Truncate data/state to first 2 dims across all tasks; uniform observation schema

README.md

@@ -127,13 +127,15 @@ Each task is shipped as a single **`data.zarr.zip`** following the [Diffusion Po
 ```
 data.zarr.zip
 ├── data/
-│   ├── action   (N, action_dim)   float32
-│   ├── img      (N, 96, 96, 3)    uint8
-│   └── state    (N, state_dim)    float32
+│   ├── action   (N, 2)             float32
+│   ├── img      (N, 96, 96, 3)     uint8
+│   └── state    (N, 2)             float32
 └── meta/
-    └── episode_ends   (E,)         int64    # exclusive end indices
+    └── episode_ends   (E,)          int64    # exclusive end indices
 ```
 
+All five tasks share the same observation schema: 96×96 RGB image, 2-D agent state, 2-D action. This uniformity is intentional — the same policy architecture can be trained and evaluated across every task with no per-task adapter.
+
 The `data/*` arrays are **flat over all episodes** within a task; episode boundaries live in `meta/episode_ends`. To iterate episode `i`:
 
 ```python

pusht-asymmetrical/data.zarr.zip

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