Python – tensorflow.IndexedSlices.graph Attribute
Last Updated :
20 Jul, 2020
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
import tensorflow as tf
data = tf.constant([[ 1 , 2 , 3 ], [ 4 , 5 , 6 ]], dtype = tf.float32)
print ( 'data: ' , data)
res = tf.IndexedSlices(data, [ 0 ])
@tf .function
def gfg():
tf.compat.v1.disable_eager_execution()
graph = res.graph
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
import tensorflow as tf
data = tf.constant([ 1 , 2 , 3 ])
print ( 'data: ' , data)
res = tf.IndexedSlices(data, [ 0 ])
graph = res.graph
print ( 'graph: ' , graph)
|
Output:
data: Tensor("Const_6:0", shape=(3, ), dtype=int32)
graph: <tensorflow.python.framework.ops.Graph object at 0x7f2eeda9e630>
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