.. _l-onnx-op-squeeze-d1-13:

Squeeze - 1 vs 13
=================

Next section compares an older to a newer version of the same operator 
after both definition are converted into markdown text.
Green means an addition to the newer version, red means a deletion.
Anything else is unchanged.

.. raw:: html


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    --- a/Squeeze1
    +++ b/Squeeze13
    @@ -1 +1 @@
      Remove single-dimensional entries from the shape of a tensor.
    - Takes a  parameter axes with a list of axes to squeeze.
    ?         ^ ^^^^^ --
    + Takes an input axes with a list of axes to squeeze.
    ?        + ^^ ^
      If axes is not provided, all the single dimensions will be removed from
      the shape. If an axis is selected with shape entry not equal to one, an error is raised.
  
    - ### Attributes
    + ### Inputs
  
    + Between 1 and 2 inputs.
    - * **axes - INTS** :
    - 
    -   List of non-negative integers, indicate the dimensions to squeeze.
    - 
    - ### Inputs
  
      - **data** (heterogeneous) - **T**:
  
        Tensors with at least max(dims) dimensions.
    + - **axes** (optional, heterogeneous) - **tensor(int64)**:
    + 
    +   List of integers indicating the dimensions to squeeze. Negative value means counting dimensions from the back. Accepted range is [-r, r-1] where r = rank(data).
  
      ### Outputs
  
      - **squeezed** (heterogeneous) - **T**:
  
        Reshaped tensor with same data as input.
  
      ### Type Constraints
  
    - * **T** in ( 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) ):
    + * **T** in ( tensor(bfloat16), 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) ):
    ?             ++++++++++++++++++
  
        Constrain input and output types to all tensor types.
    `;

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