70 lines
2.7 KiB
C++
70 lines
2.7 KiB
C++
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// Copyright (C) 2018-2025 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#pragma once
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#include "openvino/op/op.hpp"
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namespace ov {
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namespace op {
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namespace v1 {
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/// \brief Tensor dynamic reshape operation.
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///
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/// "Converts" an input tensor into a new shape with the same number of elements.
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/// This op does not touch the actual data. If needed, use Transpose for that purpose.
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///
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/// \ingroup ov_ops_cpp_api
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class OPENVINO_API Reshape : public Op {
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public:
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OPENVINO_OP("Reshape", "opset1", op::Op);
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Reshape() = default;
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/// \brief Constructs a dynamic reshape operation. This operation does not perform
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/// transpose.
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///
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/// \param arg The tensor to be reshaped.
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/// \param shape_pattern The node that defines output shape shape_pattern.
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/// If the input shape is \f$(a_0,\dots,a_{k-1})\f$ then the output shape
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/// must
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/// be of the form \f$(b_0,\dots,b_{j-1})\f$ where \f$\Pi(a_i) = \Pi(b_i)\f$.
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/// A value of -1 is allowed for at most one dimension, in which case the
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/// dimension size is inferred based on element count of input tensor.
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/// \param special_zero Treats zeros in `shape_pattern` as wildcard flags indicating
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/// a
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/// copy from input shape at the same index.
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///
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Reshape(const Output<Node>& arg, const Output<Node>& shape_pattern, bool special_zero);
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bool visit_attributes(AttributeVisitor& visitor) override;
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void validate_and_infer_types() override;
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std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
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bool get_special_zero() const {
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return m_special_zero;
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}
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void set_special_zero(bool special_zero) {
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m_special_zero = special_zero;
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}
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bool evaluate(ov::TensorVector& outputs, const ov::TensorVector& inputs) const override;
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bool has_evaluate() const override;
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bool evaluate_upper(TensorVector& outputs) const override;
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bool evaluate_lower(TensorVector& outputs) const override;
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bool evaluate_symbol(TensorSymbolVector& output_symbols) const override;
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bool constant_fold(OutputVector& output_values, const OutputVector& inputs_values) override;
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bool can_constant_fold(const OutputVector& inputs_values) const override;
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protected:
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bool m_special_zero;
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bool evaluate_reshape(ov::TensorVector& outputs, const ov::TensorVector& inputs) const;
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private:
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void calculate_output_shape(std::vector<Dimension>& reshape_pattern,
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const int64_t& minus_one_idx,
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const PartialShape& input_pshape,
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std::vector<Dimension>& output_shape) const;
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};
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} // namespace v1
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} // namespace op
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} // namespace ov
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