python-tensorflowHow can I use a GPU with Python TensorFlow?

Using a GPU with Python TensorFlow is relatively straightforward. First, you'll need to install the GPU version of TensorFlow. You can do this using pip install tensorflow-gpu. Once installed, you can use the GPU with TensorFlow by adding the following code block to the start of your code:

import tensorflow as tf

# Tell TensorFlow that you want to use the GPU
with tf.device('/gpu:0'):
    # Define your operations and TensorFlow will automatically use the GPU
    a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
    b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
    c = tf.matmul(a, b)

# Creates a session with log_device_placement set to True.
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

# Runs the op.
print(sess.run(c))

The output of this code should be:

[[22. 28.]
 [49. 64.]]

The code consists of the following parts:

1. import tensorflow as tf - imports the TensorFlow library.
2. with tf.device('/gpu:0') - tells TensorFlow to use the GPU.
3. a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a') - creates a constant TensorFlow operation with the given values.
4. b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b') - creates a second constant TensorFlow operation with the given values.
5. c = tf.matmul(a, b) - creates a TensorFlow operation that multiplies a and b.
6. sess = tf.Session(config=tf.ConfigProto(log_device_placement=True)) - creates a session with log_device_placement set to True.
7. print(sess.run(c)) - runs the operation and prints the result.

For more information, see the TensorFlow documentation.

Edit this code on GitHub