Pow - 7 vs 12

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  1. Pow7 → Pow12 +18 -3
Pow7 → Pow12 RENAMED
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  Pow takes input data (Tensor<T>) and exponent Tensor, and
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  produces one output data (Tensor<T>) where the function f(x) = x^exponent,
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  is applied to the data tensor elementwise.
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  This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check Broadcasting in ONNX <https://github.com/onnx/onnx/blob/master/docs/Broadcasting.md>_.
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  **Inputs**
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  * **X** (heterogeneous) - **T**:
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  First operand, base of the exponent.
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- * **Y** (heterogeneous) - **T**:
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+ * **Y** (heterogeneous) - **T1**:
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  Second operand, power of the exponent.
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  **Outputs**
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  * **Z** (heterogeneous) - **T**:
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  Output 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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+ tensor(float16),
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+ tensor(int32),
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+ tensor(int64)
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  ):
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+ * **T1** in (
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+ tensor(double),
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+ tensor(float),
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+ tensor(float16),
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+ tensor(int16),
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+ tensor(int32),
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+ tensor(int64),
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+ tensor(int8),
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+ tensor(uint16),
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+ tensor(uint32),
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+ tensor(uint64),
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+ tensor(uint8)
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+ ):
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- Constrain input and output types to float tensors.+ Constrain input X and output types to float/int tensors.
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+ Constrain input Y types to float/int tensors.