How to tell if tensorflow is using gpu acceleration from inside python shell?
No, I don't think "open CUDA library" is enough to tell, because different nodes of the graph may be on different devices.
When using tensorflow2:
print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU')))
For tensorflow1, to find out which device is used, you can enable log device placement like this:
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
Check your console for this type of output.
Apart from using sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
which is outlined in other answers as well as in the official TensorFlow documentation, you can try to assign a computation to the gpu and see whether you have an error.
import tensorflow as tf
with tf.device('/gpu:0'):
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)
with tf.Session() as sess:
print (sess.run(c))
Here
- "/cpu:0": The CPU of your machine.
- "/gpu:0": The GPU of your machine, if you have one.
If you have a gpu and can use it, you will see the result. Otherwise you will see an error with a long stacktrace. In the end you will have something like this:
Cannot assign a device to node 'MatMul': Could not satisfy explicit device specification '/device:GPU:0' because no devices matching that specification are registered in this process
Recently a few helpful functions appeared in TF:
- tf.test.is_gpu_available tells if the gpu is available
- tf.test.gpu_device_name returns the name of the gpu device
You can also check for available devices in the session:
with tf.Session() as sess:
devices = sess.list_devices()
devices
will return you something like
[_DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:CPU:0, CPU, -1, 4670268618893924978),
_DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:XLA_CPU:0, XLA_CPU, 17179869184, 6127825144471676437),
_DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:XLA_GPU:0, XLA_GPU, 17179869184, 16148453971365832732),
_DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:0, TPU, 17179869184, 10003582050679337480),
_DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:1, TPU, 17179869184, 5678397037036584928)