reinforcement-learning
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Bidirectional RNN
Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?
ConvTranspose Layer
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Naming inconsistency
Describe the bug
I found that some names agruments in framework aren't consistent.
So for example:
class SupervisedRunner(Runner):
"""Runner for experiments with supervised model."""
_experiment_fn: Callable = SupervisedExperiment
def __init__(
self,
model: Model = None,
device: Device = None,
input_key: Any = "features",
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这里好像有个bug,我是在非源程序的目录下运行代码造成的:
Exception in thread Thread-4:
Traceback (most recent call last):
File "/home/exp/anaconda3/envs/××/lib/python3.6/threading.py", line 916, in _bootstrap_inner
self.run()
File "/home/exp/anaconda3/envs/××/lib/python3.6/threading.py", line 864, in run
self._target(*self._args, **self._kwargs)
File "train.py", line 176, in get_remote_gradient
rem
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Describe your feature request
When I run
ray upor callcreate_or_update_cluster(...), the terminal is filled up with output from eitherrsync(from file_mounts, etc) or any commands i put insetup_commands. These can get pretty spammy.It would be nice to be able to suppress these unless v