Duplicate from ZihanSu/Self_Gradient_Forcing_Plus_Release2

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README.md

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+---
+license: apache-2.0
+library_name: pytorch
+pipeline_tag: text-to-video
+tags:
+- video-generation
+- diffusion
+- sgf
+- sgf-plus
+---
+
+<h1 style="display:flex;align-items:center;gap:8px;font-size:26px;line-height:1.3;margin:16px 0"><img src="assets/logo.png" width="32" height="32" style="display:block;flex-shrink:0;margin:0" alt="SGF+ logo"> Self Gradient Forcing Plus</h1>
+
+**Decoupling Gradient Flows for Autoregressive Video Generation**
+
+[Project Page](https://zihan-su.github.io/self-gradient-forcing-plus) · [GitHub](https://github.com/Zihan-Su/Self_Gradient_Forcing_Plus)
+
+SGF+ separates context-writing and denoising parameters to resolve conflicting gradient updates, improving autoregressive video generation and enabling rollouts of up to 24 hours from only 5s training windows.
+
+![SGF+ video generation comparisons and a 24-hour rollout](assets/teaser.png)
+
+## Model Checkpoints
+
+| Checkpoint | Description |
+| :--- | :--- |
+| [`chunkwise/model.pt`](chunkwise/model.pt) | SGF+ for chunkwise video generation. |
+| [`framewise/model.pt`](framewise/model.pt) | SGF+ for framewise video generation. |
+| [`diagnostics/sgf.pt`](diagnostics/sgf.pt) | SGF checkpoint used for gradient-conflict reproduction, containing the raw generator and paired critic. |
+
+## Installation
+
+The environment follows the SGF setup.
+
+```bash
+git clone https://github.com/Zihan-Su/Self_Gradient_Forcing_Plus.git
+cd Self_Gradient_Forcing_Plus
+
+conda create -n sgf_plus python=3.10 -y
+conda activate sgf_plus
+pip install -r requirements.txt
+pip install flash-attn --no-build-isolation
+python setup.py develop
+```
+
+Run the following commands from the repository root.
+
+## Download Weights
+
+```bash
+bash scripts/download_weights.sh
+```
+
+The script uses the Hugging Face CLI command `hf` by default. Set `HF_CLI=huggingface-cli` if your environment still uses the older command name.
+
+It downloads:
+
+- Wan base models to `wan_models/Wan2.1-T2V-1.3B` and `wan_models/Wan2.1-T2V-14B`.
+- [Causal-Forcing](https://github.com/thu-ml/Causal-Forcing) AR initialization checkpoints to `checkpoints/init/chunkwise/ar_diffusion.pt` and `checkpoints/init/framewise/ar_diffusion.pt`.
+- Released SGF+ inference checkpoints to `hf_weights/chunkwise/model.pt` and `hf_weights/framewise/model.pt`.
+- The training prompt list to `prompts/vidprom_filtered_extended.txt`.
+
+Run `hf auth login` first if authentication is required.
+
+## Inference
+
+The default prompt file is `prompts/test_prompt.txt` with 8 prompts. The launcher uses 8 GPUs when at least 8 GPUs are visible; otherwise it falls back to single-GPU serial inference. By default it generates `963` latent frames, which decode to about 240 seconds of video at 16 fps.
+
+The inference script takes the release setting name (`chunkwise` or `framewise`) and a checkpoint path, and selects the matching config automatically:
+
+- chunkwise config: `configs/sgf_plus_chunkwise.yaml`
+- framewise config: `configs/sgf_plus_framewise.yaml`
+
+The long-video KV-cache geometry is set in `scripts/infer_self_gradient_forcing.sh`, which is called by the SGF+ launcher. Chunkwise defaults to `KV_CACHE_SINK=3`, `KV_CACHE_FIFO_FRAMES=6`, and `KV_CACHE_CURRENT_FRAMES=3`, so `--kv_cache_max_frames` is `12`. Framewise defaults to `KV_CACHE_SINK=4`, `KV_CACHE_FIFO_FRAMES=16`, and `KV_CACHE_CURRENT_FRAMES=1`, so `--kv_cache_max_frames` is `21`.
+
+### Chunkwise
+
+```bash
+bash scripts/infer_sgf_plus.sh chunkwise hf_weights/chunkwise/model.pt
+```
+
+This uses:
+
+```text
+configs/sgf_plus_chunkwise.yaml
+hf_weights/chunkwise/model.pt
+```
+
+### Framewise
+
+```bash
+bash scripts/infer_sgf_plus.sh framewise hf_weights/framewise/model.pt
+```
+
+This uses:
+
+```text
+configs/sgf_plus_framewise.yaml
+hf_weights/framewise/model.pt
+```
+
+### Custom checkpoint or prompt file
+
+```bash
+bash scripts/infer_sgf_plus.sh \
+  chunkwise \
+  hf_weights/chunkwise/model.pt \
+  prompts/test_prompt.txt
+```
+
+Useful overrides:
+
+```bash
+NUM_OUTPUT_FRAMES=963 SEED=42 OUTPUT_ROOT=outputs/demo \
+  bash scripts/infer_sgf_plus.sh chunkwise hf_weights/chunkwise/model.pt
+```
+
+For trained checkpoints, pass the release setting first and the produced `logs/.../checkpoint_model_*/model.pt` path as the second argument. The script uses EMA weights by default; set `USE_EMA=0` to use the non-EMA `generator` weights.
+
+## Training
+
+### Chunkwise SGF+
+
+```bash
+bash scripts/train_sgf_plus_chunkwise.sh
+```
+
+Equivalent explicit form:
+
+```bash
+bash scripts/train_sgf_plus_chunkwise.sh \
+  configs/sgf_plus_chunkwise.yaml \
+  logs/sgf_plus_chunkwise
+```
+
+### Framewise SGF+
+
+```bash
+bash scripts/train_sgf_plus_framewise.sh
+```
+
+Equivalent explicit form:
+
+```bash
+bash scripts/train_sgf_plus_framewise.sh \
+  configs/sgf_plus_framewise.yaml \
+  logs/sgf_plus_framewise
+```
+
+The launchers accept `[config.yaml] [logdir] [extra train.py args...]` and support single-node and multi-node training. Without explicit or scheduler-provided topology settings, nodes auto-register through `.rendezvous/` on the shared filesystem and launch static `torchrun` with an IP master address. For multi-node jobs, run the same command on every node within the gather window.
+
+Useful overrides:
+
+```bash
+GATHER_WINDOW=90 NUM_GPUS=8 MASTER_PORT=29501 ENABLE_WANDB=1 \
+  bash scripts/train_sgf_plus_chunkwise.sh logs/sgf_plus_chunkwise
+```
+
+To specify the topology manually, set `NNODES`, `NODE_RANK`, `MASTER_ADDR` and `MASTER_PORT`. Use a distinct `NODE_RANK` on each node and matching values for the other settings.
+
+## Gradient Conflict Experiments
+
+To reproduce our gradient-conflict experiments, see the [experiment guide](https://github.com/Zihan-Su/Self_Gradient_Forcing_Plus/blob/main/gradient_conflict/README.md).
+
+## Citation
+
+```bibtex
+@misc{su2026sgfplus,
+  title  = {{SGF+}: Decoupling Gradient Flows for Autoregressive Video Generation},
+  author = {Su, Zihan and Zhuang, Junhao and Li, Yaowei and Lu, Siwen and Li, Haoran and
+            Li, Lingen and Wu, Haoyu and Jin, Weiyang and Zhang, Songchun and
+            Huang, Haoyang and Yuan, Chun and Xue, Zeyue and Duan, Nan},
+  year   = {2026}
+}
+```
+
+## License
+
+This project is released under the [Apache-2.0 license](https://huggingface.co/ZihanSu/Self_Gradient_Forcing_Plus/blob/main/LICENSE).

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