Python – tensorflow.IndexedSlicesSpec()
TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
IndexedSlicesSpec inherits from TypeSpec and provides Type specification for IndexedSlices.
Syntax: tensorflow.IndexedSlicesSpec( shape, dtype, indices_dtype, dense_shape_dtype, indices_shape )
Parameters:
- shape(optional): It defines the dense shape of IndexedSlices. Default value is None which allows any dense shape.
- dtype(optional): It defines the dtype of IndexedSlices values. Default value is float32.
- indices_dtype(optional): It defines the dtype of indices in the IndexedSlices. It can either be int32 or int64 with default value int64.
- dense_shape_dtype(optional): It defines the dtype of dense shape in the IndexedSlices. It can either be int32, int64 or None with default value None.
- indices_shape(optional): It defines the shape of the indices component, which indicates how many slices are in the IndexedSlices.
Example 1: This example uses all the default values.
Python3
import tensorflow as tf
res = tf.IndexedSlicesSpec()
print ( 'IndexedSlicesSpec: ' , res)
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Output:
IndexedSlicesSpec: IndexedSlicesSpec(TensorShape(None), tf.float32, tf.int64, None, TensorShape([None]))
Example 2:
Python3
import tensorflow as tf
res = tf.IndexedSlicesSpec(( 2 , 3 ))
print ( 'IndexedSlicesSpec: ' , res)
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Output:
IndexedSlicesSpec: IndexedSlicesSpec(TensorShape([2, 3]), tf.float32, tf.int64, None, TensorShape([None]))
Last Updated :
14 Mar, 2023
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