Div - 13 vs 14

Next section compares an older to a newer version of the same operator after both definition are converted into markdown text.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

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1. Div13 → Div14 +4 -2

Div13 → Div14 RENAMED Viewed

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1 1	Performs element-wise binary division (with Numpy-style broadcasting support).
2 2	This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [Broadcasting in ONNX](https://github.com/onnx/onnx/blob/main/docs/Broadcasting.md).
3	+
4	+ (Opset 14 change): Extend supported types to include uint8, int8, uint16, and int16.
3 5	### Inputs
4 6	- **A** (heterogeneous) - **T**:
5 7	First operand.
6 8	- **B** (heterogeneous) - **T**:
7 9	Second operand.
8 10	### Outputs
9 11	- **C** (heterogeneous) - **T**:
10 12	Result, has same element type as two inputs
11 13	### Type Constraints
12	- * **T** in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64) ):
14	+ * **T** in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):
13	- Constrain input and output types to high-precision numeric tensors.? ^^^^^^^^^^^^^^
15	+ Constrain input and output types to all numeric tensors.? ^^^