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+Requires-Dist: gdown==5.2.0 +Requires-Dist: h5py==3.12.1 +Requires-Dist: idna==3.6 +Requires-Dist: imageio==2.36.0 +Requires-Dist: matplotlib==3.9.2 +Requires-Dist: numpy==1.26.3 +Requires-Dist: omegaconf==2.3.0 +Requires-Dist: pandas==2.2.3 +Requires-Dist: pillow==10.2.0 +Requires-Dist: pydub==0.25.1 +Requires-Dist: pytorch-lightning==2.4.0 +Requires-Dist: pytorchvideo==0.1.5 +Requires-Dist: PyYAML==6.0.1 +Requires-Dist: regex==2024.9.11 +Requires-Dist: requests==2.31.0 +Requires-Dist: scikit-learn==1.5.2 +Requires-Dist: scipy==1.13.0 +Requires-Dist: six==1.16.0 +Requires-Dist: test-tube==0.7.5 +Requires-Dist: timm==1.0.11 +Requires-Dist: torchdiffeq==0.2.4 +Requires-Dist: torchmetrics==1.5.1 +Requires-Dist: tqdm==4.66.5 +Requires-Dist: urllib3==2.2.0 +Requires-Dist: uvicorn==0.32.0 +Requires-Dist: scikit-video==1.1.11 +Requires-Dist: imageio-ffmpeg==0.5.1 +Requires-Dist: sentencepiece==0.2.0 +Requires-Dist: beautifulsoup4==4.12.3 +Requires-Dist: ftfy==6.3.0 +Requires-Dist: moviepy==1.0.3 +Requires-Dist: wandb==0.18.5 +Requires-Dist: pydantic==2.9.2 +Requires-Dist: huggingface_hub==0.26.1 +Requires-Dist: protobuf==5.28.3 +Requires-Dist: watch +Requires-Dist: gpustat +Requires-Dist: peft==0.13.2 +Requires-Dist: liger_kernel==0.4.1 +Requires-Dist: einops==0.8.0 +Requires-Dist: wheel==0.44.0 +Requires-Dist: loguru +Requires-Dist: diffusers==0.32.0 +Requires-Dist: bitsandbytes +Dynamic: license-file + +# Granular-GRPO + +
Click for the full abstract + +> The integration of online reinforcement learning (RL) into diffusion and flow models has recently emerged as a promising approach for aligning generative models with human preferences. Stochastic sampling via Stochastic Differential Equations (SDE) is employed during the denoising process to generate diverse denoising directions for RL exploration. While existing methods effectively explore potential high-value samples, they suffer from sub-optimal preference alignment due to sparse and narrow reward signals. To address these challenges, we propose a novel **G**ranular-**GRPO** (G²RPO) framework that achieves precise and comprehensive reward assessments of sampling directions in reinforcement learning of flow models. Specifically, a *Singular Stochastic Sampling* strategy is introduced to support step-wise stochastic exploration while enforcing a high correlation between the reward and the injected noise, thereby facilitating a faithful reward for each SDE perturbation. Concurrently, to eliminate the bias inherent in fixed-granularity denoising, we introduce a *Multi-Granularity Advantage Integration* module that aggregates advantages computed at multiple diffusion scales, producing a more comprehensive and robust evaluation of the sampling directions. Experiments conducted on various reward models, including both in-domain and out-of-domain evaluations, demonstrate that our G²RPO significantly outperforms existing flow-based GRPO baselines, highlighting its effectiveness and robustness. +
+ +**[G²RPO: Granular GRPO for Precise Reward in Flow Models]()** +
+[Yujie Zhou*](https://github.com/YujieOuO/), +[Pengyang Ling*](https://github.com/LPengYang/), +[Jiazi Bu*](https://bujiazi.github.io/), +[Yibin Wang](https://codegoat24.github.io/), +[Yuhang Zang](https://yuhangzang.github.io/), +[Jiaqi Wang†](https://myownskyw7.github.io/), +[Li Niu†](https://www.ustcnewly.com/), +[Guangtao Zhai](https://faculty.sjtu.edu.cn/zhaiguangtao/en/index.htm/) + +(*Equal Contribution)(†Corresponding Author) + +[![arXiv](https://img.shields.io/badge/arXiv-2510.01982-b31b1b.svg)](https://arxiv.org/abs/2510.01982) +[![Project Page](https://img.shields.io/badge/Project-Website-green)](https://bujiazi.github.io/g2rpo.github.io/) +[![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Demo-red)](https://github.com/bcmi/Granular-GRPO) + +## 📜 News + +**[2025/10/3]** Code is available now! + +**[2025/10/2]** The paper and project page have been released! + +## 🏗️ Todo +- [ ] Release a gradio demo. + +## 📚 Gallery +We show more results in the [Project Page](https://bujiazi.github.io/g2rpo.github.io/). + +## 🚀 Method Overview + +
+ +
+Granular-GRPO: an online RL framework for precise and comprehensive reward assessments. + +## 🔧 Installations + +### Setup repository and conda environment + +```bash +git clone https://github.com/bcmi/Granular-GRPO.git +cd Granular-GRPO + +conda create -n g2rpo python=3.10 +conda activate g2rpo + +bash env_setup.sh + +git clone https://github.com/tgxs002/HPSv2.git +cd HPSv2 +pip install -e . +cd .. +``` + +The environment dependency is the same as [DanceGRPO](https://github.com/XueZeyue/DanceGRPO). + +## 🔑 Model Preparations + +### 1. FLUX +```bash +# Download the FLUX.1-dev model. +mkdir ./ckpt/flux +huggingface-cli login +huggingface-cli download --resume-download black-forest-labs/FLUX.1-dev --local-dir ./ckpt/flux +``` + +### 2. Reward Models + +#### HPS-v2.1 +```bash +# Download the HPS reward model. +python scripts/huggingface/download_hf.py --repo_id xswu/HPSv2 --local_dir ./ckpt/hps + +# Download the CLIP-ViT-H-14-laion2B-s32B-b79K. +python scripts/huggingface/download_hf.py --repo_id laion/CLIP-ViT-H-14-laion2B-s32B-b79K --local_dir ./ckpt/CLIP-ViT-H-14-laion2B-s32B-b79K +``` + +#### CLIP_Score +```bash +# Download the CLIP_Score reward model. +python scripts/huggingface/download_hf.py --repo_id apple/DFN5B-CLIP-ViT-H-14 --local_dir ./ckpt/clip_score +``` + +## 🎈 Quick Start + +### Preprocess Data +```bash +# Obtain the embeddings of the prompt dataset. +bash scripts/preprocess/preprocess_flux_rl_embeddings.sh +``` + +### Training +```bash +# Training with 16 GPUs for hps reward. +bash scripts/finetune/finetune_g2rpo_hps.sh + +# Training with 16 GPUs for hps and clip_score reward. +bash scripts/finetune/finetune_g2rpo_hps_clip.sh +``` + +### Inference +We provide our G2RPO ckpt at [Huggingface](https://huggingface.co/yujieouo/G2RPO) +```bash +# Download the G2RPO ckpt +mkdir ./ckpt/g2rpo +huggingface-cli login +huggingface-cli download --resume-download yujieouo/G2RPO diffusion_pytorch_model.safetensors --local-dir ./ckpt/g2rpo + +# inference +python scripts/inference/infer.py +``` + +## 📎 Citation +If you find our work helpful for your research, please consider giving a star ⭐ and citation 📝 +```bibtex +@article{zhou2025g2rpo, + title={G$^2$RPO: Granular GRPO for Precise Reward in Flow Models}, + author={Zhou, Yujie and Ling, Pengyang and Bu, Jiazi and Wang, Yibin and Zang, Yuhang and Wang, Jiaqi and Niu, Li and Zhai, Guangtao}, + journal={arXiv preprint arXiv:2510.01982}, + year={2025} +} +``` + +## 💞 Acknowledgement +The code is built upon the below repositories, we thank all the contributors for open-sourcing. + +* [DanceGRPO](https://github.com/XueZeyue/DanceGRPO) +* [Flow-GRPO](https://github.com/yifan123/flow_grpo) +* [MixGRPO](https://github.com/Tencent-Hunyuan/MixGRPO) +* [FastVideo](https://github.com/hao-ai-lab/FastVideo) +* [DDPO](https://github.com/kvablack/ddpo-pytorch) diff --git a/fastvideo.egg-info/SOURCES.txt b/fastvideo.egg-info/SOURCES.txt new file mode 100644 index 0000000000000000000000000000000000000000..b2402d5d77893ac7d27a40d36a03e53369d303d2 --- /dev/null +++ b/fastvideo.egg-info/SOURCES.txt @@ -0,0 +1,124 @@ +LICENSE +README.md +pyproject.toml +fastvideo/train_g2rpo_hps.py +fastvideo/train_g2rpo_hps_clip_merge copy.py +fastvideo/train_g2rpo_hps_clip_merge.py +fastvideo/train_g2rpo_hps_merge.py +fastvideo/train_g2rpo_multi_reward_merge.py +fastvideo/train_g2rpo_qwenimage_merge.py +fastvideo/train_g2rpo_rfpt.py +fastvideo/train_g2rpo_rlpt_dino.py +fastvideo/train_g2rpo_rlpt_from_noise.py +fastvideo/train_g2rpo_sd_merge.py +fastvideo/train_grpo_qwenimage.py +fastvideo/train_grpo_rlpt.py +fastvideo/train_grpo_rlpt_from_noise.py +fastvideo/train_grpo_sd.py 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+fastvideo/models/hunyuan/modules/embed_layers.py +fastvideo/models/hunyuan/modules/mlp_layers.py +fastvideo/models/hunyuan/modules/models.py +fastvideo/models/hunyuan/modules/modulate_layers.py +fastvideo/models/hunyuan/modules/norm_layers.py +fastvideo/models/hunyuan/modules/posemb_layers.py +fastvideo/models/hunyuan/modules/token_refiner.py +fastvideo/models/hunyuan/text_encoder/__init__.py +fastvideo/models/hunyuan/utils/__init__.py +fastvideo/models/hunyuan/utils/data_utils.py +fastvideo/models/hunyuan/utils/file_utils.py +fastvideo/models/hunyuan/utils/helpers.py +fastvideo/models/hunyuan/utils/preprocess_text_encoder_tokenizer_utils.py +fastvideo/models/hunyuan/vae/__init__.py +fastvideo/models/hunyuan/vae/autoencoder_kl_causal_3d.py +fastvideo/models/hunyuan/vae/unet_causal_3d_blocks.py +fastvideo/models/hunyuan/vae/vae.py +fastvideo/models/hunyuan_hf/modeling_hunyuan.py +fastvideo/models/hunyuan_hf/pipeline_hunyuan.py +fastvideo/models/mochi_hf/convert_diffusers_to_mochi.py +fastvideo/models/mochi_hf/mochi_latents_utils.py +fastvideo/models/mochi_hf/modeling_mochi.py +fastvideo/models/mochi_hf/norm.py +fastvideo/models/mochi_hf/pipeline_mochi.py +fastvideo/models/stable_diffusion/ddim_with_logprob.py +fastvideo/models/stable_diffusion/ddim_with_logprob_v6.py +fastvideo/models/stable_diffusion/ddim_with_logprob_v6_2.py +fastvideo/models/stable_diffusion/ddim_with_logprob_v6_8.py +fastvideo/models/stable_diffusion/ddim_with_logprob_v8.py +fastvideo/models/stable_diffusion/ddim_with_logprob_w_x0.py +fastvideo/models/stable_diffusion/ddim_with_logprob_w_x0_2.py +fastvideo/models/stable_diffusion/ddim_with_logprob_w_x0_v7.py +fastvideo/models/stable_diffusion/ddim_with_logprob_wo_eta.py +fastvideo/models/stable_diffusion/pipeline_with_logprob.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_p1.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_p2.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_prefix.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_w_eta.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_w_eta_bid.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_w_eta_mask.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_w_eta_mask2.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_w_eta_v7.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_w_eta_v8.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_wo_eta.py +fastvideo/models/stable_diffusion/pipeline_with_logprob_wo_eta_2.py +fastvideo/reward_model/clip_score.py +fastvideo/reward_model/hps_score.py +fastvideo/reward_model/image_reward.py +fastvideo/reward_model/pick_score.py +fastvideo/reward_model/unified_reward.py +fastvideo/reward_model/utils.py +fastvideo/utils/checkpoint.py +fastvideo/utils/communications.py +fastvideo/utils/communications_flux.py +fastvideo/utils/communications_flux_rfpt.py +fastvideo/utils/dataset_utils.py +fastvideo/utils/env_utils.py +fastvideo/utils/fsdp_util.py +fastvideo/utils/fsdp_util_qwenimage.py +fastvideo/utils/load.py +fastvideo/utils/logging_.py +fastvideo/utils/optimizer.py +fastvideo/utils/parallel_states.py +fastvideo/utils/validation.py \ No newline at end of file diff --git a/fastvideo.egg-info/dependency_links.txt b/fastvideo.egg-info/dependency_links.txt new file mode 100644 index 0000000000000000000000000000000000000000..8b137891791fe96927ad78e64b0aad7bded08bdc --- /dev/null +++ b/fastvideo.egg-info/dependency_links.txt @@ -0,0 +1 @@ + diff --git a/fastvideo.egg-info/requires.txt b/fastvideo.egg-info/requires.txt new file mode 100644 index 0000000000000000000000000000000000000000..9c5bdb1b40b34350bb4efee62f3f86ac9e86a280 --- /dev/null +++ b/fastvideo.egg-info/requires.txt @@ -0,0 +1,52 @@ +transformers==4.46.1 +accelerate==1.0.1 +tokenizers==0.20.1 +albumentations==1.4.20 +av==13.1.0 +decord==0.6.0 +einops==0.8.0 +fastapi==0.115.3 +gdown==5.2.0 +h5py==3.12.1 +idna==3.6 +imageio==2.36.0 +matplotlib==3.9.2 +numpy==1.26.3 +omegaconf==2.3.0 +pandas==2.2.3 +pillow==10.2.0 +pydub==0.25.1 +pytorch-lightning==2.4.0 +pytorchvideo==0.1.5 +PyYAML==6.0.1 +regex==2024.9.11 +requests==2.31.0 +scikit-learn==1.5.2 +scipy==1.13.0 +six==1.16.0 +test-tube==0.7.5 +timm==1.0.11 +torchdiffeq==0.2.4 +torchmetrics==1.5.1 +tqdm==4.66.5 +urllib3==2.2.0 +uvicorn==0.32.0 +scikit-video==1.1.11 +imageio-ffmpeg==0.5.1 +sentencepiece==0.2.0 +beautifulsoup4==4.12.3 +ftfy==6.3.0 +moviepy==1.0.3 +wandb==0.18.5 +pydantic==2.9.2 +huggingface_hub==0.26.1 +protobuf==5.28.3 +watch +gpustat +peft==0.13.2 +liger_kernel==0.4.1 +einops==0.8.0 +wheel==0.44.0 +loguru +diffusers==0.32.0 +bitsandbytes diff --git a/fastvideo.egg-info/top_level.txt b/fastvideo.egg-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..a1c1aae0348e441c9286ac6ddef3173bea01d3af --- /dev/null +++ b/fastvideo.egg-info/top_level.txt @@ -0,0 +1,7 @@ +__assets__ +checkpoints_g2rpo +data +fastvideo +hope +images_g2rpo +wandb diff --git a/hope/finetune_mergestep.hope b/hope/finetune_mergestep.hope new file mode 100644 index 0000000000000000000000000000000000000000..34aa6ec0ab063f049a924a8c0f65de3fa06f86a9 --- /dev/null +++ b/hope/finetune_mergestep.hope @@ -0,0 +1,68 @@ +[base] +type = ml-vision + +[resource] +usergroup = hadoop-camera3d +queue = root.hldy_training_cluster.hadoop-aipnlp.h800_vi_sp + +[dataset] +dataset_name = +dataset_type = +dataset_path = + +[job_track] +demand_id = 91369190 +upstream_jobid = +input_dir = +output_dir = +log_dir = + +[user_args] + +[roles] +workers = 2 +worker.memory = 1920000 +worker.vcore = 128 +worker.gcoresh800-80g = 8 +worker.script = sh /mnt/dolphinfs/ssd_pool/docker/user/hadoop-videogen-hl/hadoop-camera3d/zhangshengjun/Granular-GRPO/hope/finetune_mergestep.sh /mnt/dolphinfs/ssd_pool/docker/user/hadoop-videogen-hl/hadoop-camera3d/zhangshengjun/DanceGRPO /mnt/dolphinfs/ssd_pool/docker/user/hadoop-videogen-hl/hadoop-camera3d/zhangshengjun/conda-envs/dancegrpo-v2/bin/python fastvideo/train_g2rpo_hps_merge.py 2 8 + +worker.ports = 1 + +[am] +afo.app.am.resource.mb = 4096 + +[tensorboard] +with.tensor.board = false + +[docker] +afo.docker.image.name = registryonline-hulk.sankuai.com/custom_prod/com.sankuai.data.hadoop.gpu/data-hadoop-camera3d_cuda12.4-nccl2.21.5-prod-10ab7b1d + + +[data] +afo.data.prefetch = false + +[failover] +afo.app.support.engine.failover = true + +[conda] +afo.conda.env.name = +afo.conda.env.path = +afo.conda.store.type = + +[distribute] +afo.role.worker.gpu_driver_version = 470.103.01 + +[others] +afo.app.env.YARN_CONTAINER_RUNTIME_DOCKER_SHM_SIZE_BYTES = 640000000000 +afo.xm.notice.receivers.account = zhangshengjun02 +with_requirements = false +afo.app.yarn.allocate.timeout.seconds = 3600000 +afo.app.blacklist.fail_times = 16 +#afo.role.worker.task.attempt.max.retry = 16 +afo.role.worker.task.attempt.max.retry = 1 +afo.dolphinfs.otherusers = hadoop-videogen-hl,hadoop-imagen-hl:true,hadoop-vision-data:true +afo.use.hdfs.fuse=true +afo.use.hdfs.fuse.subpath=:/mnt/hdfs +afo.use.hdfs.fuse.readonly=false +afo.role.worker.not.node_name = hldy-data-k8s-gpu-h800-node0483.mt,hldy-data-k8s-gpu-h800-node0866.mt,hldy-data-k8s-gpu-h800-node0187.mt,hldy-data-k8s-gpu-h800-node0059.mt,hldy-data-k8s-gpu-h800-node0178.mt,hldy-data-k8s-gpu-h800-node0670.mt,hldy-data-k8s-gpu-h800-node0303.mt,hldy-data-k8s-gpu-h800-node0950.mt,hldy-data-k8s-gpu-h800-node0785.mt,hldy-data-k8s-gpu-h800-node0416.mt,hldy-data-k8s-gpu-h800-node0846.mt,hldy-data-k8s-gpu-h800-node0836.mt,hldy-data-k8s-gpu-h800-node0802.mt,hldy-data-k8s-gpu-h800-node0768.mt,hldy-data-k8s-gpu-h800-node1014.mt,hldy-data-k8s-gpu-h800-node0843.mt +afo.role.am.not.node_name = hlsc-data-k8s-node0187.mt \ No newline at end of file diff --git a/hope/finetune_mergestep_multi.hope b/hope/finetune_mergestep_multi.hope new file mode 100644 index 0000000000000000000000000000000000000000..92121121a5fee2e31ac43a08f805ef7d8b409352 --- /dev/null +++ b/hope/finetune_mergestep_multi.hope @@ -0,0 +1,68 @@ +[base] +type = ml-vision + +[resource] +usergroup = hadoop-camera3d +queue = root.hldy_training_cluster.hadoop-aipnlp.h800_vi_sp + +[dataset] +dataset_name = +dataset_type = +dataset_path = + +[job_track] +demand_id = 91369190 +upstream_jobid = +input_dir = +output_dir = +log_dir = + +[user_args] + +[roles] +workers = 4 +worker.memory = 1920000 +worker.vcore = 128 +worker.gcoresh800-80g = 8 +worker.script = sh /mnt/dolphinfs/ssd_pool/docker/user/hadoop-videogen-hl/hadoop-camera3d/zhangshengjun/Granular-GRPO/hope/finetune_mergestep_multi.sh /mnt/dolphinfs/ssd_pool/docker/user/hadoop-videogen-hl/hadoop-camera3d/zhangshengjun/DanceGRPO /mnt/dolphinfs/ssd_pool/docker/user/hadoop-videogen-hl/hadoop-camera3d/zhangshengjun/conda-envs/dancegrpo-v2/bin/python fastvideo/train_g2rpo_hps_clip_merge.py 4 8 + +worker.ports = 1 + +[am] +afo.app.am.resource.mb = 4096 + +[tensorboard] +with.tensor.board = false + +[docker] +afo.docker.image.name = registryonline-hulk.sankuai.com/custom_prod/com.sankuai.data.hadoop.gpu/data-hadoop-camera3d_cuda12.4-nccl2.21.5-prod-10ab7b1d + + +[data] +afo.data.prefetch = false + +[failover] +afo.app.support.engine.failover = true + +[conda] +afo.conda.env.name = +afo.conda.env.path = +afo.conda.store.type = + +[distribute] +afo.role.worker.gpu_driver_version = 470.103.01 + +[others] +afo.app.env.YARN_CONTAINER_RUNTIME_DOCKER_SHM_SIZE_BYTES = 640000000000 +afo.xm.notice.receivers.account = zhangshengjun02 +with_requirements = false +afo.app.yarn.allocate.timeout.seconds = 3600000 +afo.app.blacklist.fail_times = 16 +#afo.role.worker.task.attempt.max.retry = 16 +afo.role.worker.task.attempt.max.retry = 1 +afo.dolphinfs.otherusers = hadoop-videogen-hl,hadoop-imagen-hl:true,hadoop-vision-data:true +afo.use.hdfs.fuse=true +afo.use.hdfs.fuse.subpath=:/mnt/hdfs +afo.use.hdfs.fuse.readonly=false +afo.role.worker.not.node_name = hldy-data-k8s-gpu-h800-node0483.mt,hldy-data-k8s-gpu-h800-node0866.mt,hldy-data-k8s-gpu-h800-node0187.mt,hldy-data-k8s-gpu-h800-node0059.mt,hldy-data-k8s-gpu-h800-node0178.mt,hldy-data-k8s-gpu-h800-node0670.mt,hldy-data-k8s-gpu-h800-node0303.mt,hldy-data-k8s-gpu-h800-node0950.mt,hldy-data-k8s-gpu-h800-node0785.mt,hldy-data-k8s-gpu-h800-node0416.mt,hldy-data-k8s-gpu-h800-node0846.mt,hldy-data-k8s-gpu-h800-node0836.mt,hldy-data-k8s-gpu-h800-node0802.mt,hldy-data-k8s-gpu-h800-node0768.mt,hldy-data-k8s-gpu-h800-node1014.mt,hldy-data-k8s-gpu-h800-node0843.mt +afo.role.am.not.node_name = hlsc-data-k8s-node0187.mt \ No newline at end of file diff --git a/scripts/run_g2rpo_qwenimage.sh b/scripts/run_g2rpo_qwenimage.sh new file mode 100644 index 0000000000000000000000000000000000000000..9d63195bd58fa16d32b7d85db769f7786488b3de --- /dev/null +++ b/scripts/run_g2rpo_qwenimage.sh @@ -0,0 +1,65 @@ +#!/bin/bash +# E-GRPO (G2RPO) training script for QwenImage +# Based on finetune_mergestep.sh configuration + +set -e + +# GPU 6 is faulty - use only the 6 confirmed working GPUs: 0,1,2,3,4,5 +# Force set these values (override any existing env vars) +export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5" +NPROC_PER_NODE=6 +NNODES=${NNODES:-1} +NODE_RANK=${NODE_RANK:-0} +MASTER_ADDR=${MASTER_ADDR:-localhost} +MASTER_PORT=${MASTER_PORT:-29501} + +# NCCL configuration to fix communication hangs +export NCCL_P2P_DISABLE=1 # Disable P2P (peer-to-peer GPU communication) +export NCCL_IB_DISABLE=1 # Disable InfiniBand +export NCCL_SHM_DISABLE=0 # Keep shared memory enabled +export NCCL_SOCKET_IFNAME=lo # Use localhost interface +export NCCL_DEBUG=WARN # Show warnings + +# Change to source_code directory +cd "$(dirname "$0")/.." + +echo "==========================================" +echo "E-GRPO Training for QwenImage" +echo "==========================================" +echo "Nodes: $NNODES" +echo "GPUs per node: $NPROC_PER_NODE" +echo "Master addr: $MASTER_ADDR" +echo "Master port: $MASTER_PORT" +echo "==========================================" + +# Run training +python -m torch.distributed.run \ + --nnodes=$NNODES \ + --nproc_per_node=$NPROC_PER_NODE \ + --node_rank=$NODE_RANK \ + --master_addr=$MASTER_ADDR \ + --master_port=$MASTER_PORT \ + fastvideo/train_g2rpo_qwenimage_merge.py \ + --pretrained_model_name_or_path ./data/QwenImage \ + --data_json_path ./data/qwenimage_rl_embeddings/videos2caption.json \ + --output_dir ./output/g2rpo_qwenimage \ + --hps_path ./data/hps/HPS_v2.1_compressed.pt \ + --hps_clip_path ./data/hps/open_clip_pytorch_model.bin \ + --h 1024 \ + --w 1024 \ + --sampling_steps 16 \ + --eta 0.7 \ + --shift 3.0 \ + --num_generations 12 \ + --learning_rate 2e-6 \ + --max_train_steps 301 \ + --checkpointing_steps 50 \ + --eta_step_list 0 1 2 3 4 5 6 7 \ + --eta_step_merge_list 1 1 1 2 2 2 3 3 \ + --granular_list 1 \ + --init_same_noise \ + --clip_range 1e-4 \ + --adv_clip_max 5.0 \ + --use_hpsv2 + +echo "Training completed!" diff --git a/scripts/run_g2rpo_sd.sh b/scripts/run_g2rpo_sd.sh new file mode 100644 index 0000000000000000000000000000000000000000..b1b4273c5b4a9c0e3816913da7aa93c6e792baff --- /dev/null +++ b/scripts/run_g2rpo_sd.sh @@ -0,0 +1,51 @@ +#!/bin/bash +# E-GRPO (G2RPO) training script for Stable Diffusion +# Based on finetune_mergestep.sh configuration + +set -e + +# GPU 6 is faulty - use only the 6 confirmed working GPUs: 0,1,2,3,4,5 +# Force set these values (override any existing env vars) +export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5" +NPROC_PER_NODE=6 +NNODES=1 +NODE_RANK=0 +MASTER_ADDR=localhost +MASTER_PORT=29500 + +# NCCL configuration to fix communication hangs +export NCCL_P2P_DISABLE=1 # Disable P2P (peer-to-peer GPU communication) +export NCCL_IB_DISABLE=1 # Disable InfiniBand +export NCCL_SHM_DISABLE=0 # Keep shared memory enabled +export NCCL_SOCKET_IFNAME=lo # Use localhost interface +export NCCL_DEBUG=WARN # Show warnings + +# Change to source_code directory +cd "$(dirname "$0")/.." + +echo "==========================================" +echo "E-GRPO Training for Stable Diffusion" +echo "==========================================" +echo "Nodes: $NNODES" +echo "GPUs per node: $NPROC_PER_NODE" +echo "Master addr: $MASTER_ADDR" +echo "Master port: $MASTER_PORT" +echo "==========================================" + +# Run training +python -m torch.distributed.run \ + --nnodes=$NNODES \ + --nproc_per_node=$NPROC_PER_NODE \ + --node_rank=$NODE_RANK \ + --master_addr=$MASTER_ADDR \ + --master_port=$MASTER_PORT \ + fastvideo/train_g2rpo_sd_merge.py \ + --config fastvideo/config_sd/base.py \ + --eta_step_list 0,1,2,3,4,5,6,7 \ + --eta_step_merge_list 1,1,1,2,2,2,3,3 \ + --granular_list 1 \ + --num_generations 4 \ + --eta 1.0 \ + --init_same_noise + +echo "Training completed!" diff --git a/wandb/debug-internal.log b/wandb/debug-internal.log new file mode 100644 index 0000000000000000000000000000000000000000..62c87df8738812e5ada90559b82b92af7f6ebf49 --- /dev/null +++ b/wandb/debug-internal.log @@ -0,0 +1,8 @@ +{"time":"2026-01-24T15:47:30.396962377+08:00","level":"INFO","msg":"using version","core version":"0.18.5"} +{"time":"2026-01-24T15:47:30.396995431+08:00","level":"INFO","msg":"created symlink","path":"/data1/zsj/SceneDPO/Rebuttal/E-GRPO/scoure_code/wandb/run-20260124_154730-hq86r6nt/logs/debug-core.log"} +{"time":"2026-01-24T15:47:30.522196443+08:00","level":"INFO","msg":"created new stream","id":"hq86r6nt"} +{"time":"2026-01-24T15:47:30.522235646+08:00","level":"INFO","msg":"stream: started","id":"hq86r6nt"} +{"time":"2026-01-24T15:47:30.522411807+08:00","level":"INFO","msg":"sender: started","stream_id":"hq86r6nt"} +{"time":"2026-01-24T15:47:30.522375695+08:00","level":"INFO","msg":"writer: Do: started","stream_id":{"value":"hq86r6nt"}} +{"time":"2026-01-24T15:47:30.522431913+08:00","level":"INFO","msg":"handler: started","stream_id":{"value":"hq86r6nt"}} +{"time":"2026-01-24T15:47:31.101294174+08:00","level":"INFO","msg":"Starting system monitor"} diff --git a/wandb/debug.log b/wandb/debug.log new file mode 100644 index 0000000000000000000000000000000000000000..ee1abc881287579e3c4c4fc4251993c63691e302 --- /dev/null +++ b/wandb/debug.log @@ -0,0 +1,25 @@ +2026-01-24 15:47:30,388 INFO MainThread:61675 [wandb_setup.py:_flush():79] Current SDK version is 0.18.5 +2026-01-24 15:47:30,388 INFO MainThread:61675 [wandb_setup.py:_flush():79] Configure stats pid to 61675 +2026-01-24 15:47:30,388 INFO MainThread:61675 [wandb_setup.py:_flush():79] Loading settings from /home/zsj/.config/wandb/settings +2026-01-24 15:47:30,388 INFO MainThread:61675 [wandb_setup.py:_flush():79] Loading settings from /data1/zsj/SceneDPO/Rebuttal/E-GRPO/scoure_code/wandb/settings +2026-01-24 15:47:30,388 INFO MainThread:61675 [wandb_setup.py:_flush():79] Loading settings from environment variables: {} +2026-01-24 15:47:30,388 INFO MainThread:61675 [wandb_setup.py:_flush():79] Applying setup settings: {'mode': None, '_disable_service': None} +2026-01-24 15:47:30,388 INFO MainThread:61675 [wandb_setup.py:_flush():79] Inferring run settings from compute environment: {'program_relpath': 'fastvideo/train_g2rpo_qwenimage_merge.py', 'program_abspath': '/data1/zsj/SceneDPO/Rebuttal/E-GRPO/scoure_code/fastvideo/train_g2rpo_qwenimage_merge.py', 'program': '/data1/zsj/SceneDPO/Rebuttal/E-GRPO/scoure_code/fastvideo/train_g2rpo_qwenimage_merge.py'} +2026-01-24 15:47:30,389 INFO MainThread:61675 [wandb_setup.py:_flush():79] Applying login settings: {} +2026-01-24 15:47:30,389 INFO MainThread:61675 [wandb_init.py:_log_setup():534] Logging user logs to /data1/zsj/SceneDPO/Rebuttal/E-GRPO/scoure_code/wandb/run-20260124_154730-hq86r6nt/logs/debug.log +2026-01-24 15:47:30,389 INFO MainThread:61675 [wandb_init.py:_log_setup():535] Logging internal logs to /data1/zsj/SceneDPO/Rebuttal/E-GRPO/scoure_code/wandb/run-20260124_154730-hq86r6nt/logs/debug-internal.log +2026-01-24 15:47:30,389 INFO MainThread:61675 [wandb_init.py:init():621] calling init triggers +2026-01-24 15:47:30,389 INFO MainThread:61675 [wandb_init.py:init():628] wandb.init called with sweep_config: {} +config: {'data_json_path': './data/qwenimage_rl_embeddings/videos2caption.json', 'dataloader_num_workers': 4, 'train_batch_size': 1, 'num_latent_t': 1, 'pretrained_model_name_or_path': './data/QwenImage', 'hps_path': './data/hps/HPS_v2.1_compressed.pt', 'hps_clip_path': './data/hps/open_clip_pytorch_model.bin', 'cfg': 0.0, 'seed': 42, 'output_dir': './output/g2rpo_qwenimage', 'checkpointing_steps': 50, 'max_train_steps': 301, 'learning_rate': 2e-06, 'lr_warmup_steps': 0, 'max_grad_norm': 1.0, 'gradient_checkpointing': False, 'selective_checkpointing': 1.0, 'mixed_precision': 'bf16', 'use_cpu_offload': False, 'sp_size': 1, 'train_sp_batch_size': 1, 'fsdp_sharding_startegy': 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a/wandb/run-20260124_023109-p3wmwi8u/files/output.log b/wandb/run-20260124_023109-p3wmwi8u/files/output.log new file mode 100644 index 0000000000000000000000000000000000000000..93a167f1b12e10b139c53bf6ee4c28cd2ea5dfcd --- /dev/null +++ b/wandb/run-20260124_023109-p3wmwi8u/files/output.log @@ -0,0 +1,46 @@ +I0124 02:31:11.127583 137984181106496 train_g2rpo_sd_merge.py:471] +allow_tf32: true +logdir: logs +mixed_precision: bf16 +num_checkpoint_limit: 5 +num_epochs: 300 +pretrained: + model: ./data/StableDiffusion + revision: main +prompt_fn: imagenet_animals +prompt_fn_kwargs: {} +resume_from: '' +reward_fn: hpsv2 +run_name: 2026.01.24_02.31.08 +sample: + batch_size: 1 + eta: 1.0 + guidance_scale: 5.0 + num_batches_per_epoch: 2 + num_steps: 50 +save_freq: 20 +seed: 42 +train: + adam_beta1: 0.9 + adam_beta2: 0.999 + adam_epsilon: 1.0e-08 + adam_weight_decay: 0.0001 + adv_clip_max: 5 + batch_size: 1 + cfg: true + clip_range: 0.0001 + gradient_accumulation_steps: 1 + learning_rate: 1.0e-05 + max_grad_norm: 1.0 + num_inner_epochs: 1 + timestep_fraction: 1.0 + use_8bit_adam: false +use_lora: false + +Loading pipeline components...: 100%|███████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:02<00:00, 2.66it/s] +/home/zsj/anaconda3/envs/g2rpo/lib/python3.10/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +I0124 02:31:14.318543 137984181106496 factory.py:159] Loaded ViT-H-14 model config. +I0124 02:31:19.361439 137984181106496 factory.py:207] Loading pretrained ViT-H-14 weights (./data/hps/open_clip_pytorch_model.bin). +/home/zsj/anaconda3/envs/g2rpo/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:4876: UserWarning: barrier(): using the device under current context. You can specify `device_id` in `init_process_group` to mute this warning. + warnings.warn( # warn only once diff --git a/wandb/run-20260124_023109-p3wmwi8u/files/requirements.txt b/wandb/run-20260124_023109-p3wmwi8u/files/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..ee5c7ffa6079b296e15f3c9ff9edceed1bfe0802 --- /dev/null +++ b/wandb/run-20260124_023109-p3wmwi8u/files/requirements.txt @@ -0,0 +1,189 @@ +scipy==1.13.0 +regex==2024.9.11 +sentencepiece==0.2.0 +six==1.16.0 +anyio==4.11.0 +nvidia-cuda-nvrtc-cu12==12.6.77 +scikit-video==1.1.11 +platformdirs==4.5.0 +mypy==1.11.1 +ruff==0.6.5 +charset-normalizer==3.4.4 +torch==2.9.0+cu126 +av==13.1.0 +pillow==10.2.0 +gpustat==1.1.1 +torchvision==0.24.0+cu126 +multidict==6.7.0 +torchmetrics==1.5.1 +aiohttp==3.13.1 +transformers==4.46.1 +decord==0.6.0 +wcwidth==0.2.14 +sphinx-lint==1.0.0 +nvidia-cuda-runtime-cu12==12.6.77 +pytz==2025.2 +codespell==2.3.0 +hpsv2==1.2.0 +mypy_extensions==1.1.0 +numpy==1.26.3 +omegaconf==2.3.0 +Markdown==3.9 +tzdata==2025.2 +pandas==2.2.3 +pytorch-lightning==2.4.0 +aiosignal==1.4.0 +aiohappyeyeballs==2.6.1 +python-dateutil==2.9.0.post0 +seaborn==0.13.2 +beautifulsoup4==4.12.3 +isort==5.13.2 +httpx==0.28.1 +certifi==2025.10.5 +ml_collections==1.1.0 +nvidia-cudnn-cu12==9.10.2.21 +hf-xet==1.2.0 +requests==2.31.0 +inflect==6.0.4 +iniconfig==2.1.0 +braceexpand==0.1.7 +h5py==3.12.1 +wandb==0.18.5 +protobuf==3.20.3 +ninja==1.13.0 +kiwisolver==1.4.9 +networkx==3.3 +packaging==25.0 +fvcore==0.1.5.post20221221 +pyparsing==3.2.5 +starlette==0.41.3 +frozenlist==1.8.0 +docker-pycreds==0.4.0 +Werkzeug==3.1.3 +MarkupSafe==2.1.5 +einops==0.8.0 +sentry-sdk==2.42.0 +PyYAML==6.0.1 +nvidia-nccl-cu12==2.27.5 +datasets==4.3.0 +polib==1.2.0 +safetensors==0.6.2 +async-timeout==5.0.1 +setproctitle==1.3.7 +clint==0.5.1 +matplotlib==3.9.2 +propcache==0.4.1 +termcolor==3.1.0 +antlr4-python3-runtime==4.9.3 +cycler==0.12.1 +fastvideo==1.2.0 +toml==0.10.2 +xxhash==3.6.0 +wheel==0.44.0 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components...: 100%|███████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:02<00:00, 2.94it/s] +/home/zsj/anaconda3/envs/g2rpo/lib/python3.10/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +I0124 02:37:36.227559 136656101939008 factory.py:159] Loaded ViT-H-14 model config. +I0124 02:37:40.703484 136656101939008 factory.py:207] Loading pretrained ViT-H-14 weights (./data/hps/open_clip_pytorch_model.bin). +I0124 02:37:50.086529 136656101939008 train_g2rpo_sd_merge.py:655] ***** Running E-GRPO (G2RPO) Training for Stable Diffusion ***** +I0124 02:37:50.086876 136656101939008 train_g2rpo_sd_merge.py:656] Num Epochs = 300 +I0124 02:37:50.086986 136656101939008 train_g2rpo_sd_merge.py:657] Num generations per prompt = 4 +I0124 02:37:50.087092 136656101939008 train_g2rpo_sd_merge.py:658] Eta step list = [0, 1, 2, 3, 4, 5, 6, 7] +I0124 02:37:50.087175 136656101939008 train_g2rpo_sd_merge.py:659] Eta step merge list = [1, 1, 1, 2, 2, 2, 3, 3] +I0124 02:37:50.087247 136656101939008 train_g2rpo_sd_merge.py:660] Granular list = [1] diff --git a/wandb/run-20260124_023732-grygcm94/files/requirements.txt b/wandb/run-20260124_023732-grygcm94/files/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..ee5c7ffa6079b296e15f3c9ff9edceed1bfe0802 --- /dev/null +++ b/wandb/run-20260124_023732-grygcm94/files/requirements.txt @@ -0,0 +1,189 @@ +scipy==1.13.0 +regex==2024.9.11 +sentencepiece==0.2.0 +six==1.16.0 +anyio==4.11.0 +nvidia-cuda-nvrtc-cu12==12.6.77 +scikit-video==1.1.11 +platformdirs==4.5.0 +mypy==1.11.1 +ruff==0.6.5 +charset-normalizer==3.4.4 +torch==2.9.0+cu126 +av==13.1.0 +pillow==10.2.0 +gpustat==1.1.1 +torchvision==0.24.0+cu126 +multidict==6.7.0 +torchmetrics==1.5.1 +aiohttp==3.13.1 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a/wandb/run-20260124_141237-3a51ocuw/run-3a51ocuw.wandb b/wandb/run-20260124_141237-3a51ocuw/run-3a51ocuw.wandb new file mode 100644 index 0000000000000000000000000000000000000000..abfcc053a5b5b81944ba2d822ba3cbddc62d2ee2 Binary files /dev/null and b/wandb/run-20260124_141237-3a51ocuw/run-3a51ocuw.wandb differ diff --git a/wandb/run-20260124_154730-hq86r6nt/files/output.log b/wandb/run-20260124_154730-hq86r6nt/files/output.log new file mode 100644 index 0000000000000000000000000000000000000000..7de561f9094056ec5afa791383f27517b3dfe076 --- /dev/null +++ b/wandb/run-20260124_154730-hq86r6nt/files/output.log @@ -0,0 +1,28 @@ +***** Running E-GRPO (G2RPO) Training for QwenImage ***** + Num examples = 103764 + Dataloader size = 17294 + Eta step list = [0, 1, 2, 3, 4, 5, 6, 7] + Eta step merge list = [1, 1, 1, 2, 2, 2, 3, 3] + Granular list = [1] + Total training parameters per FSDP shard = 3.405066888 B +Get Anchor Progress: 100%|████████████████████████████████████████████████| 16/16 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