tf.squeeze()

Removes dimensions of size 1 from the shape of a tensor.

tf.squeeze(
    input, axis=None, name=None
)

Given a tensor input, this operation returns a tensor of the same 
type with all dimensions of size 1 removed. If you don't want to 
remove all size 1 dimensions, you can remove specific size 1 
dimensions by specifying axis.

Example:
# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
tf.shape(tf.squeeze(t))  # [2, 3]
# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
tf.shape(tf.squeeze(t, [2, 4]))  # [1, 2, 3, 1]

Here is what the above code is Doing:
1. We have a tensor of shape [1, 2, 1, 3, 1, 1]
2. We use tf.squeeze to remove all size 1 dimensions
3. We get a tensor of shape [2, 3]
4. We use tf.squeeze to remove the size 1 dimension at index 2
5. We get a tensor of shape [1, 2, 3, 1]