_infer_types();
}
bool ngraph::op::v0::Sqrt::visit_attributes(AttributeVisitor& visitor) {
OV_OP_SCOPE(v0_Sqrt_visit_attrinutes);
return true;
}
shared_ptr<Node> op::Sqrt::clone_with_new_inputs(const OutputVector& new_args) const {
std::shared_ptr<Node> Sqrt::clone_with_new_inputs(const OutputVector& new_args) const {
OV_OP_SCOPE(v0_Sqrt_clone_with_new_inputs);
check_new_args_count(this, new_args);
return make_shared<Sqrt>(new_args.at(0));
return std::make_shared<Sqrt>(new_args.at(0));
}
OPENVINO_SUPPRESS_DEPRECATED_START
namespace sqrtop {
namespace {
template <element::Type_t ET>
inline bool evaluate(const HostTensorPtr& arg0, const HostTensorPtr& out, const size_t count) {
using T = typename element_type_traits<ET>::value_type;
ov::reference::sqrt<T>(arg0->get_data_ptr<ET>(), out->get_data_ptr<ET>(), count);
return true;
}
bool evaluate_sqrt(const HostTensorPtr& arg0, const HostTensorPtr& out, const size_t count) {
bool rc = true;
out->set_unary(arg0);
switch (arg0->get_element_type()) {
OPENVINO_TYPE_CASE(evaluate_sqrt, i32, arg0, out, count);
OPENVINO_TYPE_CASE(evaluate_sqrt, i64, arg0, out, count);
OPENVINO_TYPE_CASE(evaluate_sqrt, u32, arg0, out, count);
OPENVINO_TYPE_CASE(evaluate_sqrt, u64, arg0, out, count);
OPENVINO_TYPE_CASE(evaluate_sqrt, f16, arg0, out, count);
OPENVINO_TYPE_CASE(evaluate_sqrt, f32, arg0, out, count);
OPENVINO_TYPE_CASE(evaluate_sqrt, f64, arg0, out, count);
default:
rc = false;
break;
}
return rc;
}
} // namespace
} // namespace sqrtop
bool op::Sqrt::evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const {
bool Sqrt::evaluate(TensorVector& outputs, const TensorVector& inputs) const {
OV_OP_SCOPE(v0_Sqrt_evaluate);
return sqrtop::evaluate_sqrt(inputs[0], outputs[0], shape_size(inputs[0]->get_shape()));
OPENVINO_ASSERT(outputs.size() == 1);
OPENVINO_ASSERT(inputs.size() == 1);
const auto& in_shape = inputs[0].get_shape();
outputs[0].set_shape(in_shape);
using namespace ov::element;
return IfTypeOf<f16, f32, f64, i32, i64, u32, u64>::apply<sqrt::Evaluate>(inputs[0].get_element_type(),
inputs[0],
outputs[0],
shape_size(in_shape));
}
bool op::Sqrt::has_evaluate() const {
bool Sqrt::has_evaluate() const {
OV_OP_SCOPE(v0_Sqrt_has_evaluate);
switch (get_input_element_type(0)) {
case ngraph::element::i32:
case ngraph::element::i64:
case ngraph::element::u32:
case ngraph::element::u64:
case ngraph::element::f16:
case ngraph::element::f32:
case ngraph::element::f64:
case element::f16:
case element::f32:
case element::f64:
case element::i32:
case element::i64:
case element::u32:
case element::u64:
return true;
default:
break;
}
return false;
}
}
} // namespace v0
} // namespace op
} // namespace ov