Commit 853f1422 authored by Benjamin Beyret's avatar Benjamin Beyret
Browse files

evaluation resolution documentation

parent 2daecad8
......@@ -16,6 +16,7 @@ experiments we will run, therefore we provide the agent with the length of the e
are the ones returned by the Gym environment `AnimalAIEnv` from `animalai.envs.environment`. If you wish to directly
work on the ML Agents `BrainInfo` you can access them via `info['brain_info']`
**NEW (v1.0.4)**: you can now select the resolution of the observation your agent takes as input, this argument will be passed to the environment directly (must be between 4 and 256).
Make sure any data loaded in the docker is referred to using **absolute paths** in the container or the form `/aaio/data/...` (see below). An example that you can modify is provided [here](
## Create an EvalAI account and add submission details
......@@ -28,11 +28,11 @@ def main():
resolution = submitted_agent.resolution
assert isinstance(resolution, int)
assert 4 <= resolution <= 256
except AttributeError:
resolution = 84
except AssertionError:
print('Resolution must be an integer')
print('Resolution must be between 4 and 256')
env = AnimalAIEnv(
......@@ -55,7 +55,7 @@ def main():
obs, reward, done, info = env.step([0, 0])
for i in range(arena_config_in.arenas[0].t):
action = submitted_agent.step(obs, reward, done, info)
obs, reward, done, info = env.step(action)
cumulated_reward += reward
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