# EmbeddingBagOffsetsSum {#openvino_docs_ops_sparse_EmbeddingBagOffsetsSum_3}

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.. meta::
  :description: Learn about EmbeddingBagOffsetsSum-3 - a sparse operation, which 
                can be performed on three required and two optional input tensors.

**Versioned name**: *EmbeddingBagOffsetsSum-3*

**Category**: *Sparse*

**Short description**: Computes sums of "bags" of embeddings, without instantiating the intermediate embeddings.

**Detailed description**: This is the second case of the PyTorch `EmbeddingBag <https://pytorch.org/docs/stable/nn.html#embeddingbag>`__ , it has indices in two 1D tensors provided as 2nd and 3rd inputs. For each index in ``indices`` this operator gets values from ``data`` embedding table and sums all values belonging to each bag. Values in ``offsets`` define starting index in ``indices`` tensor of each "bag", e.g. ``offsets`` with value ``[0,3,4,4,6]`` define 5 "bags" containing ``[3,1,0,2,n-6]`` elements.

**Attributes**: EmbeddingBagOffsetsSum operation has no attributes.

**Inputs**:

* **1**: ``emb_table`` tensor containing the embedding lookup table of the module of shape ``[num_emb, emb_dim1, emb_dim2, ...]`` and  of type *T*. **Required.**
* **2**: ``indices`` tensor of shape ``[num_indices]`` and of type *T_IND*. **Required.**
* **3**: ``offsets`` tensor of shape ``[batch]`` and of type *T_IND* containing the starting index positions of each "bag" in ``indices``. **Required.**
* **4**: ``default_index`` scalar of type *T_IND* containing default index in embedding table to fill empty "bags". If not provided empty "bags" are filled with zeros. **Optional.**
* **5**: ``per_sample_weights`` tensor of the same shape as ``indices`` and of type *T*. Each value in this tensor are multiplied with each value pooled from embedding table for each index. Optional, default is tensor of ones.

**Outputs**:

* **1**: tensor of shape ``[batch, emb_dim1, emb_dim2, ...]`` and of type *T* containing embeddings for each bag.

**Types**

* *T*: any numeric type.
* *T_IND*: ``int32`` or ``int64``.

**Example**

.. code-block:: cpp
   
   <layer ... type="EmbeddingBagOffsetsSum" ... >
       <input>
           <port id="0">     < !-- emb_table value is: [[-0.2, -0.6], [-0.1, -0.4], [-1.9, -1.8], [-1.,  1.5], [ 0.8, -0.7]] -->
               <dim>5</dim>
               <dim>2</dim>
           </port>
           <port id="1">     < !-- indices value is: [0, 2, 3, 4] -->
               <dim>4</dim>
           </port>
           <port id="2">     < !-- offsets value is: [0, 2, 2] - 3 "bags" containing [2,0,4-2] elements, second "bag" is empty -->
               <dim>3</dim>
           </port>
           <port id="3"/>    < !-- default_index value is: 0 -->
           <port id="4"/>    < !-- per_sample_weigths value is: [0.5, 0.5, 0.5, 0.5] -->
               <dim>4</dim>
           </port>
       </input>
       <output>
           <port id="5">     < !-- output value is: [[-1.05, -1.2], [-0.2, -0.6], [-0.1, 0.4]] -->
               <dim>3</dim>
               <dim>2</dim>
           </port>
       </output>
   </layer>

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