Add multi3d_games dataset card

README.md

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+---
+license: other
+---
+
+# multi3d_games Latent Dataset
+
+Partial Multi3D games latent dataset uploaded to
+`mignonjia/multi3d_games`.
+
+This dataset uses the expanded parquet layout rather than tar archive shards.
+It contains latent/video-conditioning rows for four gameplay videos from
+Horizon Forbidden West, Dark Souls Remastered, and Code Vein.
+
+## Layout
+
+```text
+README.md
+map_style_cache/file_info.pkl
+action_latent/node1/manifest.jsonl
+action_latent/node1/manifest.rankNNN.jsonl
+action_latent/node1/dist_merged.ok
+action_latent/node1/dist_done/rankNNN.done
+action_latent/node1/combined_parquet_dataset/rankNNN/worker_0/*.parquet
+```
+
+The uploaded repo contains one node (`node1`) split across 8 ranks:
+`rank000` through `rank007`.
+
+## Size and Counts
+
+- Total uploaded data size: about 224.7 GB
+- Uploaded files: 1,715 data files plus `README.md` and `.gitattributes`
+- Parquet files: 1,696
+- Parquet rows / samples: 13,551
+- Manifest rows:
+  - `manifest.jsonl`: 13,551 rows
+  - rank manifests: 13,551 rows total
+- Rank parquet layout:
+  - `rank000`: 212 parquet files, 1,694 rows, 26.17 GiB
+  - `rank001`: 212 parquet files, 1,694 rows, 26.13 GiB
+  - `rank002`: 212 parquet files, 1,694 rows, 26.14 GiB
+  - `rank003`: 212 parquet files, 1,694 rows, 26.16 GiB
+  - `rank004`: 212 parquet files, 1,694 rows, 26.15 GiB
+  - `rank005`: 212 parquet files, 1,694 rows, 26.17 GiB
+  - `rank006`: 212 parquet files, 1,694 rows, 26.16 GiB
+  - `rank007`: 212 parquet files, 1,693 rows, 26.16 GiB
+
+## Source Videos
+
+The rows come from four source videos:
+
+| idx | video_id | game | rows | shard |
+| --- | --- | --- | ---: | --- |
+| 2246 | `KchWtQyuyvU` | Horizon Forbidden West | 3,396 | `SHARD_0006` |
+| 8224 | `d_lTaTapecI` | Dark Souls Remastered | 3,969 | `SHARD_0026` |
+| 12601 | `m2Nt3DVfYqk` | Code Vein | 1,847 | `SHARD_0040` |
+| 18529 | `soS-p5-Oh7A` | Dark Souls Remastered | 4,339 | `SHARD_0059` |
+
+## Parquet Schema
+
+Each parquet row stores byte arrays plus explicit shape and dtype metadata.
+The main fields are:
+
+- `id`: sample id, matching manifest ids
+- `vae_latent_bytes`, `vae_latent_shape`, `vae_latent_dtype`
+- `clip_feature_bytes`, `clip_feature_shape`, `clip_feature_dtype`
+- `first_frame_latent_bytes`, `first_frame_latent_shape`,
+  `first_frame_latent_dtype`
+- `mouse_cond_bytes`, `mouse_cond_shape`, `mouse_cond_dtype`
+- `keyboard_cond_bytes`, `keyboard_cond_shape`, `keyboard_cond_dtype`
+- `pil_image_bytes`, `pil_image_shape`, `pil_image_dtype`
+- `file_name`, `caption`, `media_type`, `width`, `height`, `num_frames`,
+  `duration_sec`, `fps`
+
+Example row metadata:
+
+- `vae_latent_shape`: `[16, 21, 60, 104]`, dtype `float32`
+- `first_frame_latent_shape`: `[16, 21, 60, 104]`, dtype `float32`
+- `clip_feature_shape`: `[257, 1280]`, dtype `float32`
+- `mouse_cond_shape`: `[81, 2]`, dtype `float32`
+- `keyboard_cond_shape`: `[81, 6]`, dtype `float32`
+- `media_type`: `video`
+- `width`: 480
+- `height`: 832
+- `num_frames`: 21
+- `duration_sec`: 2.7
+- `fps`: 30.0
+
+## Processing Notes
+
+- Source local root before upload:
+  `/mnt/weka/home/hao.zhang/alex/wm-lab/datas/datasets/multi3d-partial`
+- The dataset was uploaded directly with `hf upload-large-folder`, preserving
+  the expanded parquet paths.
+- The original local upload command used 8 workers and committed all
+  1,715 files successfully.
+- Multi3D mouse up/down convention was corrected before upload by flipping
+  `mouse_cond[:, 0]`.
+- The mouse flip was validated over all 1,696 parquet files and 13,551 rows.
+  The final scan showed the expected swapped axis-0 sign counts relative to the
+  pre-flip baseline.
+
+## Download
+
+Download the full dataset:
+
+```bash
+hf download mignonjia/multi3d_games --repo-type dataset --local-dir multi3d_games
+```
+
+Download one rank only:
+
+```bash
+hf download mignonjia/multi3d_games \
+  --repo-type dataset \
+  --include 'action_latent/node1/combined_parquet_dataset/rank000/**' \
+  --local-dir multi3d_games_rank000
+```
+
+## Reading Arrays
+
+The array fields are stored as raw bytes. Reconstruct them using the matching
+`*_shape` and `*_dtype` columns:
+
+```python
+import numpy as np
+import pandas as pd
+
+df = pd.read_parquet("action_latent/node1/combined_parquet_dataset/rank000/worker_0/data_chunk_0.parquet")
+row = df.iloc[0]
+
+vae = np.frombuffer(row["vae_latent_bytes"], dtype=np.dtype(row["vae_latent_dtype"]))
+vae = vae.reshape(tuple(row["vae_latent_shape"]))
+
+mouse = np.frombuffer(row["mouse_cond_bytes"], dtype=np.dtype(row["mouse_cond_dtype"]))
+mouse = mouse.reshape(tuple(row["mouse_cond_shape"]))
+
+keyboard = np.frombuffer(row["keyboard_cond_bytes"], dtype=np.dtype(row["keyboard_cond_dtype"]))
+keyboard = keyboard.reshape(tuple(row["keyboard_cond_shape"]))
+```
+
+## Verification
+
+- Hugging Face repo after upload contained 1,716 files:
+  `.gitattributes` plus 1,715 uploaded dataset files.
+- Upload log final state:
+  - hashed: 1,715 / 1,715
+  - pre-uploaded: 1,697 / 1,697
+  - committed: 1,715 / 1,715
+  - committed bytes: 224.7 GB / 224.7 GB