# 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()

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>

# 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)

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