Description
I wanted to try out dreamerv2 on our own environment (or at least the examples) but unfortunately run into some issues along the way.
The README example & Dockerfile use TensorFlow (and other library) versions that are outdated, in some cases pip doesn't even distribute the older versions anymore.
I attempted to run the minigrid example with a recent TensorFlow version.
The import from tensorflow.keras.mixed_precision import experimental as prec in nets.py causes an error as that API is no longer listed under experimental.
MiniGrid has migrated elsewhere and now uses Gymnasium: https://github.com/Farama-Foundation/Minigrid
Using the new minigrid env throws an error:
...
File ".../dreamerv2/api.py", line 77, in train
env = common.ResizeImage(env)
File ".../dreamerv2/common/envs.py", line 447, in __init__
self._keys = [
File ".../dreamerv2/common/envs.py", line 449, in <listcomp>
if len(v.shape) > 1 and v.shape[:2] != size]
TypeError: object of type 'NoneType' has no len()
Attempting to call train.py with our own environment (with an observation of an intensity image of size 42x30, contained in a NumPy array) manages to collect a prefill dataset but then fails with the error
File ".../dreamerv2/api.py", line 101, in train
train_agent(next(dataset))
File ".../dreamerv2/common/other.py", line 201, in __call__
self._state, out = self._fn(*args, self._state)
File ".../tensorflow/python/util/traceback_utils.py", line 153, in error_handler
raise e.with_traceback(filtered_tb) from None
File ".../dreamerv2/agent.py", line 60, in train
state, outputs, mets = self.wm.train(data, state)
File ".../dreamerv2/agent.py", line 100, in train
model_loss, state, outputs, metrics = self.loss(data, state)
File ".../dreamerv2/agent.py", line 108, in loss
post, prior = self.rssm.observe(
File ".../dreamerv2/common/nets.py", line 50, in observe
post, prior = common.static_scan(
File ".../dreamerv2/common/other.py", line 41, in static_scan
last = fn(last, inp)
File ".../dreamerv2/common/nets.py", line 51, in <lambda>
lambda prev, inputs: self.obs_step(prev[0], *inputs),
File ".../dreamerv2/common/nets.py", line 96, in obs_step
prior = self.img_step(prev_state, prev_action, sample)
File ".../dreamerv2/common/nets.py", line 124, in img_step
dist = self.get_dist(stats)
File ".../dreamerv2/common/nets.py", line 81, in get_dist
dist = tfd.Independent(common.OneHotDist(logit), 1)
File ".../decorator.py", line 232, in fun
return caller(func, *(extras + args), **kw)
File ".../tensorflow_probability/python/distributions/distribution.py", line 342, in wrapped_init
default_init(self_, *args, **kwargs)
File ".../tensorflow_probability/python/distributions/independent.py", line 162, in __init__
super(_Independent, self).__init__(
File ".../tensorflow_probability/python/distributions/distribution.py", line 603, in __init__
d for d in self._parameter_control_dependencies(is_init=True)
File ".../tensorflow_probability/python/distributions/independent.py", line 337, in _parameter_control_dependencies
raise ValueError('reinterpreted_batch_ndims({}) cannot exceed '
ValueError: reinterpreted_batch_ndims(1) cannot exceed distribution.batch_ndims(0)
I was unable to figure out what exactly the problem is here, and whether it is caused by the updated dependency versions, a problem with our environment or something else entirely.
Could you update the dependencies and examples to make it possible again to try out dreamerv2?