Update README.md

README.md

@@ -1,3 +1,203 @@
----
-license: cc-by-4.0
----
+---
+license: mit
+datasets:
+- internlm/EndoCoT-Data
+language:
+- en
+base_model:
+- Qwen/Qwen-Image-Edit-2511
+---
+
+<p align="center">   <img src="fig/banner.svg" alt="EndoCoT" width="900"/> </p>
+
+<p align="center">
+  <a href="https://github.com/InternLM/EndoCoT"><img src="https://img.shields.io/github/stars/InternLM/EndoCoT?style=flat-square&logo=github&label=Stars&color=FFB300"></a>
+  <a href="https://github.com/InternLM/EndoCoT/forks"><img src="https://img.shields.io/github/forks/InternLM/EndoCoT?style=flat-square&logo=github&label=Forks&color=2196F3"></a>
+  <a href="https://github.com/InternLM/EndoCoT/issues"><img src="https://img.shields.io/github/issues/InternLM/EndoCoT?style=flat-square&logo=github&label=Issues&color=4CAF50"></a>
+  <a href="https://github.com/InternLM/EndoCoT/blob/main/LICENSE"><img src="https://img.shields.io/github/license/InternLM/EndoCoT?style=flat-square&label=License&color=9C27B0"></a>
+  <br>
+  <a href="https://arxiv.org/abs/xxxx.xxxxx"><img src="https://img.shields.io/badge/Paper-arXiv-B31B1B?style=flat-square"></a>
+  <a href="https://internlm.github.io/EndoCoT/"><img src="https://img.shields.io/badge/Homepage-Project-blue?style=flat-square"></a>
+  <a href="https://huggingface.co/internlm/EndoCoT"><img src="https://img.shields.io/badge/Model-HuggingFace-yellow?style=flat-square"></a>
+  <a href="https://huggingface.co/datasets/internlm/EndoCoT-Data"><img src="https://img.shields.io/badge/Dataset-HuggingFace-orange?style=flat-square"></a>
+  <br>
+  <br>
+  <img src="fig/teaser.jpg" alt="Teaser" width="100%" style="border-radius: 10px; box-shadow: 0 6px 20px rgba(0,0,0,0.2);">
+</p>
+
+
+
+
+# EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models
+
+## 📝TODO
+
+- [x] Open source the training code
+- [ ] Open source the training data
+- [x] Open source the main task ckpt
+- [ ] Open source the edit model ckpt
+- [ ] Refactor the codebase for better usability and maintainability
+
+## 📰News
+
+- 🚀 [2026/3/12] We have released the EndoCoT [repository](https://github.com/InternLM/EndoCoT) and [ckpts](https://huggingface.co/internlm/EndoCoT).
+
+## 🌟Highlight
+
+![main](fig/main.jpg)
+
+- EndoCoT is a reasoning paradigm for diffusion models that enables step-by-step inference. It outperforms conventional training methods on Qwen-Image-Edit-2511.
+
+![exp](fig/exp.png)
+
+- And provide transparent, intermediate reasoning trajectories.
+
+![case](fig/case.jpg)
+
+## ⚡Quick Start
+
+### Setup environment
+
+```bash
+git clone https://github.com/InternLM/EndoCoT
+cd EndoCoT
+conda create -n EndoCoT python=3.10
+conda activate EndoCot
+# Please install the version of torch compatible with your machine.
+pip install -r requirements.txt
+# Please install the version of vLLM compatible with your machine.
+```
+
+### Inference
+
+1. Download the ckpt:
+
+   - You may find our pretrained weights at: [**EndoCoT**](https://huggingface.co/InternLM/EndoCoT)
+
+   >  Following the configuration of *[**Diffthinker**](https://github.com/lcqysl/DiffThinker)*, we provide a customized checkpoint for **Qwen-Image-Edit**. This checkpoint has been merged from the original `safetensors` to ensure compatibility with*[**Diffsynth-Studio**](https://github.com/modelscope/DiffSynth-Studio)* training. Please use the checkpoint provided in this repository instead of the official version for correct loading and inference.
+
+2. Test Single Case
+
+   ```bash
+   cd test
+   python test.py \
+       --task Maze \
+       --model_root /path/to/merged_ckpts \
+       --lora_path /path/to/your_lora_weight.safetensors \
+       --input_image ./data/sudoku_sample.png \
+       --output_dir ./outputs/sudoku_results
+   ```
+
+3. Eval Our Ckpt
+
+   > We follow the exact same setting as *[**Diffthinker**](https://github.com/lcqysl/DiffThinker)*
+
+   ```bash
+   cd Maze
+   bash eval/gen_and_parse.sh
+   bash eval/eval_path.sh
+   ```
+
+### Training
+
+1. Download the datasets & metadata.csv
+
+   - You may find our training data at: [**EndoCoT dataset**](https://huggingface.co/datasets/InternLM/EndoCoT)
+
+   > Since the metadata uses relative paths, please ensure the dataset files are placed in the same directory as `metadata.csv`
+
+2. Train your model
+
+   ```bash
+   cd DiffSynth-Studio
+   bash add/Maze/stage1.sh
+   python change_ckpt_prefix.py --src /path/to/the/Maze/save/dir/Maze_stage1	
+   bash add/Maze/stage2.sh
+   python change_ckpt_prefix.py --src /path/to/the/Maze/save/dir/Maze_stage2
+   ```
+
+### How to change the latent reasoning steps?
+
+> **Note on Customization:** Since the current implementation is straightforward, you can only manually adjust the latent reasoning steps in `DiffSynth-Studio/diffsynth/pipelines/qwen_image.py`:
+>
+> - **Line 442:** Modify `infer_steps`.
+> - **Line 471:** Modify `training_steps`.
+>
+> ##### **We plan to optimize this in future releases.**
+
+```python
+def encode_prompt_edit(self, pipe: QwenImagePipeline, prompt, edit_image, is_final, gt_prompt=None, idx=None):
+
+        drop_idx = 64
+        if type(prompt[0])==str:
+            template =  "<|im_start|>system\nDescribe the key features of the input image (color, shape, size, texture, objects, background), then explain how the user's text instruction should alter or modify the image. Generate a new image that meets the user's requirements while maintaining consistency with the original input where appropriate.<|im_end|>\n<|im_start|>user\n<|vision_start|><|image_pad|><|vision_end|>{}<|im_end|>\n<|im_start|>assistant\n"
+            txt = template.format(prompt[0])
+            model_inputs = pipe.processor(text=txt, images=edit_image, padding=True, return_tensors="pt").to(pipe.device)
+            embedding_layers = pipe.text_encoder.model.language_model.get_input_embeddings()
+            with torch.no_grad():
+                inputs_embeds = embedding_layers(model_inputs.input_ids)
+            self.attention_mask = model_inputs.attention_mask
+            self.pixel_values = model_inputs.pixel_values
+            self.image_grid_thw = model_inputs.image_grid_thw
+        else:
+            inputs_embeds= prompt[0]
+            
+        # dxl: test use
+        if is_final==None or idx!=None:
+            print("现在在inference。或者stage2训练")
+            if idx!=None:
+                iter_times = idx-2
+            else:
+                # infer step
+                iter_times = 50
+                
+            with torch.no_grad():
+                inputs_embeds = self.manual_generate_eval(
+                    pipe, 
+                    inputs_embeds=inputs_embeds,
+                    max_new_tokens=iter_times,
+                ).detach()
+            
+            # dxl: only update the last 2 tokens
+            if idx!=None:
+                inputs_embeds = self.manual_generate_eval(
+                    pipe,
+                    inputs_embeds=inputs_embeds,
+                    max_new_tokens=2,
+                )
+
+            generated_embeds = inputs_embeds
+
+		... ... 
+        
+        # dxl：training
+        if is_final!=None and idx==None:
+            try:
+                generated_embeds, _ = self.manual_generate(
+                    pipe,
+                    inputs_embeds=inputs_embeds,
+                    is_final=is_final,
+                    # training steps
+                    max_new_tokens=2,
+                )
+            except Exception as e:
+                print(f"Error!: {type(e).__name__} - {e}")
+                print(inputs_embeds.shape)
+                assert False
+
+        try: 
+            return split_hidden_states, generated_embeds, eos_loss
+        except:
+            print(f"[WARNING] Prompt was not updated correctly for inference.")
+            return split_hidden_states
+```
+
+## 📖 Citation
+
+```
+Coming Soon
+```
+
+## ⚖️ License
+
+![Code License](https://img.shields.io/badge/Code%20License-MIT-green.svg) ![Data License](https://img.shields.io/badge/Data%20License-CC%20By%20NC%204.0-red.svg)