Comments changed
diff --git a/tensorflow/python/data/ops/dataset_ops.py b/tensorflow/python/data/ops/dataset_ops.py
index b166247..581341a 100644
--- a/tensorflow/python/data/ops/dataset_ops.py
+++ b/tensorflow/python/data/ops/dataset_ops.py
@@ -534,8 +534,8 @@
>>> list(dataset.as_numpy_iterator())
[(array([1, 2, 3], dtype=int32), b'A')]
- >>> # `from_tensors` creates 3D tensor in below example
- >>> # unlike `from_tensor_slices` which merges the input tensor.
+ >>> # `from_tensors` adds one more dimension to the shape
+ >>> # use `from_tensor_slices` to merge the input tensor.
>>> dataset = tf.data.Dataset.from_tensors([tf.random_uniform([2, 3]),
tf.random_uniform([2, 3])])
>>> list(dataset.as_numpy_iterator())[0].shape
@@ -618,8 +618,8 @@
[3, 2]], dtype=int32), array([[b'A'],
[b'B']], dtype=object))
- >>> # `from_tensor_slices` merges the input tensor
- >>> # unlike `from_tensors` which will create 3D tensor in below example.
+ >>> # `from_tensor_slices` merges the input tensor, unlike `from_tensors`
+ >>> # which increases dimensionality.
>>> dataset = tf.data.Dataset.from_tensor_slices([tf.random.uniform([2, 3]),
tf.random.uniform([2, 3])])
>>> list(dataset.as_numpy_iterator())[0].shape
