Keras: real amount of GPU memory used

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I'm using Keras with Tensorflow backend and looking at nvidia-smi is not sufficient to understand how much memory current network architecture need because seems like Tensorflow just allocate all availible memory.

So the question is how to find out real GPU memory usage?

keras tensorflow linux python
2 Answers

You can still use nvidia-smi after telling TensorFlow not to reserve all memory of the GPU, but to grow this reservation on demand:

config = tf.ConfigProto()
config.gpu_options.allow_growth = True
keras.backend.tensorflow_backend.set_session(tf.Session(config=config))
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