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.. _op_ai_onnx_Unsqueeze-1:

Unsqueeze - version 1
=====================

This page documents version **1** of operator **Unsqueeze**. See :doc:`Unsqueeze` for the latest version (since version 25).

- **Domain**: ``ai.onnx``
- **Since version**: 1

Insert single-dimensional entries to the shape of an input tensor (``data``).
Takes one required argument ``axes`` - which contains a list of dimension indices and this operator will insert a dimension of value ``1`` into the corresponding index of the output tensor (``expanded``).

For example:

.. code-block:: text

    Given an input tensor (`data`) of shape [3, 4, 5], then
    Unsqueeze(data, axes=[0, 4]) outputs a tensor (`expanded`) containing the same data as `data` but with shape [1, 3, 4, 5, 1].

The attribute ``axes`` should not contain any duplicate entries. It is an error if it contains duplicates.
The rank of the output tensor (``output_rank``) is the rank of the input tensor (``data``) plus the number of values in ``axes``.
Each value in ``axes`` should be within the (inclusive) range [-output_rank , output_rank - 1].
The order of values in ``axes`` does not matter and can come in any order.

**Inputs**

- **data** (*T*): Original tensor

**Outputs**

- **expanded** (*T*): Reshaped tensor with same data as input.

**Attributes**

- **axes** (*int[]*): List of non-negative integers, indicate the dimensions to be inserted

**Type Constraints**

- **T**: Constrain input and output types to all tensor types.
  Allowed types: tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8).