Python - tensorflow.math.truediv()

The tensorflow.math.truediv() function is used to compute the true division of two tensors element-wise. It is a part of the TensorFlow math module and is commonly used in machine learning and deep learning applications.

Syntax

tensorflow.math.truediv(x, y, name=None)

Parameters

• x: A tensor of numeric type.
• y: A tensor of numeric type.
• name (optional): A name to give to the operation.

Returns

A tensor with the same shape as the input tensors, containing the element-wise true division of x by y.

Example

import tensorflow as tf

# Create input tensors
x = tf.constant([4, 8, 12], dtype=tf.float32)
y = tf.constant([2, 4, 6], dtype=tf.float32)
 
# Compute true division
result = tf.math.truediv(x, y)

# Print the result
print(result)

Output:

<tf.Tensor: shape=(3,), dtype=float32, numpy=array([2., 2., 2.], dtype=float32)>

In this example, we create two input tensors x and y with values [4, 8, 12] and [2, 4, 6] respectively. We then compute the true division of x by y using the tf.math.truediv() function, which results in [2.0, 2.0, 2.0].