no robomimic

sim/simulator.py

@@ -4,10 +4,7 @@ import numpy as np
 import einops
 import skimage
 import time
-import robomimic.utils.file_utils as FileUtils
 
-from sim.robomimic.robomimic_wrapper import RobomimicLowdimWrapper
-from sim.robomimic.robomimic_runner import create_env, OBS_KEYS, RESOLUTION
 from genie.st_mask_git import STMaskGIT
 from genie.st_mar import STMAR
 from datasets.utils import get_image_encoder
@@ -103,65 +100,7 @@ class ReplaySimulator(PhysicsSimulator):
         return self._dt
     
 
-class RobomimicSimulator(PhysicsSimulator):
-    """
-    Example usage:
-    sim = RobomimicSimulator("lift")
-    useless_low_dim_state = sim.reset()
-    image = sim.step([0] * 7)
-    Image.fromarray(image).save("test.png")
-    """
-    def __init__(self, env_name):
-        super().__init__()
-        env_meta = FileUtils.get_env_metadata_from_dataset(
-            f'data/robomimic_datasets/robomimic_raw/datasets/{env_name}/ph/image.hdf5')
-        env_meta['use_image_obs'] = True
-        env = create_env(env_meta, obs_keys=OBS_KEYS)
-        self.env = RobomimicLowdimWrapper(env=env, obs_keys=OBS_KEYS)
-        self.env_name = env_name
-
-    def set_initial_state(self, state):
-        self.env.init_state = state
-
-    def step(self, action):
-        obs, reward, done, info = self.env.step(action)
-        img = self.env.render()
-        img = cv2.resize(img, RESOLUTION)
-        return {
-            'pred_next_frame': img,
-            'reward': reward,
-            'done': done,
-            'info': info
-        }
-
-    def reset(self):
-        self.env.reset()    # reset to initial state
-        img = self.env.render()
-        img = cv2.resize(img, RESOLUTION)
-        return img
-
-    def close(self):
-        self.env.close()
-
-    @property
-    def dt(self):
-        return self.env.env.env.sim.model.opt.timestep
-    
-    @property
-    def action_dimension(self):
-        return self.env.env.action_dimension
-
-    def set_dt(self, dt):
-        self.env.env.env.sim.model.opt.timestep = dt
-
-    def get_raw_state(self, port: Optional[str] = None):
-        raw_state = self.env.env.get_state()
-        raw_obs = self.env.env.get_observation()
-        raw_state.update(raw_obs)
-        if port is not None:
-            return raw_state[port]
-        return raw_state
-
+ 
 
 class GenieSimulator(LearnedSimulator):