Tf.math.cumsum
This is true of absolutely every op in TensorFlow.  If the op itself says it takes a Tensor, but you pass a numpy array, it will convert the numpy array to a tensor.

We should _not_ modify the documentation here.
At present as per documentation of `tf.math.cumsum` for the argument `input(x)` the supported type is `Tensor`. But it also accepts python list,tuple and numpy arrays also which have registered Tensor conversion function.Even in the code of `tf.math.cumsum` it converts the` input(x)` to a tensor explicitly.

Also for the argument `axis` the supported type is `Tensor of int32`.But it accepts also `Python integer` with range `[-rank(x), rank(x))`.

Please refer to attached [gist](https://colab.research.google.com/gist/SuryanarayanaY/4a44261fadc8e2a137a99df4e429133c/tf-math-cumsum.ipynb) for the testing on same.
