python-tensorflowHow can I use Python and TensorFlow to implement multithreading?

Python and TensorFlow can be used together to implement multithreading by using threading.Thread. This will allow multiple threads to run at the same time, with each thread executing its own TensorFlow operations.

Example code

import threading
import tensorflow as tf

def thread_function(name):
  with tf.Session() as sess:
    # do TensorFlow operations
    ...

threads = []
for i in range(3):
  t = threading.Thread(target=thread_function, args=(i,))
  threads.append(t)
  t.start()

for t in threads:
  t.join()

Code explanation

1. Importing threading and TensorFlow - import threading and import tensorflow as tf
2. Defining a thread function - def thread_function(name)
3. Creating and starting the threads - t = threading.Thread(target=thread_function, args=(i,)) and t.start()
4. Joining the threads - t.join()

Helpful links

• Python threading
• TensorFlow threading

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