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Error running a loaded agent in multienviroment

1

@jerabaul29 @b-fg I am running a simulation with several enviroments ``` environment_base = CylinderEnvironment(simu_name = '2DCyl', do_baseline=True, continue_training=False, ENV_ID = -1, host = '') network = [dict(type='dense', size=512), dict(type='dense', size=512)]...

franalcantara

Bumps [mistune](https://github.com/lepture/mistune) from 0.8.4 to 2.0.3. Release notes Sourced from mistune's releases. Version 2.0.2 Fix escape_url via lepture/mistune#295 Version 2.0.1 Fix XSS for image link syntax. Version 2.0.0 First release...

dependabot[bot]

Parameters are not working

2

when runninng: from tensorforce.core.parameters import Linear Linear(unit='episodes', num_steps=100000, initial_value=1.0, final_value=0.05) I get: --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Input In [2], in () ----> 1 Linear(unit='episodes', num_steps=100000, initial_value=1.0, final_value=0.05)...

wernerolaf

parallel processing fails when preprocessing is Sequence or Deltafier and batch_agent_calls=True

1

When I have a code like this: class PongRamEnvironment(Environment): def __init__(self): self.base_env=Environment.create( environment='gym', level='Pong-ram-v4',max_episode_timesteps=10000) super().__init__() def states(self): return {'type': 'float', 'shape': (4,), 'min_value': 0.0, 'max_value': 255.0} def actions(self): return {'type':...

wernerolaf

🐛: TensorforceError has no attribute 'dtype'. So fixed typo TensorforceError.dtype -> TensorforceError.type (Bagfix)

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Hi developers! As commented in the issue #879, TensorforceError has no attribute 'dtype', but it has ['type' method](https://github.com/tensorforce/tensorforce/blob/master/tensorforce/exception.py#L128). So fixed bellow typo by this PR https://github.com/tensorforce/tensorforce/blob/868d12d7db655c816dc1439dd7826eef06d6ef0e/tensorforce/core/parameters/decaying.py#L136-L145 https://github.com/tensorforce/tensorforce/blob/868d12d7db655c816dc1439dd7826eef06d6ef0e/tensorforce/core/parameters/constant.py#L35-L44 I really appreciate...

HinataKikuchi

Hi, When I define the agent configuration through a JSON file (e.g., ppo.json) and I define a "saver" entity inside the JSON to have the intermediate models saved, it throws...

salehisaeed

Beta distribution with parameters <1

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Hi, I am using a custom Gym environment and training the agent with PPO and DDPG. The action space is continuous and bounded. One good solution with PPO parametrizing a...

lguas

After the first iteration, `str_result` should have length `cls.MAX_BYTES`, however, since `n = 0`, the checks will return an error even if the `recv` operation was successful. With this fix,...

lguas

accept kwargs and pass to Environment.create #875

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rolandrmgservices

Thanks for such a useful codebase. I had a question re customizing environment creation via the runner class. Say we have an environment like the `ThermostatEnvironment` defined in: https://github.com/tensorforce/tensorforce/blob/master/examples/temperature-controller.ipynb but...

rolandrmgservices