**Short description**: *VariadicSplit* operation splits an input tensor into chunks along some axis. The chunks may have variadic lengths depending on ``split_lengths`` input tensor.
*VariadicSplit* operation splits a given input tensor `data` into chunks along a scalar or tensor with shape ``[1]`` ``axis``. It produces multiple output tensors based on additional input tensor ``split_lengths``.
The i-th output tensor shape is equal to the input tensor `data` shape, except for dimension along `axis` which is ``split_lengths[i]``.
* **1**: ``data``. A tensor of type `T1` and arbitrary shape. **Required.**
* **2**: ``axis``. Axis along ``data`` to split. A scalar or tensor with shape ``[1]`` of type ``T2`` with value from range ``-rank(data) .. rank(data)-1``. Negative values address dimensions from the end. **Required.**
* **3**: ``split_lengths``. A list containing the dimension values of each output tensor shape along the split ``axis``. A 1D tensor of type ``T2``. The number of elements in ``split_lengths`` determines the number of outputs. The sum of elements in ``split_lengths`` must match ``data.shape[axis]``. In addition ``split_lengths`` can contain a single ``-1`` element, which means, all remaining items along specified ``axis`` that are not consumed by other parts. **Required.**
* **Multiple outputs**: Tensors of type ``T1``. The i-th output has the same shape as `data` input tensor except for dimension along ``axis`` which is ``split_lengths[i]`` if ``split_lengths[i] != -1``. Otherwise, the dimension along ``axis`` is processed as described in ``split_lengths`` input description.