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55 行
2.5 KiB
55 行
2.5 KiB
from typing import Dict
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class BrainInfo:
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def __init__(self, visual_observation, vector_observation, text_observations, memory=None,
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reward=None, agents=None, local_done=None,
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vector_action=None, text_action=None, max_reached=None):
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"""
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Describes experience at current step of all agents linked to a brain.
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"""
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self.visual_observations = visual_observation
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self.vector_observations = vector_observation
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self.text_observations = text_observations
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self.memories = memory
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self.rewards = reward
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self.local_done = local_done
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self.max_reached = max_reached
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self.agents = agents
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self.previous_vector_actions = vector_action
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self.previous_text_actions = text_action
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AllBrainInfo = Dict[str, BrainInfo]
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class BrainParameters:
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def __init__(self, brain_name, brain_param):
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"""
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Contains all brain-specific parameters.
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:param brain_name: Name of brain.
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:param brain_param: Dictionary of brain parameters.
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"""
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self.brain_name = brain_name
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self.vector_observation_space_size = brain_param["vectorObservationSize"]
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self.num_stacked_vector_observations = brain_param["numStackedVectorObservations"]
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self.number_visual_observations = len(brain_param["cameraResolutions"])
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self.camera_resolutions = brain_param["cameraResolutions"]
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self.vector_action_space_size = brain_param["vectorActionSize"]
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self.vector_action_descriptions = brain_param["vectorActionDescriptions"]
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self.vector_action_space_type = ["discrete", "continuous"][brain_param["vectorActionSpaceType"]]
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def __str__(self):
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return '''Unity brain name: {}
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Number of Visual Observations (per agent): {}
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Vector Observation space size (per agent): {}
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Number of stacked Vector Observation: {}
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Vector Action space type: {}
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Vector Action space size (per agent): {}
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Vector Action descriptions: {}'''.format(self.brain_name,
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str(self.number_visual_observations),
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str(self.vector_observation_space_size),
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str(self.num_stacked_vector_observations),
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self.vector_action_space_type,
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str(self.vector_action_space_size),
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', '.join(self.vector_action_descriptions))
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