Name every checkpoint 'ckpt' instead of its training step

Adds the renamed paths; the step-named paths are removed in the follow-up commit.

.gitattributes

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README.md

@@ -28,13 +28,18 @@ simulation environments live in the benchmark environment repository.
 <condition>/<method>/
 ├── train_config.json      # the run's own config (see "Paths" below)
 ├── <sidecar>              # norm_stats.json | action_codec.json | demonstration_config.txt
-└── <step>/                # the evaluated checkpoint
+└── ckpt/ | ckpt.pt | ckpt.pth    # the evaluated checkpoint
 ```
 
+Every method's weights are called **`ckpt`** whichever trainer wrote them — a
+directory for the JAX/orbax and LeRobot policies, a single file for Vid2Robot
+(`ckpt.pt`) and UniSkill (`ckpt.pth`). The training step each one corresponds
+to is in the table below, not in the path.
+
 `<condition>` is the training suite, and it is the **top** level: **`nd/`** = no
 distraction (clean scenes), **`wd/`** = with distraction (distractors in both
 train and eval). So the keyframe policy trained with distractors is
-`wd/vid_cond_pi05_keyframes/20000/`.
+`wd/vid_cond_pi05_keyframes/ckpt/`.
 
 The paper's third suite, **ED** (clean training, distracted evaluation), needs
 no extra weights — it evaluates everything under `nd/` against the WD scene
@@ -42,21 +47,23 @@ bank.
 
 ## Checkpoints
 
-| Paper label | Method dir | ND step (`nd/`) | WD step (`wd/`) | Size each |
-|---|---|---|---|---|
-| VLM + π0.5 | `vlm_pi05` | `050000` | `050000` | 9.35 GB |
-| Vid. Cond. π0.5 (Uniform) | `vid_cond_pi05_uniform` | `49999` | `49999` | 6.20 GB |
-| Vid. Cond. π0.5 (Keyframes) | `vid_cond_pi05_keyframes` | `49999` | **`20000`** | 6.20 GB |
-| Vid2Robot | `vid2robot` | `vid2robot_step50000.pt` | `vid2robot_step50000.pt` | 2.37 GB |
-| UniSkill | `uniskill_policy` | `models/model_epoch_1000.pth` | `models/model_epoch_1000.pth` | 0.74 GB |
-
-Two things about the step numbers that are easy to misread:
-
-- **openpi/orbax saves at `num_train_steps - 1`**, so a 50k-step run ends at
-  `49999`, unpadded. The LeRobot trainer saves at `num_train_steps` and
-  zero-pads, so the same run length ends at `050000`.
-- **WD keyframes is step `20000`, not `49999`.** That run reached 20k steps;
-  it is the checkpoint the reported WD keyframe numbers come from.
+| Paper label | Method dir | Weights | Step — `nd/` | Step — `wd/` | Size each |
+|---|---|---|---|---|---|
+| VLM + π0.5 | `vlm_pi05` | `ckpt/` | 50,000 | 50,000 | 9.35 GB |
+| Vid. Cond. π0.5 (Uniform) | `vid_cond_pi05_uniform` | `ckpt/` | 50,000 | 50,000 | 6.20 GB |
+| Vid. Cond. π0.5 (Keyframes) | `vid_cond_pi05_keyframes` | `ckpt/` | 50,000 | **20,000** | 6.20 GB |
+| Vid2Robot | `vid2robot` | `ckpt.pt` | 50,000 | 50,000 | 2.37 GB |
+| UniSkill | `uniskill_policy` | `ckpt.pth` | epoch 1,000 | epoch 1,000 | 0.74 GB |
+
+**The WD keyframes policy is from step 20,000, not 50,000.** That run reached
+20k steps, and it is the checkpoint the reported WD keyframe numbers come from.
+It is the one place where the two conditions are not trained equally long.
+
+The step directories these were renamed from, for cross-referencing against the
+training logs: `050000` (the LeRobot trainer saves at `num_train_steps`,
+zero-padded), `49999` and `20000` (openpi/orbax saves at
+`num_train_steps - 1`, unpadded) and `model_epoch_1000.pth` (Robomimic is
+epoch-based, 100 iterations per epoch).
 
 UniSkill is a Robomimic diffusion policy over skill representations produced by
 an **off-the-shelf, un-finetuned UniSkill inverse-skill-dynamics model**. That

nd/uniskill_policy/ckpt.pth

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nd/vid2robot/ckpt.pt

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nd/vid_cond_pi05_keyframes/ckpt/_CHECKPOINT_METADATA

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nd/vid_cond_pi05_keyframes/ckpt/params/array_metadatas/process_0

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