--- 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