Comments (1)
Given a fast CPU with all cores used, simple models tend to be faster on the CPU. I suspect the overhead of setting up the GPU becomes significant.
from deep-q-learning.
Related Issues (20)
- What am I doing wrong? HOT 2
- a hidden bug in your code HOT 3
- missing the initialization of target action value and refreshing the Qhat HOT 1
- memory for state HOT 4
- Saving/reloading weight does not seem to work HOT 2
- model save and load does not work HOT 8
- should update the weight every time step ? HOT 3
- Speeding the replay HOT 2
- k frame
- What is the purpose of "done"? HOT 2
- ddqn_batch
- Would it make sense to restrict the action to what's possible? HOT 2
- Predict the action for new environment - Inference HOT 1
- IndexError
- Why are we training the neural network for only 1 epoch HOT 1
- Question: Is this some form of reward engineering? HOT 1
- Possible incrrection in DQN & DDQN file
- ValueError: cannot reshape array of size 2 into shape (1,4) HOT 2
- Not learning
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from deep-q-learning.