Elu - 1 vs 6#

Next section compares an older to a newer version of the same operator after both definition are converted into markdown text.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. Elu1 → Elu6 +4 -2
Elu1 → Elu6 RENAMED
@@ -1 +1 @@
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  Elu takes one input data (Tensor<T>) and produces one output data
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  (Tensor<T>) where the function f(x) = alpha * (exp(x) - 1.) for x <
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  0, f(x) = x for x >= 0., is applied to the tensor elementwise.
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  **Attributes**
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  * **alpha**:
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- Coefficient of ELU.
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+ Coefficient of ELU default to 1.0.
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+ * **consumed_inputs**:
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+ legacy optimization attribute.
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  **Inputs**
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  * **X** (heterogeneous) - **T**:
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  1D input tensor
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  **Outputs**
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  * **Y** (heterogeneous) - **T**:
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- 1D output tensor
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+ 1D input tensor
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  **Type Constraints**
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  * **T** in (
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  tensor(double),
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  tensor(float),
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  tensor(float16)
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  ):
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  Constrain input and output types to float tensors.