depth_to_space.hpp

// Copyright (C) 2018-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
 
#pragma once
 
#include "ngraph/node.hpp"
#include "ngraph/op/op.hpp"
#include "ngraph/op/util/attr_types.hpp"
#include "ngraph/op/util/fused_op.hpp"
#include "ngraph/runtime/host_tensor.hpp"
 
namespace ngraph
{
    namespace op
    {
        namespace v0
        {
            /// \brief DepthToSpace permutes data from the depth dimension of the input blob into
            ///        spatial dimensions.
            ///
            /// \note  Values from the depth dimension (assuming NCHW layout) are moved in
            ///        spatial blocks to the height and width dimensions.
            ///
            ///        Output node produces a tensor with shape:
            ///        [N, C/(blocksize * blocksize), H * blocksize, W * blocksize]
            class NGRAPH_API DepthToSpace : public Op
            {
            public:
                NGRAPH_RTTI_DECLARATION;
 
                enum class DepthToSpaceMode
                {
                    // The input depth is divided to [block_size, ..., block_size, new_depth]
                    BLOCKS_FIRST,
                    // The input depth is divided to [new_depth, block_size, ..., block_size]
                    DEPTH_FIRST
                };
 
                DepthToSpace() = default;
                /// \brief Constructs a DepthToSpace operation.
                ///
                /// \param data Node producing the input tensor
                /// \param mode Specifies how the input depth dimension is split to block
                /// coordinates
                /// \param block_size The size of the block of values to be moved
                DepthToSpace(const Output<Node>& data,
                             const DepthToSpaceMode& mode,
                             std::size_t block_size = 1);
 
                DepthToSpace(const Output<Node>& data,
                             const std::string& mode,
                             std::size_t block_size = 1);
                bool visit_attributes(AttributeVisitor& visitor) override;
 
                std::size_t get_block_size() const { return m_blocksize; }
                DepthToSpaceMode get_mode() const { return m_mode; }
                virtual std::shared_ptr<Node>
                    clone_with_new_inputs(const OutputVector& new_args) const override;
                void validate_and_infer_types() override;
                bool evaluate(const HostTensorVector& outputs,
                              const HostTensorVector& inputs) const override;
                bool has_evaluate() const override;
 
            protected:
                std::size_t m_blocksize;
                DepthToSpaceMode m_mode;
                DepthToSpaceMode mode_from_string(const std::string& mode) const;
 
            private:
                bool evaluate_depth_to_space(const HostTensorVector& outputs,
                                             const HostTensorVector& inputs) const;
            };
        } // namespace v0
        using v0::DepthToSpace;
    } // namespace op
 
    NGRAPH_API
    std::ostream& operator<<(std::ostream& s, const op::v0::DepthToSpace::DepthToSpaceMode& type);
 
    template <>
    class NGRAPH_API AttributeAdapter<op::v0::DepthToSpace::DepthToSpaceMode>
        : public EnumAttributeAdapterBase<op::v0::DepthToSpace::DepthToSpaceMode>
    {
    public:
        AttributeAdapter(op::v0::DepthToSpace::DepthToSpaceMode& value)
            : EnumAttributeAdapterBase<op::v0::DepthToSpace::DepthToSpaceMode>(value)
        {
        }
 
        static constexpr DiscreteTypeInfo type_info{
            "AttributeAdapter<op::v0::DepthToSpace::DepthToSpaceMode>", 0};
        const DiscreteTypeInfo& get_type_info() const override { return type_info; }
    };
} // namespace ngraph