TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
expand_dims() is used to insert an addition dimension in input Tensor.
Syntax: tensorflow.expand_dims( input, axis, name)
Parameters:
- input: It is the input Tensor.
- axis: It defines the index at which dimension should be inserted. If input has D dimensions then axis must have value in range [-(D+1), D].
- name(optional): It defines the name for the operation.
Returns: It returns a Tensor with expanded dimension.
Example 1:
Python3
# Importing the library import tensorflow as tf # Initializing the input x = tf.constant([[ 2 , 3 , 6 ], [ 4 , 8 , 15 ]]) # Printing the input print ( 'x:' , x) # Calculating result res = tf.expand_dims(x, 1 ) # Printing the result print ( 'res: ' , res) |
Output:
x: tf.Tensor( [[ 2 3 6] [ 4 8 15]], shape=(2, 3), dtype=int32) res: tf.Tensor( [[[ 2 3 6]] [[ 4 8 15]]], shape=(2, 1, 3), dtype=int32) # shape has changed from (2, 3) to (2, 1, 3)
Example 2:
Python3
# Importing the library import tensorflow as tf # Initializing the input x = tf.constant([[ 2 , 3 , 6 ], [ 4 , 8 , 15 ]]) # Printing the input print ( 'x:' , x) # Calculating result res = tf.expand_dims(x, 0 ) # Printing the result print ( 'res: ' , res) |
Output:
x: tf.Tensor( [[ 2 3 6] [ 4 8 15]], shape=(2, 3), dtype=int32) res: tf.Tensor( [[[ 2 3 6] [ 4 8 15]]], shape=(1, 2, 3), dtype=int32) # shape has changed from (2, 3) to (1, 2, 3)