Python – tensorflow.IndexedSlices.shape Attribute
TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
shape is used to get the tensorflow.TensorShape representing the shape of the dense tensor.
Syntax: tensorflow.IndexedSlices.shape
Returns: It returns tensorflow.TensorShape representing the shape of the dense tensor.
Example 1:
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 ], tf.constant([ 1 , 2 ])) # Finding Shape shape = res.shape # Printing the result print ( 'Shape: ' , shape) |
Output:
data: tf.Tensor( [[1 2 3] [4 5 6]], shape=(2, 3), dtype=int32) Shape: (1, 2)
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 ], tf.constant([ 1 ])) # Finding Shape shape = res.shape # Printing the result print ( 'Shape: ' , shape) |
Output:
data: tf.Tensor( [[1 2 3] [4 5 6]], shape=(2, 3), dtype=int32) Shape: (1, )
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