Can I run Keras model on gpu?

Question

I\'m running a Keras model, with a submission deadline of 36 hours, if I train my model on the cpu it will take approx 50 hours, is there a way to run Keras on gpu?

Answer 1

2.0 Compatible Answer: While above mentioned answer explain in detail on how to use GPU on Keras Model, I want to explain how it can be done for Tensorflow Version 2.0.

To know how many GPUs are available, we can use the below code:

print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))

To find out which devices your operations and tensors are assigned to, put tf.debugging.set_log_device_placement(True) as the first statement of your program.

Enabling device placement logging causes any Tensor allocations or operations to be printed. For example, running the below code:

tf.debugging.set_log_device_placement(True)

# Create some tensors
a = tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
b = tf.constant([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])
c = tf.matmul(a, b)

print(c)

gives the Output shown below:

Executing op MatMul in device /job:localhost/replica:0/task:0/device:GPU:0 tf.Tensor( [[22. 28.] [49. 64.]], shape=(2, 2), dtype=float32)

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