.. _l-onnx-op-prelu-d9-16:

PRelu - 9 vs 16
===============

Next section compares an older to a newer version of the same operator 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/PRelu9
    +++ b/PRelu16
    @@ -1 +1 @@
      PRelu takes input data (Tensor<T>) and slope tensor as input, and produces one
      output data (Tensor<T>) where the function f(x) = slope * x for x < 0,
      f(x) = x for x >= 0., is applied to the data tensor elementwise.
      This operator supports **unidirectional broadcasting** (tensor slope should be unidirectional broadcastable to input tensor X); for more details please check [Broadcasting in ONNX](https://github.com/onnx/onnx/blob/main/docs/Broadcasting.md).
    + 
    + #### Function Body
    + 
    + The function definition for this operator.
    + 
    + 
    + <
    +   domain: "",
    +   opset_import: ["" : 16]
    + >
    + PRelu (X, slope) => (Y)
    + {
    +    Zero = Constant <value: tensor = float {0}> ()
    +    ZeroCast = CastLike (Zero, X)
    +    XLessThanZero = Less (X, ZeroCast)
    +    SlopeMulX = Mul (slope, X)
    +    Y = Where (XLessThanZero, SlopeMulX, X)
    + }
    + 
  
      ### Inputs
  
      - **X** (heterogeneous) - **T**:
  
        Input tensor
      - **slope** (heterogeneous) - **T**:
  
        Slope tensor. The shape of slope can be smaller than first input X; if so, its shape must be unidirectional broadcastable to X
  
      ### Outputs
  
      - **Y** (heterogeneous) - **T**:
  
        Output tensor (same size as X)
  
      ### Type Constraints
  
    - * **T** in ( tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) ):
    + * **T** in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) ):
    ?             ++++++++++++++++++
  
        Constrain input and output types to float/int tensors.
    `;

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