Added exploration code

Author: AlexandreBrown

README.md

@@ -1,2 +1,19 @@
 # RoboHiveTorchRL-Prototype
-Small prototype to see if RoboHive can easily be used with TorchRL
+Small prototype to show RoboHive usage with TorchRL.
+
+# Setup
+1. ```shell
+    micromamba create -n robohive -f environment.yaml -y
+   ```
+2. ```shell
+    micromamba activate robohive
+    ```
+3. ```shell
+    robohive_init
+   ```  
+
+# Explore Random Environments
+1. ```shell
+    python explore_robohive_envs.py
+    ```
+2. Look under the newly created `videos/` for videos of the explored envs. The script explores a few envs by default. 

environment.yaml

@@ -0,0 +1,15 @@
+name: robohive
+channels:
+  - conda-forge
+dependencies:
+  - python=3.9
+  - pip
+  - pip:
+    - torchrl==0.5.0
+    - torch==2.4.1
+    - torchvision==0.19.1
+    - torchaudio==2.4.1
+    - robohive==0.7.0
+    - gymnasium==0.29.1
+    - numpy==1.26.4
+    - av==13.0.0 # Required for torchrl video recorder

explore_robohive_envs.py

@@ -0,0 +1,62 @@
+import torch
+from torchrl.collectors.collectors import SyncDataCollector
+from torchrl.envs.utils import RandomPolicy
+from torchrl.record.loggers.csv import CSVLogger
+from torchrl.record import VideoRecorder
+from torchrl.envs import RoboHiveEnv
+from torchrl.envs.transforms import TransformedEnv
+
+ENV_NAMES_TO_EXPLORE = [
+    "DKittyStandRandom-v0",
+    "FetchReachRandom-v0",
+    "FK1_LdoorOpenRandom-v4",
+    "FrankaPushRandom-v0",
+    "MyoHandCupDrink-v0",
+    "relocate-v1",
+    "rpFrankaRobotiqData-v0"
+]
+
+
+def main():
+    print(f"Envs : {RoboHiveEnv.available_envs}")
+    envs = []
+    for env_name in ENV_NAMES_TO_EXPLORE:
+        print(f"Exploring {env_name}...")
+
+        video_logger = CSVLogger(exp_name=env_name, log_dir="videos", video_format="mp4", video_fps=30)
+        recorder = VideoRecorder(logger=video_logger, tag="iteration", skip=2)
+
+        env = TransformedEnv(
+            RoboHiveEnv(env_name=env_name,
+                        from_pixels=True,
+                        pixels_only=True,
+                        from_depths=False,
+                        frame_skip=None)
+        )
+        env.append_transform(recorder)
+        envs.append(env)
+
+        policy = RandomPolicy(action_spec=env.action_spec)
+
+        device = torch.device('cpu')
+
+        collector = SyncDataCollector(
+            create_env_fn=env,
+            policy=policy,
+            total_frames=200,
+            max_frames_per_traj=50,
+            frames_per_batch=200,
+            device=device,
+            storing_device=device,
+        )
+
+        for _ in collector:
+            continue
+
+        env.transform.dump()
+    
+    for env in envs:
+        env.close()
+
+if __name__ == "__main__":
+    main()