63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
from collections import deque
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from typing import Optional
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from tensordict import TensorDict
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from torchrl.envs import EnvBase
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class AbstractEnv(EnvBase):
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def __init__(
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self,
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task,
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frame_skip: int = 1,
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from_pixels: bool = False,
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pixels_only: bool = False,
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image_size=None,
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seed=1337,
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device="cpu",
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num_prev_obs=1,
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num_prev_action=0,
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):
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super().__init__(device=device, batch_size=[])
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self.task = task
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self.frame_skip = frame_skip
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self.from_pixels = from_pixels
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self.pixels_only = pixels_only
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self.image_size = image_size
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self.num_prev_obs = num_prev_obs
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self.num_prev_action = num_prev_action
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if pixels_only:
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assert from_pixels
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if from_pixels:
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assert image_size
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self._make_env()
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self._make_spec()
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self._current_seed = self.set_seed(seed)
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if self.num_prev_obs > 0:
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self._prev_obs_image_queue = deque(maxlen=self.num_prev_obs)
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self._prev_obs_state_queue = deque(maxlen=self.num_prev_obs)
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if self.num_prev_action > 0:
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raise NotImplementedError()
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# self._prev_action_queue = deque(maxlen=self.num_prev_action)
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def render(self, mode="rgb_array", width=640, height=480):
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raise NotImplementedError("Abstract method")
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def _reset(self, tensordict: Optional[TensorDict] = None):
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raise NotImplementedError("Abstract method")
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def _step(self, tensordict: TensorDict):
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raise NotImplementedError("Abstract method")
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def _make_env(self):
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raise NotImplementedError("Abstract method")
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def _make_spec(self):
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raise NotImplementedError("Abstract method")
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def _set_seed(self, seed: Optional[int]):
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raise NotImplementedError("Abstract method")
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