Python – tensorflow.IndexedSlices.graph Attribute

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

graph is used to find the  Graph that contains the values, indices, and shape tensors. 

Syntax: tensorflow.IndexedSlices.graph

Return: It returns a Graph instance.

Example 1:

Python3

# Importing the library
import tensorflow as tf

# Initializing the input
data = tf.constant([[1, 2, 3], [4, 5, 6]], dtype = tf.float32)

# Printing the input
print('data: ', data)

# Calculating result
res = tf.IndexedSlices(data, [0])

# Finding Graph
@tf.function
def gfg():
  tf.compat.v1.disable_eager_execution()

  graph = res.graph

  # Printing the result
  print('graph: ', graph)


gfg()

Output:

data:  Tensor("Const_1:0", shape=(2, 3), dtype=float32)
graph:  <tensorflow.python.framework.ops.Graph object at 0x7f2eeda9e630>

<tf.Operation 'PartitionedCall_1' type=PartitionedCall>

Example 2: 

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])

# Finding Graph
graph = res.graph

# Printing the result
print('graph: ', graph)

Output:

data:  Tensor("Const_6:0", shape=(3, ), dtype=int32)
graph:  <tensorflow.python.framework.ops.Graph object at 0x7f2eeda9e630>