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c335050 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | # Dynamic SpatialVID Training
Training recipes for the motion-filtered dynamic SpatialVID pool. They mirror the six dynamic rows used for demos and inference:
| Row | Script | Notes |
| --- | --- | --- |
| Context K=1 | `run_dyn_ctx1.sh` | FOV top-0, 1 context frame |
| Context K=5 | `run_dyn_ctx5.sh` | FOV top-4, per-frame context VAE |
| Context K=20 | `run_dyn_ctx20.sh` | FOV top-19, per-frame context VAE |
| Spatial Memory | `run_dyn_spatial_mem.sh` | 64 spatial memory tokens |
| Block-wise SSM | `run_dyn_block_wise_ssm.sh` | Paper-aligned state-space memory |
| VideoSSM hybrid | `run_dyn_videossm_hybrid.sh` | Legacy temporal-conv baseline |
Set paths through environment variables:
```bash
export WAN_BASE_MODEL=/path/to/Wan2.1-T2V-1.3B
export DATASET_BASE_PATH=data/dynamic-spatialvid-motion60/mixed
export OUTPUT_BASE_ROOT=$PWD/outputs/dynamic_spatialvid
```
The local validation pool used during development is:
```bash
export DATASET_BASE_PATH=/pfs/weiyang/DynMemBench-V2/camcl_spatialvid_motion60_ready/mixed
```
Public scripts should keep the relative form above. The expected dataset root contains:
```text
mixed/
βββ frames/L{1,2,3}/{clip_id}/0000.png ... 0080.png
βββ jsons/L{1,2,3}/{clip_id}.json
βββ overlap_labels/L{1,2,3}/{clip_id}/
βββ metadata_train.csv
βββ metadata_train_sample.csv
βββ metadata_train_sample_L1.csv
βββ metadata_eval.csv
βββ metadata_eval_2chunk.csv
```
For quick local validation, override the metadata and step count:
```bash
METADATA_NAME=metadata_train_sample_L1.csv \
MAX_TRAIN_STEPS=1 \
PROGRESS_TOTAL_STEPS=30000 \
NUM_WORKERS=0 \
bash train/dynamic_spatialvid/run_dyn_block_wise_ssm.sh
```
Dynamic evaluation is TODO; current public support covers training and inference.
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