mx.io.NDArrayIter cant pad when size is large

[samskalicky]

Description

When input data is smaller than batch size, sometime it errors out with:

Traceback (most recent call last):
  File "test.py", line 7, in <module>
    for batch in dataiter:
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/io/io.py", line 230, in __next__
    return self.next()
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/io/io.py", line 682, in next
    data = self.getdata()
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/io/io.py", line 764, in getdata
    return self._batchify(self.data)
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/io/io.py", line 751, in _batchify
    second_data = self._getdata(data_source, end=pad)
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/io/io.py", line 707, in _getdata
    ]]) for x in data_source
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/io/io.py", line 707, in <listcomp>
    ]]) for x in data_source
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/ndarray/ndarray.py", line 705, in __getitem__
    return self._slice(key.start, key.stop)
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/ndarray/ndarray.py", line 1338, in _slice
    start, stop, _ = _get_index_range(start, stop, self.shape[0])
  File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/ndarray/ndarray.py", line 3080, in _get_index_range
    raise IndexError('Slicing stop %d exceeds limit of %d' % (stop, length))
IndexError: Slicing stop 190 exceeds limit of 10

To Reproduce

import numpy as np
import mxnet as mx

data = np.arange(40).reshape((10,2,2))
dataiter = mx.io.NDArrayIter(data=data, batch_size=200, last_batch_handle='pad')
for batch in dataiter:
     print(batch.data[0].asnumpy().shape)

Using a batch size of 20 succeeds, but larger sizes fail.

Steps to reproduce

This is using the 1.6.0 branch