49 lines
2.0 KiB
C++
49 lines
2.0 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/core/axis_set.hpp"
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#include "openvino/op/util/embeddingbag_packed_base.hpp"
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#include "openvino/op/util/index_reduction.hpp"
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namespace ov {
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namespace op {
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namespace v15 {
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/// \brief Returns embeddings for given indices
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/// \ingroup ov_ops_cpp_api
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class OPENVINO_API EmbeddingBagPacked : public util::EmbeddingBagPackedBase {
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public:
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OPENVINO_OP("EmbeddingBagPacked", "opset15", util::EmbeddingBagPackedBase);
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/// \brief Constructs a EmbeddingBagPacked operation.
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EmbeddingBagPacked() = default;
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/// \brief Constructs a EmbeddingBagPacked operation.
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///
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/// EmbeddingBagPacked constructs an output tensor by replacing every index in a
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/// given
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/// input tensor with a row (from the weights matrix) at that index
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///
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/// \param emb_table Tensor containing the embedding lookup table of the module of
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/// shape [num_emb, emb_dim1, emb_dim2, ...] and of type T
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/// \param indices Tensor of shape `[batch, indices_per_bag]` and of type *T_IND*.
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/// Required.
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/// \param per_sample_weights tensor of the same shape as indices and of type T.
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/// Each value in this tensor are multiplied with each
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/// value pooled from embedding table for each index. Optional.
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/// \param reduction enum to select algorithm used to perform reduction of elements in bag. Optional.
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EmbeddingBagPacked(const Output<Node>& emb_table,
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const Output<Node>& indices,
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const Output<Node>& per_sample_weights,
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const Reduction& reduction = Reduction::SUM);
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EmbeddingBagPacked(const Output<Node>& emb_table,
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const Output<Node>& indices,
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const Reduction& reduction = Reduction::SUM);
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std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
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};
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} // namespace v15
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} // namespace op
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} // namespace ov
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