Split - 13 vs 18

Next section compares an older to a newer version of the same operator after both definition are converted into markdown text.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. Split13 → Split18 +9 -3
Split13 → Split18 RENAMED
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- Split a tensor into a list of tensors, along the specified
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+ Split a tensor into a list of tensors, along the specified 'axis'.
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- 'axis'. Lengths of the parts can be specified using input 'split'.
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+ Either input 'split' or the attribute 'num_outputs' should be specified, but not both.
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- Otherwise, the tensor is split to equal sized parts.
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+ If the attribute 'num_outputs' is specified, then the tensor is split into equal sized parts.
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+ If the tensor is not evenly splittable into num_outputs, the last chunk will be smaller.
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+ If the input 'split' is specified, it indicates the sizes of each output in the split.
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  ### Attributes
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  * **axis - INT** (default is '0'):
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  Which axis to split on. A negative value means counting dimensions from the back. Accepted range is [-rank, rank-1] where r = rank(input).
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+
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+ * **num_outputs - INT** :
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+
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+ Number of outputs to split parts of the tensor into. If the tensor is not evenly splittable the last chunk will be smaller.
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  ### Inputs
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  Between 1 and 2 inputs.
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  - **input** (heterogeneous) - **T**:
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  The tensor to split
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  - **split** (optional, heterogeneous) - **tensor(int64)**:
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  Optional length of each output. Values should be >= 0.Sum of the values must be equal to the dim value at 'axis' specified.
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  ### Outputs
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  Between 1 and 2147483647 outputs.
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  - **outputs** (variadic, heterogeneous) - **T**:
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  One or more outputs forming list of tensors after splitting
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  ### Type Constraints
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  * **T** in ( tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):
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  Constrain input and output types to all tensor types.