TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
concat() is used to concatenate tensors along one dimension.
Syntax: tensorflow.concat( values, axis, name )
Parameter:
- values: It is a tensor or list of tensor.
- axis: It is 0-D tensor which represents dimension to concatenate.
- name(optional): It defines the name for the operation.
Returns: It returns the concatenated Tensor.
Example 1:
Python3
# Importing the library import tensorflow as tf # Initializing the input tensor t1 = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]] t2 = [[[7, 4], [8, 4]], [[2, 10], [15, 11]]] # Printing the input tensor print('t1: ', t1) print('t2: ', t2) # Calculating result res = tf.concat([t1, t2], 2) # Printing the result print('Result: ', res) |
Output:
t1: [[[1, 2], [3, 4]], [[5, 6], [7, 8]]] t2: [[[7, 4], [8, 4]], [[2, 10], [15, 11]]] Result: tf.Tensor( [[[ 1 2 7 4] [ 3 4 8 4]] [[ 5 6 2 10] [ 7 8 15 11]]], shape=(2, 2, 4), dtype=int32)
Example 2:
Python3
# Importing the library import tensorflow as tf # Initializing the input tensor t1 = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]] t2 = [[[7, 4], [8, 4]], [[2, 10], [15, 11]]] # Printing the input tensor print('t1: ', t1) print('t2: ', t2) # Calculating result res = tf.concat([t1, t2], 1) # Printing the result print('Result: ', res) |
Output:
t1: [[[1, 2], [3, 4]], [[5, 6], [7, 8]]] t2: [[[7, 4], [8, 4]], [[2, 10], [15, 11]]] Result: tf.Tensor( [[[ 1 2] [ 3 4] [ 7 4] [ 8 4]] [[ 5 6] [ 7 8] [ 2 10] [15 11]]], shape=(2, 4, 2), dtype=int32)
