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>
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