GPU Testing Code TF

Python code to check if our GPU is visible to our computer and use it in our python code using tensorflow.

import tensorflow as tf
from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential
import numpy as np
import time

start_time = time.time()

# Check if TensorFlow can access the GPU
print("Is there a GPU available: "),
print(tf.test.is_gpu_available())

print("GPU(s) available: "),
print(tf.config.list_physical_devices('GPU'))

np.random.seed(0)
X_train = np.random.rand(100, 10)
y_train = np.random.randint(0, 2, (100, 1))

with tf.device('/GPU:0'): # Change this num to switch GPU
    model = Sequential([
        Dense(64, activation='relu', input_shape=(10,)),
        Dense(64, activation='relu'),
        Dense(1, activation='sigmoid')
    ])

    model.compile(optimizer='adam',
                  loss='binary_crossentropy',
                  metrics=['accuracy'])

    model.fit(X_train, y_train, epochs=100)

end_time = time.time()
total_time = end_time - start_time
print(f"Total time taken: {total_time} seconds")