d3rlpy.dataset.Episode¶
-
class
d3rlpy.dataset.
Episode
(observation_shape, action_size, observations, actions, rewards)[source]¶ Episode class.
This class is designed to hold data collected in a single episode.
Episode object automatically splits data into list of
d3rlpy.dataset.Transition
objects. Also Episode object behaves like a list object for ease of access to transitions.# return the number of transitions len(episode) # access to the first transition transitions = episode[0] # iterate through all transitions for transition in episode: pass
Parameters: - observation_shape (tuple) – observation shape.
- action_size (int) – dimension of action-space.
- observations (numpy.ndarray or list(numpy.ndarray)) – observations.
- actions (numpy.ndarray) – actions.
- rewards (numpy.ndarray) – scalar rewards.
- terminals (numpy.ndarray) – binary terminal flags.
Methods
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compute_return
()[source]¶ Computes sum of rewards.
\[R = \sum_{i=1} r_i\]Returns: episode return. Return type: float
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get_action_size
()[source]¶ Returns dimension of action-space.
Returns: dimension of action-space. Return type: int
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get_observation_shape
()[source]¶ Returns observation shape.
Returns: observation shape. Return type: tuple
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size
()[source]¶ Returns the number of transitions.
Returns: the number of transitions. Return type: int
Attributes
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actions
¶ Returns the actions.
Returns: array of actions. Return type: numpy.ndarray
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observations
¶ Returns the observations.
Returns: array of observations. Return type: (numpy.ndarray or list(numpy.ndarray))
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rewards
¶ Returns the rewards.
Returns: array of rewards. Return type: numpy.ndarray
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transitions
¶ Returns the transitions.
Returns: list of d3rlpy.dataset.Transition
objects.Return type: list(d3rlpy.dataset.Transition)