TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
reduce_any() is used to compute the "logical or" of elements across dimensions of a tensor.
Syntax: tensorflow.math.reduce_any( input_tensor, axis, keepdims, name)
Parameters:
- input_tensor: It is boolean tensor to reduce.
- axis(optional): It represent the dimensions to reduce. It's value should be in range [-rank(input_tensor), rank(input_tensor)). If no value is given for this all dimensions are reduced.
- keepdims(optional): It's default value is False. If it's set to True it will retain the reduced dimension with length 1.
- name(optional): It defines the name for the operation.
Returns: It returns a tensor.
Example 1:
# importing the library
import tensorflow as tf
# Initializing the input tensor
a = tf.constant([True, False, False, True], dtype = tf.bool)
# Printing the input tensor
print('Input: ', a)
# Calculating result
res = tf.math.reduce_any(a)
# Printing the result
print('Result: ', res)
Output:
Input: tf.Tensor([ True False False True], shape=(4, ), dtype=bool) Result: tf.Tensor(True, shape=(), dtype=bool)
Example 2:
# importing the library
import tensorflow as tf
# Initializing the input tensor
a = tf.constant([[True, False], [False, True]], dtype = tf.bool)
# Printing the input tensor
print('Input: ', a)
# Calculating result
res = tf.math.reduce_any(a, axis = 1, keepdims = True)
# Printing the result
print('Result: ', res)
Output:
Input: tf.Tensor( [[ True False] [False True]], shape=(2, 2), dtype=bool) Result: tf.Tensor( [[ True] [ True]], shape=(2, 1), dtype=bool)
