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)
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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)
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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))