PRelu - 1 vs 7

Next section compares an older to a newer version of the same operator after both definition are converted into markdown text.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.

Files changed (1) hide show
  1. PRelu1 → PRelu7 +3 -8
PRelu1 → PRelu7 RENAMED
@@ -1 +1 @@
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  PRelu takes input data (Tensor<T>) and slope tensor as input, and produces one
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  output data (Tensor<T>) where the function f(x) = slope * x for x < 0,
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  f(x) = x for x >= 0., is applied to the data tensor elementwise.
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+ 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).
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-
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- ### Attributes
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-
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- * **consumed_inputs - INTS** :
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-
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- legacy optimization attribute.
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  ### Inputs
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  - **X** (heterogeneous) - **T**:
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  Input tensor
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  - **slope** (heterogeneous) - **T**:
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- Slope tensor. If Slope is of size 1, the value is sharedacross different channels
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+ Slope tensor. The shape of slope can be smaller than first input X; if so, its shape must be unidirectional broadcastable to X
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  ### Outputs
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  - **Y** (heterogeneous) - **T**:
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- Output tensor
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+ Output tensor (same size as X)
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  ### Type Constraints
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  * **T** in ( tensor(double), tensor(float), tensor(float16) ):
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  Constrain input and output types to float tensors.