Python – tensorflow.dynamic_stitch()
Last Updated :
10 Jul, 2020
TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
dynamic_stitch() is used to merge multiple tensors into single tensor.
Syntax: tensorflow.dynamic_stitch( indices, data, name)
Parameter:
- indices: It is a list of Tensors having minimum 1 tensor and each tensor with dtype int32.
- data : It is list of Tensors having same length as indices.
- name(optional): It defines the name for the operation.
Result:
It returns a Tensor of same dtype as data.
Example 1:
Python3
import tensorflow as tf
indices = [[ 0 , 1 , 5 ], [ 2 , 4 , 3 , 6 ]]
data = [[ 1 , 2 , 3 ], [ 4 , 5 , 6 , 7 ]]
print ( 'indices:' , indices)
print ( 'data: ' , data)
x = tf.dynamic_stitch(indices, data)
print ( 'x: ' , x)
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Output:
indices: [[0, 1, 5], [2, 4, 3, 6]]
data: [[1, 2, 3], [4, 5, 6, 7]]
x: tf.Tensor([1 2 4 6 5 3 7], shape=(7, ), dtype=int32)
Example 2:
Python3
import tensorflow as tf
indices = [[ 0 , 1 , 6 ], [ 5 , 4 , 3 ]]
data = [[ 1 , 2 , 3 ], [ 4 , 5 , 6 ]]
print ( 'indices:' , indices)
print ( 'data: ' , data)
x = tf.dynamic_stitch(indices, data)
print ( 'x: ' , x)
|
Output:
indices: [[0, 1, 2], [5, 4, 3]]
data: [[1, 2, 3], [4, 5, 6]]
x: tf.Tensor([1 2 3 6 5 4], shape=(6, ), dtype=int32)
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