Specified TensorFlow Data Type in Python
Python TensorFlow Basic: Exercise-14 with Solution
Write a Python program that creates a TensorFlow tensor with a specified data type (e.g., float32) and prints its data type
Sample Solution:
Python Code:
import tensorflow as tf
# Declare the data type (e.g., float32)
data_type = tf.float32
# Create a TensorFlow tensor with the specified data type
# Tensors are multi-dimensional arrays with a uniform type (called a dtype ).
ts = tf.constant([1.0, 2.0, 3.0], dtype=data_type)
# Print the data type of the tensor
print("Data Type of the Tensor:", ts.dtype)
Output:
Data Type of the Tensor: <dtype: 'float32'>
Explanation:
In the exercise above -
- Import TensorFlow as tf.
- Define the desired data type, such as tf.float32, and store it in the data_type variable.
- Create a TensorFlow tensor using tf.constant() with the specified data type by providing the dtype argument.
- Finally, we print the data type of the created tensor using tensor.dtype.
Python Code Editor:
Previous: Common TensorFlow data types in Python.
Next: Convert TensorFlow Tensor data type in Python.
What is the difficulty level of this exercise?
It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.
https://w3resource.com/machine-learning/tensorflow/python-tensorflow-basic-exercise-14.php
- Weekly Trends and Language Statistics
- Weekly Trends and Language Statistics