Closed lrthorita closed 5 years ago
Hi @lrthorita, I am not sure why isn't the graph visible on Tensorboard on your setup. It is working fine over here, please see below.
Anyway, I don't think it is easy to understand the network layout from Tensorboard. This is why we have implemented a feature to textually summarize the graph layout, accessible through the --print_networks_summary
flag. For instance, this is what you'll be getting for CartPole_DQN:
Input Embedder: observation Input size = [4] Dense (num outputs = 256) Activation (type = <function relu at 0x7f5958bcb378>) Middleware: Dense (num outputs = 512) Activation (type = <function relu at 0x7f5958bcb378>) Output Head: q_values_head Dense (num outputs = 2)
Hi @galleibo-intel! Thank you for answering.
I'll try the textual summary feature as soon as I can. About the TensorFlow, is there any restriction about its version? I'm using 1.10.
Hi @lrthorita,
You're welcome. Yeah, 1.10 should be ok AFAIK.
I have run the CartPole_DQN preset to see how it works. After training, I tried to see the dashboard and the tensorboard. The problem is that I can't see the Neural Network graph on tensorboard. Since the code saves the ''graphdef.pb", shouldn't it be there?
Basically, what I did was running the preset by using:
coach -p CartPole_DQN -s 1800
(I set-s 1800
to save checkpoints of the model for each 30 minutes.Then, I used
tensorboard --logdir /path/to/checkpoints/dir/
to try to see the neural network graph.