59 lines
1.6 KiB
C++
59 lines
1.6 KiB
C++
|
|
// Copyright (C) 2018-2025 Intel Corporation
|
||
|
|
// SPDX-License-Identifier: Apache-2.0
|
||
|
|
//
|
||
|
|
|
||
|
|
#pragma once
|
||
|
|
|
||
|
|
#include <memory>
|
||
|
|
|
||
|
|
#include "openvino/op/op.hpp"
|
||
|
|
|
||
|
|
namespace ov {
|
||
|
|
namespace op {
|
||
|
|
namespace v0 {
|
||
|
|
/// \brief Permutes data in the channel dimension of the input
|
||
|
|
/// \ingroup ov_ops_cpp_api
|
||
|
|
class OPENVINO_API ShuffleChannels : public Op {
|
||
|
|
public:
|
||
|
|
OPENVINO_OP("ShuffleChannels", "opset1");
|
||
|
|
|
||
|
|
ShuffleChannels() = default;
|
||
|
|
/// \brief Constructs a ShuffleChannels node.
|
||
|
|
///
|
||
|
|
/// \param data Node producing the input tensor.
|
||
|
|
/// \param axis Channel dimension index in the data tensor.
|
||
|
|
/// A negative value means that the index should be
|
||
|
|
/// calculated from the back of the input data shape.
|
||
|
|
/// \param group Number of group the channel dimension should be split into.
|
||
|
|
///
|
||
|
|
ShuffleChannels(const Output<Node>& data, const int64_t axis = 1, const int64_t group = 1);
|
||
|
|
|
||
|
|
bool visit_attributes(AttributeVisitor& visitor) override;
|
||
|
|
size_t get_zero_based_axis() const;
|
||
|
|
|
||
|
|
void validate_and_infer_types() override;
|
||
|
|
|
||
|
|
std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
|
||
|
|
|
||
|
|
void set_axis(int64_t axis);
|
||
|
|
|
||
|
|
const int64_t& get_axis() const {
|
||
|
|
return m_axis;
|
||
|
|
}
|
||
|
|
|
||
|
|
void set_group(int64_t group);
|
||
|
|
|
||
|
|
const int64_t& get_group() const {
|
||
|
|
return m_group;
|
||
|
|
}
|
||
|
|
bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
|
||
|
|
bool has_evaluate() const override;
|
||
|
|
|
||
|
|
private:
|
||
|
|
int64_t m_axis{1};
|
||
|
|
int64_t m_group{1};
|
||
|
|
};
|
||
|
|
} // namespace v0
|
||
|
|
} // namespace op
|
||
|
|
} // namespace ov
|