Comments (1)
Just now, i have a test for whether using the lstm cell. The result shows when using lstm cell, our net will converge faster than not. In GTX950, the time cost is 40 minutes and one hour.So it seems useful to use lstm.
from pytorch-a3c.
Related Issues (20)
- gradient share problem HOT 1
- GAE parameter name should be lambda not tau. And why is default 1.0? HOT 4
- What's the difference between environment 'Pong-v4' and 'PongDeterministic-v4'
- Reward Smoothing
- Multi-processing or multi-threading HOT 1
- The while True loop of function train?
- NotImplementedError HOT 6
- [Question] Does a2c support distributed processing?
- Question in train.py
- with respect to how to choose an action
- How does A3C aggregate the model from different learner? HOT 1
- Why do we reverse rewards? HOT 1
- Dependency list not provided (environment.yml file)
- Stuck in 'p.join()' HOT 1
- After some steps, all the NNs always output same action HOT 1
- Scepticism about the correctness of the use of the LSTMCell
- Can you provide the python, pytorch, numpy and other versions used in the project?
- TypeError: tuple indices must be integers or slices, not tuple
- if there's no "if shared_param.grad is not None: return" what will happen? HOT 1
- where see the result?
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from pytorch-a3c.