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Python – tensorflow.IndexedSlices()

  • Last Updated : 20 Jul, 2020

TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks. 

IndexedSlices() is used to find the sparse representation of a set of tensor slices at given indices.

Syntax: tensorflow.IndexedSlices(values, indices, dense_shape = None)

Parameters:

  • values: It is a Tensor of any dtype.
  • indices: It is a 1-D Tensor.

Returns: It returns a IndexedSlices object.



Example 1:

Python3




# Importing the library
import tensorflow as tf
  
# Initializing the input
data = tf.constant([1, 2, 3])
  
# Printing the input
print('data: ', data)
  
# Calculating result
res = tf.IndexedSlices(data, [0])
  
# Printing the result
print('res: ', res)

Output:


data:  tf.Tensor([1 2 3], shape=(3, ), dtype=int32)
res:  IndexedSlices(indices=[0], values=tf.Tensor([1 2 3], shape=(3, ), dtype=int32))

Example 2:

Python3




# Importing the library
import tensorflow as tf
  
# Initializing the input
data = tf.constant([[1, 2, 3], [4, 5, 6]])
  
# Printing the input
print('data: ', data)
  
# Calculating result
res = tf.IndexedSlices(data, [0])
  
# Printing the result
print('res: ', res)

Output:


data:  tf.Tensor(
[[1 2 3]
 [4 5 6]], shape=(2, 3), dtype=int32)
res:  IndexedSlices(indices=[0], values=tf.Tensor(
[[1 2 3]
 [4 5 6]], shape=(2, 3), dtype=int32))

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