tf.gradients returns None for gradient with self for integer variable?

I was playing around with tf.gradients and got gradients as None for the below code:
>>> x = tf.Variable(10) # integer type >>> tf.gradients(x,x) [None] >>>,x)) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/", line 929, in run run_metadata_ptr) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/", line 1137, in _run self._graph, fetches, feed_dict_tensor, feed_handles=feed_handles) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/", line 471, in __init__ self._fetch_mapper = _FetchMapper.for_fetch(fetches) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/", line 261, in for_fetch return _ListFetchMapper(fetch) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/", line 370, in __init__ self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches] File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/", line 258, in for_fetch type(fetch))) TypeError: Fetch argument None has invalid type <type 'NoneType'>
>>> x = tf.Variable(10.0) # float type >>> tf.gradients(x,x) [<tf.Tensor 'gradients_6/Fill:0' shape=() dtype=float32>] >>>,x)) [1.0]

The environment is Python 2.7 with tensorflow 1.12
I'm not able to understand why this happens. shouldn't it be the same for both the cases of float and int?

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