update readme

v1.0.0 update

.gitignore

@@ -15,6 +15,6 @@ dev
 scepter.egg-info
 .readthedocs.yml
 1.9
-MANIFEST.in
+#MANIFEST.in
 *resources
 *.ipynb_checkpoints*

docs/en/conf.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 # Configuration file for the Sphinx documentation builder.
 #
 # This file only contains a selection of the most common options. For a full

docs/en/tasks/stylebooth.md

@@ -29,8 +29,21 @@ Given an original image, image editing aims to generate an image that align with
     <td><img src="../../../asset/images/stylebooth/retrogame.jpeg" width="240"></td>
     <td><img src="../../../asset/images/stylebooth/vangogh.jpeg" width="240"></td>
   </tr>
+  <tr>
+    <td><strong>Origin Image</strong></td>
+    <td><strong>Lowpoly</strong></td>
+    <td><strong>Colored Pencil Art</strong></td>
+    <td><strong>Watercolor</strong></td>
+    <td><strong>misc-disco</strong></td>
+  </tr>
+  <tr>
+    <td><img src="../../../asset/images/stylebooth/mountain.jpg" width="240"></td>
+    <td><img src="../../../asset/images/stylebooth/lowpoly.jpg" width="240"></td>
+    <td><img src="../../../asset/images/stylebooth/colorpencil.jpeg" width="240"></td>
+    <td><img src="../../../asset/images/stylebooth/watercolor.jpeg" width="240"></td>
+    <td><img src="../../../asset/images/stylebooth/disco.jpeg" width="240"></td>
+  </tr>
 </table>
-
 ## Features
 
 | **Text-Based** | **Exemplar-Based** |
@@ -43,7 +56,7 @@ Given an original image, image editing aims to generate an image that align with
 - More models will be released in the future.
 
 ## Run StyleBooth
-- Code implementation: See model configuration and code based on [🪄SCEPTER](https://github.com/modelscope/scepter).
+- Code implementation: See model configuration and code based on [🪄SCEPTER](https://github.com/modelscope/scepter/blob/main/docs/en/tasks/stylebooth.md).
 
 - Demo: Try [🖥️SCEPTER Studio](https://github.com/modelscope/scepter/tree/main?tab=readme-ov-file#%EF%B8%8F-scepter-studio).
 
@@ -92,7 +105,7 @@ class DiffusionInferenceTest(unittest.TestCase):
         output = diff_infer({'prompt': 'Let this image be in the style of sai-lowpoly'},
                             style_edit_image=Image.open('asset/images/inpainting_text_ref/ex4_scene_im.jpg'),
                             style_guide_scale_text=7.5,
-                            style_guide_scale_image=0.5)
+                            style_guide_scale_image=1.5)
         save_path = os.path.join(self.tmp_dir,
                                  'stylebooth_test_lowpoly_cute_dog.png')
         save_image(output['images'], save_path)
@@ -101,3 +114,17 @@ class DiffusionInferenceTest(unittest.TestCase):
 if __name__ == '__main__':
     unittest.main()
 ```
+
+## StyleTuner and De-StyleTuner.
+
+### Base I2I Model.
+
+For style and de-style tuning, we use a private high-resolution I2I model trained with [InstructPix2Pix dataset](https://instruct-pix2pix.eecs.berkeley.edu/) as base model. However, one can try the same tunning process using this [yaml](https://github.com/modelscope/scepter/blob/main/scepter/methods/edit/edit_512_lora.yaml) based on any other I2I model, such as StyleBooth (shown in this yaml), [InstructPix2Pix](https://github.com/timothybrooks/instruct-pix2pix) or [MagicBrush](https://github.com/OSU-NLP-Group/MagicBrush).
+
+### Training Data.
+
+Please check the zips for correct format: [De-Text](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fdetext.zip), [Image2Hed](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fhed_pair.zip), [Image2Depth](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fimage2depth.zip), [Depth2Image](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fdepth2image.zip).
+
+### Launch.
+
+See [code](https://github.com/modelscope/scepter/blob/cbbef4a2da5b66fc33b9f8ece7f2fb4aac9d6e3c/tests/tools/test_train.py#L220) for more information.

docs/en/tutorials/dataset.md

@@ -5,7 +5,7 @@ Below are examples for each format, illustrating their details and basic usage.
 
 ## Modelscope Format
 
-We use a [custom-stylized dataset](https://modelscope.cn/datasets/damo/style_custom_dataset/summary), which included classes 3D, anime, flat illustration, oil painting, sketch, and watercolor, each with 30 image-text pairs.
+We use a [custom-stylized dataset](https://modelscope.cn/datasets/iic/style_custom_dataset/summary), which included classes 3D, anime, flat illustration, oil painting, sketch, and watercolor, each with 30 image-text pairs.
 
 ```python
 # pip install modelscope
@@ -16,7 +16,11 @@ print(next(iter(ms_train_dataset)))
 
 ## CSV Format
 
-For the data format used by SCEPTER Studio, please refer to [3D_example_csv.zip](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/3D_example_csv.zip).
+For the data format used by SCEPTER Studio, please refer to [3D_example_csv.zip](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/3D_example_csv.zip) and [hed_pair.zip](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fhed_pair.zip).
+```shell
+mkdir -p cache/datasets/ && wget 'https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/3D_example_csv.zip' -O cache/datasets/3D_example_csv.zip && unzip cache/datasets/3D_example_csv.zip -d cache/datasets/ && rm cache/datasets/3D_example_csv.zip
+mkdir -p cache/datasets/ && wget 'https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/hed_pair.zip' -O cache/datasets/hed_pair.zip && unzip cache/datasets/hed_pair.zip -d cache/datasets/ && rm cache/datasets/hed_pair.zip
+```
 
 ## TXT Format
 
@@ -24,3 +28,4 @@ To facilitate starting training in command-line mode, you can use a dataset in t
 
 ```shell
 mkdir -p cache/datasets/ && wget 'https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/3D_example_txt.zip' -O cache/datasets/3D_example_txt.zip && unzip cache/datasets/3D_example_txt.zip -d cache/datasets/ && rm cache/datasets/3D_example_txt.zip
+```

docs/en/tutorials/inference.md

@@ -40,6 +40,6 @@ python scepter/tools/run_inference.py --cfg scepter/methods/scedit/t2i/sd15_512_
 
 - SCEdit
 ```shell
-python scepter/tools/run_inference.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_canny.yaml --num_samples 1 --prompt 'a single flower is shown in front of a tree' --save_folder 'test_flower_canny' --image_size 768 --task control --image 'asset/images/flower.jpg' --control_mode canny --pretrained_model ms://damo/scepter_scedit@controllable_model/SD2.1/canny_control/0_SwiftSCETuning/pytorch_model.bin   # canny
-python scepter/tools/run_inference.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_pose.yaml --num_samples 1 --prompt 'super mario' --save_folder 'test_mario_pose' --image_size 768 --task control --image 'asset/images/pose_source.png' --control_mode source --pretrained_model ms://damo/scepter_scedit@controllable_model/SD2.1/pose_control/0_SwiftSCETuning/pytorch_model.bin   # pose
+python scepter/tools/run_inference.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_canny.yaml --num_samples 1 --prompt 'a single flower is shown in front of a tree' --save_folder 'test_flower_canny' --image_size 768 --task control --image 'asset/images/flower.jpg' --control_mode canny --pretrained_model ms://iic/scepter_scedit@controllable_model/SD2.1/canny_control/0_SwiftSCETuning/pytorch_model.bin   # canny
+python scepter/tools/run_inference.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_pose.yaml --num_samples 1 --prompt 'super mario' --save_folder 'test_mario_pose' --image_size 768 --task control --image 'asset/images/pose_source.png' --control_mode source --pretrained_model ms://iic/scepter_scedit@controllable_model/SD2.1/pose_control/0_SwiftSCETuning/pytorch_model.bin   # pose
 ```

docs/zh_cn/conf.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 # Configuration file for the Sphinx documentation builder.
 #
 # This file only contains a selection of the most common options. For a full

environment.yaml

@@ -6,4 +6,5 @@ dependencies:
   - pip>=20.3
   - numpy>=1.23.1
   - pip:
+      - -r requirements/recommended.txt
       - -r requirements.txt

example/classifier/classifier_dataset.py

@@ -2,7 +2,6 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 import numpy as np
 import torchvision
-
 from scepter.modules.data.dataset.base_dataset import BaseDataset
 from scepter.modules.data.dataset.registry import DATASETS
 from scepter.modules.utils.config import dict_to_yaml

readme.md

@@ -18,6 +18,9 @@ SCEPTER offers 3 core components:
 
 
 ## 🎉 News
+- [2024.09]: We introduce **ACE**, an **A**ll-round **C**reator and **E**ditor adept at executing a diverse array of image editing tasks tailored to your specifications. Built upon the cutting-edge Diffusion Transformer architecture, ACE has been extensively trained on a comprehensive dataset to seamlessly interpret and execute any natural language instruction. For further information, please consult the [project page]().
+- [2024.07]: Support the inference and training of open-source generative models based on the [DiT](https://arxiv.org/abs/2212.09748) architecture, such as [SD3](https://arxiv.org/pdf/2403.03206) and [PixArt](https://arxiv.org/abs/2310.00426).
+- [2024.05]: Introducing SCEPTER v1, supporting customized image edit tasks! Simply provide 10 image pairs, SCEPTER will tune an edit tuner for your own Image-to-Image tasks, like `Clay Style`, `De-Text`, `Segmentation`, etc.
 - [2024.04]: New [StyleBooth](https://ali-vilab.github.io/stylebooth-page/) demo on SCEPTER Studio for`Text-Based Style Editing`.
 - [2024.03]: We optimize the training UI and checkpoint management. New [LAR-Gen](https://arxiv.org/abs/2403.19534) model has been added on SCEPTER Studio, supporting `zoom-out`, `virtual try on`, `inpainting`.
 - [2024.02]: We release new SCEdit controllable image synthesis models for SD v2.1 and SD XL. Multiple strategies applied to accelerate inference time for SCEPTER Studio.
@@ -29,59 +32,31 @@ SCEPTER offers 3 core components:
 
 ## 🖼 Gallery for Recent Works
 
-### StyleBooth
-<table>
-  <tr>
-    <td><strong>Origin Image</strong><br>Gold Dragon Tuner</td>
-    <td><strong>Graffiti Art</strong></td>
-    <td><strong>Adorable Kawaii</strong></td>
-    <td><strong>game-retro game</strong></td>
-    <td><strong>Vincent van Gogh</strong></td>
-  </tr>
-  <tr>
-    <td><img src="asset/images/scedit/tuner_gold_dragon.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/graffiti.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/kawaii.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/retrogame.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/vangogh.jpeg" width="240"></td>
-  </tr>
-</table>
+### <img src="asset/images/ace/logo.png" height=20> <img src="asset/images/ace/text.png" height=20>
 
-<table>
-  <tr>
-    <td><strong>Origin Image</strong></td>
-    <td><strong>Lowpoly</strong></td>
-    <td><strong>Colored Pencil Art</strong></td>
-    <td><strong>Watercolor</strong></td>
-    <td><strong>misc-disco</strong></td>
-  </tr>
-  <tr>
-    <td><img src="asset/images/stylebooth/mountain.jpg" width="240"></td>
-    <td><img src="asset/images/stylebooth/lowpoly.jpg" width="240"></td>
-    <td><img src="asset/images/stylebooth/colorpencil.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/watercolor.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/disco.jpeg" width="240"></td>
-  </tr>
-</table>
+ACE is a unified foundational model framework that supports a wide range of visual generation tasks. By defining CU for unifying multi-modal inputs across different tasks and incorporating long-
+context CU, we introduce historical contextual information into visual generation tasks, paving
+the way for ChatGPT-like dialog systems in visual generation.
+
+<a href="https://ali-vilab.github.io/ace-page/">
+  <img src="asset/images/ace/teaser_dy.gif" width=1024>
+</a>
 
 
 ## 🛠️ Installation
 
-- Create new environment
+- Create new environment with `conda` command:
 
 ```shell
 conda env create -f environment.yaml
 conda activate scepter
 ```
-- We recommend installing the specific version of PyTorch and accelerate toolbox [xFormers](https://pypi.org/project/xformers/). You can install these recommended version by pip:
 
+- Install with `pip` command:
+
+We recommend installing the specific version of PyTorch and accelerate toolbox [xFormers](https://pypi.org/project/xformers/). You can install these recommended version by pip:
 ```shell
 pip install -r requirements/recommended.txt
-```
-
-- Install SCEPTER by the `pip` command:
-
-```shell
 pip install scepter
 ```
 
@@ -132,8 +107,6 @@ The startup of **SCEPTER Studio** eliminates the need for manual downloading and
 Depending on the network and hardware situation, the initial startup usually requires 15-60 minutes, primarily involving the download and processing of SDv1.5, SDv2.1, and SDXL models.
 Therefore, subsequent startups will become much faster (about one minute) as downloading is no longer required.
 
-To support the sharing and downloading of models,
-please make sure that you have installed **zip** and Git Large File Storage (**git lfs**).
 ### Usage Demo
 
 |              [Image Editing](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Fimage_editing_20240419.webm)              |                [Training](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Ftraining_20240419.webm)                 |              [Model Sharing](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Fmodel_sharing_20240419.webm)               |             [Model Inference](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Fmodel_inference_20240419.webm)              |             [Data Management](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Fdata_management_20240419.webm)              |
@@ -142,7 +115,7 @@ please make sure that you have installed **zip** and Git Large File Storage (**g
 
 ### Modelscope Studio & Huggingface Space
 
-We deploy a work studio on Modelscope that includes only the inference tab, please refer to [ms_scepter_studio](https://www.modelscope.cn/studios/damo/scepter_studio/summary) and [hf_scepter_studio](https://huggingface.co/spaces/modelscope/scepter_studio)
+We deploy a work studio on Modelscope that includes only the inference tab, please refer to [ms_scepter_studio](https://www.modelscope.cn/studios/iic/scepter_studio/summary) and [hf_scepter_studio](https://huggingface.co/spaces/modelscope/scepter_studio)
 
 
 ## 🔍 Learn More

requirements/framework.txt

@@ -1,7 +1,8 @@
 albumentations
+beautifulsoup4
 bezier
 einops
-modelscope
+modelscope==1.14.0
 ms-swift>=2.0.1
 numpy
 open_clip_torch

requirements/scepter_studio.txt

@@ -1,5 +1,5 @@
 bitsandbytes
-gradio>=3.47.1,<4.0.0
+gradio
 imagehash
 psutil
 tiktoken

scepter/methods/edit/edit_512_lora.yaml

@@ -0,0 +1,250 @@
+ENV:
+  BACKEND: nccl
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 2000
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 100
+  #
+  WORK_DIR: ./cache/save_data/edit_512_lora
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  TUNER:
+    -
+      NAME: SwiftLoRA
+      R: 64
+      LORA_ALPHA: 64
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: model.*(to_q|to_k|to_v|to_out.0|net.0.proj|net.2)$
+  #
+  MODEL:
+    NAME: LatentDiffusionEdit
+    PARAMETERIZATION: eps
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL: ms://iic/stylebooth@models/stylebooth-tb-5000-0.bin
+    IGNORE_KEYS: [ ]
+    CONCAT_NO_SCALE_FACTOR: True
+    SCALE_FACTOR: 0.18215
+    SIZE_FACTOR: 8
+    # DEFAULT_N_PROMPT: 'lowres, error, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "scaled_linear"
+      "BETA_MIN": 0.00085
+      "BETA_MAX": 0.012
+    USE_EMA: False
+    #
+    DIFFUSION_MODEL:
+      NAME: DiffusionUNet
+      IN_CHANNELS: 8
+      OUT_CHANNELS: 4
+      MODEL_CHANNELS: 320
+      NUM_HEADS: 8
+      NUM_RES_BLOCKS: 2
+      ATTENTION_RESOLUTIONS: [ 4, 2, 1 ]
+      CHANNEL_MULT: [ 1, 2, 4, 4 ]
+      CONV_RESAMPLE: True
+      DIMS: 2
+      USE_CHECKPOINT: False
+      USE_SCALE_SHIFT_NORM: False
+      RESBLOCK_UPDOWN: False
+      USE_SPATIAL_TRANSFORMER: True
+      TRANSFORMER_DEPTH: 1
+      CONTEXT_DIM: 768
+      DISABLE_MIDDLE_SELF_ATTN: False
+      USE_LINEAR_IN_TRANSFORMER: False
+      PRETRAINED_MODEL:
+      IGNORE_KEYS: []
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      EMBED_DIM: 4
+      PRETRAINED_MODEL:
+      IGNORE_KEYS: []
+      BATCH_SIZE: 4
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    TOKENIZER:
+      NAME: ClipTokenizer
+      PRETRAINED_PATH: ms://AI-ModelScope/clip-vit-large-patch14
+      LENGTH: 77
+      CLEAN: True
+    #
+    COND_STAGE_MODEL:
+      NAME: FrozenCLIPEmbedder
+      FREEZE: True
+      LAYER: last
+      PRETRAINED_MODEL: ms://AI-ModelScope/clip-vit-large-patch14
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 50
+    SEED: 2023
+    GUIDE_SCALE: #7.5
+      image: 1.5
+      text: 7.5
+    GUIDE_RESCALE: 0.5
+    DISCRETIZATION: trailing
+    IMAGE_SIZE: [512, 512]
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 0.064
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: cache/datasets/hed_pair
+    MS_DATASET_NAMESPACE: ""
+    MS_DATASET_SPLIT: "train"
+    MS_DATASET_SUBNAME: ""
+    PROMPT_PREFIX: ""
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFileList
+        FILE_KEYS: ['img_path', 'src_path']
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'image', 'condition_cat' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'condition_cat', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 0
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 50
+    -
+      NAME: CheckpointHook
+      INTERVAL: 1000
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "Convert to an edge map#;#cache/datasets/hed_pair/images/src_001.jpeg" ]
+    IMAGE_SIZE: [ 512, 512 ]
+    FIELDS: [ "prompt", "src_path" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: LoadImageFromFileList
+        FILE_KEYS: [ 'src_path' ]
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'condition_cat' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'condition_cat', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'

scepter/methods/examples/classification/example.yaml

@@ -11,7 +11,7 @@ SOLVER:
   # NUM_FOLDS DESCRIPTION: Num folds for training. TYPE: int default: 0
   NUM_FOLDS: 1
   # WORK_DIR DESCRIPTION: Save dir of the training log or model. TYPE: str default: ''
-  WORK_DIR: ./exp12/
+  WORK_DIR: ./cache/save_data/example/
   LOG_FILE: std_log.txt
   # EVAL_INTERVAL DESCRIPTION: Eval the model interval. TYPE: int default: 1
   EVAL_INTERVAL: 1
@@ -102,7 +102,7 @@ SOLVER:
     # DATASET DESCRIPTION: the public dataset name TYPE: str default: 'cifar10'
     DATASET: cifar10
     # DATA_ROOT DESCRIPTION: the download data save path TYPE: str default: ''
-    DATA_ROOT: ./local_data/cifar10
+    DATA_ROOT: ./cache/cache_data/cifar10
     # MODE DESCRIPTION: test TYPE: str default: test
     MODE: test
     # PIN_MEMORY DESCRIPTION: pin_memory for data loader TYPE: bool default: False

scepter/methods/examples/generation/dit_pixart_alpha_1024_lora.yaml

@@ -0,0 +1,223 @@
+ENV:
+  BACKEND: nccl
+#
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 1000
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 100
+  RESCALE_LR: False
+  #
+  WORK_DIR: ./cache/save_data/dit_pixart_alpha_1024_lora
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  FREEZE:
+  #
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 128
+      LORA_ALPHA: 128
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "model.*(.q|.k|.v|.o|mlp.fc1|mlp.fc2)$"
+  #
+  MODEL:
+    NAME: LatentDiffusionPixart
+    PARAMETERIZATION: eps
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 0.18215
+    SIZE_FACTOR: 8
+    DECODER_BIAS: 0.5
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "linear"
+      "BETA_MIN": 0.0001
+      "BETA_MAX": 0.02
+    USE_EMA: False
+    LOAD_REFINER: False
+    #
+    DIFFUSION_MODEL:
+      NAME: PixArt
+      PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@PixArt-XL-2-1024-MS.pth
+      INPUT_SIZE: 128
+      PATCH_SIZE: 2
+      IN_CHANNELS: 4
+      HIDDEN_SIZE: 1152
+      DEPTH: 28
+      NUM_HEADS: 16
+      MLP_RATIO: 4.0
+      CLASS_DROPOUT_PROB: 0.1
+      PRED_SIGMA: True
+      DROP_PATH: 0.0
+      WINDOW_DIZE: 0
+      USE_REL_POS: False
+      CAPTION_CHANNELS: 4096
+      LEWEI_SCALE: 2
+      MODEL_MAX_LENGTH: 120
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-2-base@512-base-ema.safetensors
+      EMBED_DIM: 4
+      IGNORE_KEYS: [ ]
+      BATCH_SIZE: 1
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+      TOKENIZER_PATH: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+      LENGTH: 120
+      CLEAN: heavy
+      USE_GRAD: False
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 20
+    SEED: 2024
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+    DISCRETIZATION: trailing
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 0.0001
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a boy wearing a jacket", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 0
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'

scepter/methods/examples/generation/dit_sd3_1024.yaml

@@ -0,0 +1,233 @@
+ENV:
+  BACKEND: nccl
+#
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 500
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 50
+  RESCALE_LR: False
+  #
+  WORK_DIR: ./cache/save_data/dit_sd3_1024
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    - NAME: "ModelscopeFs"
+      TEMP_DIR: ./cache/cache_data
+  #
+  MODEL:
+    NAME: LatentDiffusionSD3
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 1.5305
+    SHIFT_FACTOR: 0.0609
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "shifted"
+      "SHIFT": 3
+    USE_EMA: False
+    T_WEIGHT: uniform
+    #
+    DIFFUSION_MODEL:
+      NAME: MMDiT
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      IGNORE_KEYS: '^first_stage_model.'
+      IN_CHANNELS: 16
+      PATCH_SIZE: 2
+      OUT_CHANNELS: 16
+      DEPTH: 24
+      INPUT_SIZE:
+      ADM_IN_CHANNELS: 2048
+      CONTEXT_EMBEDDER_CONFIG: { 'target': 'torch.nn.Linear', 'params': { 'in_features': 4096, 'out_features': 1536 } }
+      NUM_PATCHES: 36864
+      POS_EMBED_MAX_SIZE: 192
+      POS_EMBED_SCALING_FACTOR:
+      USE_CHECKPOINT: True
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      EMBED_DIM: 16
+      IGNORE_KEYS: '^model.diffusion_model.'
+      BATCH_SIZE: 1
+      USE_CONV: False
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: SD3TextEmbedder
+      P_ZERO: 0.0
+      CLIP_L:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      CLIP_G:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_2
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_2
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      T5_XXL:
+        NAME: T5EmbedderHF
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_3
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_3
+        LENGTH: 256
+        CLEAN: whitespace
+        USE_GRAD: False
+        T5_DTYPE: float16
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: euler
+    SAMPLE_STEPS: 28
+    SEED: 1749023094
+    GUIDE_SCALE: 5.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 1e-5
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a cat holds a blackboard that writes \"hello world\"", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 10000
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 50
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'

scepter/methods/examples/generation/dit_sd3_1024_lora.yaml

@@ -0,0 +1,241 @@
+ENV:
+  BACKEND: nccl
+#
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 500
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 50
+  RESCALE_LR: False
+  #
+  WORK_DIR: ./cache/save_data/dit_sd3_1024_lora
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    - NAME: "ModelscopeFs"
+      TEMP_DIR: ./cache/cache_data
+  #
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 128
+      LORA_ALPHA: 128
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "model.*(.attn.qkv|.attn.proj|mlp.fc1|mlp.fc2)$"
+  #
+  MODEL:
+    NAME: LatentDiffusionSD3
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 1.5305
+    SHIFT_FACTOR: 0.0609
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "shifted"
+      "SHIFT": 3
+    USE_EMA: False
+    T_WEIGHT: uniform
+    #
+    DIFFUSION_MODEL:
+      NAME: MMDiT
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      IGNORE_KEYS: '^first_stage_model.'
+      IN_CHANNELS: 16
+      PATCH_SIZE: 2
+      OUT_CHANNELS: 16
+      DEPTH: 24
+      INPUT_SIZE:
+      ADM_IN_CHANNELS: 2048
+      CONTEXT_EMBEDDER_CONFIG: { 'target': 'torch.nn.Linear', 'params': { 'in_features': 4096, 'out_features': 1536 } }
+      NUM_PATCHES: 36864
+      POS_EMBED_MAX_SIZE: 192
+      POS_EMBED_SCALING_FACTOR:
+      USE_CHECKPOINT: True
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      EMBED_DIM: 16
+      IGNORE_KEYS: '^model.diffusion_model.'
+      BATCH_SIZE: 1
+      USE_CONV: False
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: SD3TextEmbedder
+      P_ZERO: 0.0
+      CLIP_L:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      CLIP_G:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_2
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_2
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      T5_XXL:
+        NAME: T5EmbedderHF
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_3
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_3
+        LENGTH: 256
+        CLEAN: whitespace
+        USE_GRAD: False
+        T5_DTYPE: float16
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: euler
+    SAMPLE_STEPS: 28
+    SEED: 1749023094
+    GUIDE_SCALE: 5.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 5e-5
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a cat holds a blackboard that writes \"hello world\"", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 10000
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 50
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'

scepter/methods/examples/generation/stable_diffusion_1.5_512.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd15_512_full
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   MODEL:
     NAME: LatentDiffusion
@@ -124,7 +125,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -190,7 +191,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/examples/generation/stable_diffusion_1.5_512_lora.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd15_512_lora
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   TUNER:
     -
       NAME: SwiftLoRA
@@ -132,7 +133,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -198,7 +199,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/examples/generation/stable_diffusion_1.5_512_textlora.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd15_512_textlora
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   TUNER:
     -
       NAME: SwiftLoRA
@@ -140,7 +141,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -206,7 +207,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/examples/generation/stable_diffusion_2.1_512.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd21_512_full
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   MODEL:
     NAME: LatentDiffusion
@@ -120,7 +121,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -186,7 +187,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/examples/generation/stable_diffusion_2.1_512_lora.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd21_512_lora
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -129,7 +130,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -195,7 +196,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/examples/generation/stable_diffusion_2.1_768.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd21_768_full
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   MODEL:
     NAME: LatentDiffusion
@@ -120,7 +121,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -186,7 +187,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/examples/generation/stable_diffusion_2.1_768_lora.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd21_768_lora
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -129,7 +130,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -195,7 +196,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/examples/generation/stable_diffusion_xl_1024.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_full
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   MODEL:
     NAME: LatentDiffusionXL
@@ -238,7 +239,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -306,7 +307,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       - NAME: Select

scepter/methods/examples/generation/stable_diffusion_xl_1024_lora.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_lora
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -247,7 +248,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -315,7 +316,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       - NAME: Select

scepter/methods/examples/generation/stable_diffusion_xl_1024_textlora.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_textlora
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -255,7 +256,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -323,7 +324,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       - NAME: Select

scepter/methods/scedit/ctr/sd15_512_sce_ctr_hed.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd15_512_sce_ctr_hed
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -127,7 +128,7 @@ SOLVER:
         DOWN_RATIO: 1.0
     CONTROL_ANNO:
       NAME: HedAnnotator
-      PRETRAINED_MODEL: ms://damo/scepter_scedit@annotator/ckpts/ControlNetHED.pth
+      PRETRAINED_MODEL: ms://iic/scepter_scedit@annotator/ckpts/ControlNetHED.pth
   #
   SAMPLE_ARGS:
     SAMPLER: ddim
@@ -141,7 +142,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/scedit/ctr/sd21_768_sce_ctr_canny.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd21_768_sce_ctr_canny
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -140,7 +141,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/scedit/ctr/sd21_768_sce_ctr_pose.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd21_768_sce_ctr_pose
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -125,8 +126,8 @@ SOLVER:
         DOWN_RATIO: 1.0
     CONTROL_ANNO:
       NAME: OpenposeAnnotator
-      BODY_MODEL_PATH: ms://damo/scepter_scedit@annotator/ckpts/body_pose_model.pth
-      HAND_MODEL_PATH: ms://damo/scepter_scedit@annotator/ckpts/hand_pose_model.pth
+      BODY_MODEL_PATH: ms://iic/scepter_scedit@annotator/ckpts/body_pose_model.pth
+      HAND_MODEL_PATH: ms://iic/scepter_scedit@annotator/ckpts/hand_pose_model.pth
   #
   SAMPLE_ARGS:
     SAMPLER: ddim
@@ -140,7 +141,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/scedit/ctr/sdxl_1024_sce_ctr_canny.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_sce_ctr_canny
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -254,7 +255,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/scedit/ctr/sdxl_1024_sce_ctr_color.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_sce_ctr_color
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -255,7 +256,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/scedit/ctr/sdxl_1024_sce_ctr_color_datatxt.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_sce_ctr_color_datatxt
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -255,7 +256,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/scedit/ctr/sdxl_1024_sce_ctr_depth.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_sce_ctr_depth
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -241,7 +242,7 @@ SOLVER:
         DOWN_RATIO: 1.0
     CONTROL_ANNO:
       NAME: MidasDetector
-      PRETRAINED_MODEL: ms://damo/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt
+      PRETRAINED_MODEL: ms://iic/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt
   #
   SAMPLE_ARGS:
     SAMPLER: ddim
@@ -255,7 +256,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/scedit/t2i/sd15_512_sce_t2i.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd15_512_sce_t2i
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -134,7 +135,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -200,7 +201,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/scedit/t2i/sd15_512_sce_t2i_swift.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd15_512_sce_t2i_swift
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -132,7 +133,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -198,7 +199,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/scedit/t2i/sd15_512_textsce_t2i_swift.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd15_512_textsce_t2i_swift
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -140,7 +141,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -206,7 +207,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/scedit/t2i/sd21_768_sce_t2i.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd21_768_sce_t2i
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -130,7 +131,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -196,7 +197,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/scedit/t2i/sd21_768_sce_t2i_swift.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sd21_768_sce_t2i_swift
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -128,7 +129,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -194,7 +195,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       -

scepter/methods/scedit/t2i/sdxl_1024_sce_t2i.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_sce_t2i
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -247,7 +248,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -315,7 +316,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       - NAME: Select

scepter/methods/scedit/t2i/sdxl_1024_sce_t2i_datatxt.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_sce_t2i_datatxt
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
     FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -247,7 +248,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/scedit/t2i/sdxl_1024_sce_t2i_swift.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_sce_t2i_swift
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -245,7 +246,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -313,7 +314,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       - NAME: Select

scepter/methods/scedit/t2i/sdxl_1024_textsce_t2i_swift.yaml

@@ -14,13 +14,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: 100
+  RESCALE_LR: False
   #
   WORK_DIR: ./cache/save_data/sdxl_1024_textsce_t2i_swift
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   TUNER:
     -
@@ -253,7 +254,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2
@@ -321,7 +322,7 @@ SOLVER:
     NUM_WORKERS: 4
     FILE_SYSTEM:
       NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
     #
     TRANSFORMS:
       - NAME: Select

scepter/methods/studio/extensions/controllers/official_controllers.yaml

@@ -5,59 +5,59 @@ CONTROLLERS:
     DESCRIPTION:
     BASE_MODEL: SD2.1
     TYPE: Canny
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/canny_control/
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/canny_control/
   - NAME: openpose
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD2.1
     TYPE: Openpose
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/pose_control/
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/pose_control/
   - NAME: color
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD2.1
     TYPE: Color
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/color_control/
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/color_control/
   - NAME: hed
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD2.1
     TYPE: Hed
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/hed_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/hed_control
   - NAME: depth
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD2.1
     TYPE: Midas
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/depth_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/depth_control
   # SD_XL1.0
   - NAME: canny
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD_XL1.0
     TYPE: Canny
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/canny_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/canny_control
   - NAME: color
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD_XL1.0
     TYPE: Color
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/color_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/color_control
   - NAME: depth
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD_XL1.0
     TYPE: Midas
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/depth_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/depth_control
   - NAME: hed
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD_XL1.0
     TYPE: Hed
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/hed_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/hed_control
   - NAME: openpose
     NAME_ZH:
     DESCRIPTION:
     BASE_MODEL: SD_XL1.0
     TYPE: Openpose
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/pose_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/pose_control

scepter/methods/studio/extensions/tuners/official_tuners.yaml

@@ -1,11 +1,20 @@
 TUNERS:
+  - NAME: Clay-Style-Editing
+    NAME_ZH: 黏土风
+    SOURCE: scepter
+    DESCRIPTION: None
+    BASE_MODEL: EDIT
+    MODEL_PATH: ms://iic/stylebooth@tuners/clay_style_edit/
+    IMAGE_PATH: ms://iic/stylebooth@tuners/clay_style_edit/image.jpg
+    TUNER_TYPE: LORA
+    PROMPT_EXAMPLE: Convert this image into clay style
   - NAME: Azure-Dragon
     NAME_ZH: 青龙
     SOURCE: scepter
     DESCRIPTION: None
     BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/azure_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/azure_dragon/xl_azure_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/azure_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/azure_dragon/xl_azure_dragon.png
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: Azure Dragon, 8K, high quality,Ultra High Detail.One of the Four Divine Creatures in Charge of Water.
   - NAME: Gold-Dragon
@@ -13,8 +22,8 @@ TUNERS:
     SOURCE: scepter
     DESCRIPTION: None
     BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/gold_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/gold_dragon/xl_gold_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/gold_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/gold_dragon/xl_gold_dragon.png
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: Chinese Gold Dragon in the clouds. Translucent Texture. Zbrush.  Fuzzy Art. Exquisite Craftsmanship. 3D. 8K. Ultra High Detail
   - NAME: SpringFestival-Dragon
@@ -22,8 +31,8 @@ TUNERS:
     SOURCE: scepter
     DESCRIPTION: None
     BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/spring_festival_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/spring_festival_dragon/xl_spring_festival_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/spring_festival_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/spring_festival_dragon/xl_spring_festival_dragon.png
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: Chinese dragon. Spring Festival.Festive.Street.Lanterns.32K.High quality.expressive, dramatic, dreamlike and mysterious, Surrealism
   - NAME: Red-Dragon
@@ -31,8 +40,8 @@ TUNERS:
     SOURCE: scepter
     DESCRIPTION: None
     BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/red_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/red_dragon/xl_red_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/red_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/red_dragon/xl_red_dragon.png
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: Traditional Red Dragon of China. Low Water Level. Studio Ghibli Style. Mural Illustration. White Background. High Detail
   - NAME: ChinesePunk-Dragon
@@ -40,8 +49,8 @@ TUNERS:
     SOURCE: scepter
     DESCRIPTION: None
     BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/chinese_punk_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/chinese_punk_dragon/xl_chinese_punk_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/chinese_punk_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/chinese_punk_dragon/xl_chinese_punk_dragon.png
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: uhd Image,Dragon,Chinese Dragon, Dunhuang Mural Style, Traditional Maritime Art Style
   - NAME: Cute-Dragon
@@ -49,8 +58,8 @@ TUNERS:
     SOURCE: scepter
     DESCRIPTION: None
     BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/cute_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/cute_dragon/xl_kawaii_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/cute_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/cute_dragon/xl_kawaii_dragon.png
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: China Kawaii Dragon. Contest Winner. Minimalist Illustration. White Background. Flat Style. Digital Painting Style. Red. 32k uhd. Fun Comics. Fuzzy Art. Bold. Comic-Inspired Characters
   - NAME: Dragon-Baby
@@ -58,8 +67,8 @@ TUNERS:
     SOURCE: scepter
     DESCRIPTION: None
     BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/baby_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/baby_dragon/xl_baby_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/baby_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/baby_dragon/xl_baby_dragon.png
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: Warm Colors, Soft,Chinese Dragon Baby, Felt Style,Dragon Baby, Best Quality, 3D Doll, Macaron Tones, Glittering Big Eyes, Winter,Dragon
   - NAME: Sloppy-Dragon
@@ -67,8 +76,8 @@ TUNERS:
     SOURCE: scepter
     DESCRIPTION: None
     BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sloppy_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sloppy_dragon/xl_sloppy_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sloppy_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sloppy_dragon/xl_sloppy_dragon.png
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: Messy Chinese Dragon,Cute, Wu Guanzhong, Rough
   -
@@ -77,8 +86,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/894f40ed44b37c3372e6a22b8ae577a4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Caricature
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/894f40ed44b37c3372e6a22b8ae577a4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Caricature
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -87,8 +96,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/894f40ed44b37c3372e6a22b8ae577a4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Caricature
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/894f40ed44b37c3372e6a22b8ae577a4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Caricature
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -97,8 +106,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/894f40ed44b37c3372e6a22b8ae577a4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Caricature
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/894f40ed44b37c3372e6a22b8ae577a4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Caricature
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -107,8 +116,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/80e5b4075c572c04cbb4e48c37b8366b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/ColorFieldPainting
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/80e5b4075c572c04cbb4e48c37b8366b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/ColorFieldPainting
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -117,8 +126,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/80e5b4075c572c04cbb4e48c37b8366b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/ColorFieldPainting
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/80e5b4075c572c04cbb4e48c37b8366b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/ColorFieldPainting
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -127,8 +136,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/80e5b4075c572c04cbb4e48c37b8366b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/ColorFieldPainting
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/80e5b4075c572c04cbb4e48c37b8366b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/ColorFieldPainting
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -137,8 +146,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/9ae235d7f1a7c2a4edab52a5e9f9cbae.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/ColoredPencilArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/9ae235d7f1a7c2a4edab52a5e9f9cbae.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/ColoredPencilArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -147,8 +156,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/9ae235d7f1a7c2a4edab52a5e9f9cbae.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/ColoredPencilArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/9ae235d7f1a7c2a4edab52a5e9f9cbae.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/ColoredPencilArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -157,8 +166,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/9ae235d7f1a7c2a4edab52a5e9f9cbae.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/ColoredPencilArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/9ae235d7f1a7c2a4edab52a5e9f9cbae.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/ColoredPencilArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -167,8 +176,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/3da915da2f5cedaf243e57e08163f35b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/DarkMoodyAtmosphere
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/3da915da2f5cedaf243e57e08163f35b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/DarkMoodyAtmosphere
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -177,8 +186,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/3da915da2f5cedaf243e57e08163f35b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/DarkMoodyAtmosphere
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/3da915da2f5cedaf243e57e08163f35b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/DarkMoodyAtmosphere
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -187,8 +196,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/3da915da2f5cedaf243e57e08163f35b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/DarkMoodyAtmosphere
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/3da915da2f5cedaf243e57e08163f35b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/DarkMoodyAtmosphere
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -197,8 +206,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/69fd81f5983107acc3d334af62915851.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/DrippingPaintSplatterArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/69fd81f5983107acc3d334af62915851.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/DrippingPaintSplatterArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -207,8 +216,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/69fd81f5983107acc3d334af62915851.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/DrippingPaintSplatterArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/69fd81f5983107acc3d334af62915851.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/DrippingPaintSplatterArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -217,8 +226,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/69fd81f5983107acc3d334af62915851.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/DrippingPaintSplatterArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/69fd81f5983107acc3d334af62915851.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/DrippingPaintSplatterArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -227,8 +236,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/f152edb4b3ca6248758b48115258ddfa.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/FadedPolaroidPhoto
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/f152edb4b3ca6248758b48115258ddfa.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/FadedPolaroidPhoto
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -237,8 +246,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/f152edb4b3ca6248758b48115258ddfa.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/FadedPolaroidPhoto
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/f152edb4b3ca6248758b48115258ddfa.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/FadedPolaroidPhoto
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -247,8 +256,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/f152edb4b3ca6248758b48115258ddfa.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/FadedPolaroidPhoto
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/f152edb4b3ca6248758b48115258ddfa.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/FadedPolaroidPhoto
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -257,8 +266,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/940cfd34155634cf051e1b2942cca426.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Flat2DArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/940cfd34155634cf051e1b2942cca426.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Flat2DArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -267,8 +276,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/940cfd34155634cf051e1b2942cca426.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Flat2DArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/940cfd34155634cf051e1b2942cca426.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Flat2DArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -277,8 +286,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/940cfd34155634cf051e1b2942cca426.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Flat2DArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/940cfd34155634cf051e1b2942cca426.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Flat2DArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -287,8 +296,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/57b751b11564cb22cd49ef21f2004a5f.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/GraffitiArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/57b751b11564cb22cd49ef21f2004a5f.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/GraffitiArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -297,8 +306,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/57b751b11564cb22cd49ef21f2004a5f.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/GraffitiArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/57b751b11564cb22cd49ef21f2004a5f.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/GraffitiArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -307,8 +316,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/57b751b11564cb22cd49ef21f2004a5f.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/GraffitiArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/57b751b11564cb22cd49ef21f2004a5f.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/GraffitiArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -317,8 +326,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/0312b673dc6858a9864d7f45f0c5c1fc.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Impressionism
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/0312b673dc6858a9864d7f45f0c5c1fc.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Impressionism
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -327,8 +336,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/0312b673dc6858a9864d7f45f0c5c1fc.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Impressionism
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/0312b673dc6858a9864d7f45f0c5c1fc.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Impressionism
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -337,8 +346,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/0312b673dc6858a9864d7f45f0c5c1fc.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Impressionism
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/0312b673dc6858a9864d7f45f0c5c1fc.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Impressionism
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -347,8 +356,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/9aa040b0c60d289da9610c91ad9b7c7e.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/LogoDesign
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/9aa040b0c60d289da9610c91ad9b7c7e.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/LogoDesign
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -357,8 +366,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/9aa040b0c60d289da9610c91ad9b7c7e.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/LogoDesign
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/9aa040b0c60d289da9610c91ad9b7c7e.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/LogoDesign
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -367,8 +376,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/9aa040b0c60d289da9610c91ad9b7c7e.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/LogoDesign
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/9aa040b0c60d289da9610c91ad9b7c7e.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/LogoDesign
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -377,8 +386,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/a9056e1eac85e5e4fe96a93917d4cce4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/PencilSketchDrawing
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/a9056e1eac85e5e4fe96a93917d4cce4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/PencilSketchDrawing
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -387,8 +396,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/a9056e1eac85e5e4fe96a93917d4cce4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/PencilSketchDrawing
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/a9056e1eac85e5e4fe96a93917d4cce4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/PencilSketchDrawing
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -397,8 +406,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/a9056e1eac85e5e4fe96a93917d4cce4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/PencilSketchDrawing
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/a9056e1eac85e5e4fe96a93917d4cce4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/PencilSketchDrawing
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -407,8 +416,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/568777f447fc02510b618152726d5002.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/SilhouetteArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/568777f447fc02510b618152726d5002.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/SilhouetteArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -417,8 +426,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/568777f447fc02510b618152726d5002.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/SilhouetteArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/568777f447fc02510b618152726d5002.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/SilhouetteArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -427,8 +436,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/568777f447fc02510b618152726d5002.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/SilhouetteArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/568777f447fc02510b618152726d5002.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/SilhouetteArt
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -437,8 +446,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/07d7b27cd73f2d43684003563511c15b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Steampunk2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/07d7b27cd73f2d43684003563511c15b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Steampunk2
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -447,8 +456,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/07d7b27cd73f2d43684003563511c15b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Steampunk2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/07d7b27cd73f2d43684003563511c15b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Steampunk2
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -457,8 +466,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/07d7b27cd73f2d43684003563511c15b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Steampunk2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/07d7b27cd73f2d43684003563511c15b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Steampunk2
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -467,8 +476,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/2d1e9867058db2c57f2fe47530de3243.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/StickerDesigns
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/2d1e9867058db2c57f2fe47530de3243.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/StickerDesigns
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -477,8 +486,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/2d1e9867058db2c57f2fe47530de3243.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/StickerDesigns
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/2d1e9867058db2c57f2fe47530de3243.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/StickerDesigns
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -487,8 +496,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/2d1e9867058db2c57f2fe47530de3243.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/StickerDesigns
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/2d1e9867058db2c57f2fe47530de3243.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/StickerDesigns
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -497,8 +506,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/8859d532ae5901cc8457d6118fb9b7da.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Watercolor2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/8859d532ae5901cc8457d6118fb9b7da.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Watercolor2
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -507,8 +516,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/8859d532ae5901cc8457d6118fb9b7da.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Watercolor2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/8859d532ae5901cc8457d6118fb9b7da.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Watercolor2
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -517,8 +526,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: diva
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/8859d532ae5901cc8457d6118fb9b7da.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Watercolor2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/8859d532ae5901cc8457d6118fb9b7da.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Watercolor2
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -527,8 +536,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/5895d78cf58c1ca05178991f37cc48ff.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/mre-elemental-art
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/5895d78cf58c1ca05178991f37cc48ff.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/mre-elemental-art
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -537,8 +546,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/5895d78cf58c1ca05178991f37cc48ff.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/mre-elemental-art
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/5895d78cf58c1ca05178991f37cc48ff.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/mre-elemental-art
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -547,8 +556,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/5895d78cf58c1ca05178991f37cc48ff.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/mre-elemental-art
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/5895d78cf58c1ca05178991f37cc48ff.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/mre-elemental-art
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -557,8 +566,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/a08149bc8e50f6bc65c0010d4cd416f8.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/mre-anime
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/a08149bc8e50f6bc65c0010d4cd416f8.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/mre-anime
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -567,8 +576,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/a08149bc8e50f6bc65c0010d4cd416f8.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/mre-anime
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/a08149bc8e50f6bc65c0010d4cd416f8.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/mre-anime
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -577,8 +586,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/a08149bc8e50f6bc65c0010d4cd416f8.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/mre-anime
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/a08149bc8e50f6bc65c0010d4cd416f8.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/mre-anime
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -587,8 +596,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/48c65cebf1fa4284d7b8feb619412e65.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/mre-comic
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/48c65cebf1fa4284d7b8feb619412e65.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/mre-comic
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -597,8 +606,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/48c65cebf1fa4284d7b8feb619412e65.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/mre-comic
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/48c65cebf1fa4284d7b8feb619412e65.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/mre-comic
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -607,8 +616,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: mre
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/48c65cebf1fa4284d7b8feb619412e65.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/mre-comic
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/48c65cebf1fa4284d7b8feb619412e65.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/mre-comic
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -617,8 +626,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/8fc51113f725f27326c4398a7457cd6d.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-craftclay
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/8fc51113f725f27326c4398a7457cd6d.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-craftclay
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -627,8 +636,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/8fc51113f725f27326c4398a7457cd6d.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-craftclay
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/8fc51113f725f27326c4398a7457cd6d.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-craftclay
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -637,8 +646,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/8fc51113f725f27326c4398a7457cd6d.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-craftclay
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/8fc51113f725f27326c4398a7457cd6d.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-craftclay
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -647,8 +656,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/a6f8d92afcd5803dfb2ebecbc92091b6.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-fantasyart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/a6f8d92afcd5803dfb2ebecbc92091b6.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-fantasyart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -657,8 +666,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/a6f8d92afcd5803dfb2ebecbc92091b6.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-fantasyart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/a6f8d92afcd5803dfb2ebecbc92091b6.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-fantasyart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -667,8 +676,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/a6f8d92afcd5803dfb2ebecbc92091b6.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-fantasyart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/a6f8d92afcd5803dfb2ebecbc92091b6.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-fantasyart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -677,8 +686,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/034a51b0dd34b018be8859bf45b4f7ed.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-lineart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/034a51b0dd34b018be8859bf45b4f7ed.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-lineart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -687,8 +696,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/034a51b0dd34b018be8859bf45b4f7ed.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-lineart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/034a51b0dd34b018be8859bf45b4f7ed.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-lineart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -697,8 +706,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/034a51b0dd34b018be8859bf45b4f7ed.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-lineart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/034a51b0dd34b018be8859bf45b4f7ed.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-lineart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -707,8 +716,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/7e9ed25bb34008beb5f417df63c4b2fe.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-neonpunk
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/7e9ed25bb34008beb5f417df63c4b2fe.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-neonpunk
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -717,8 +726,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/7e9ed25bb34008beb5f417df63c4b2fe.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-neonpunk
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/7e9ed25bb34008beb5f417df63c4b2fe.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-neonpunk
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -727,8 +736,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/7e9ed25bb34008beb5f417df63c4b2fe.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-neonpunk
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/7e9ed25bb34008beb5f417df63c4b2fe.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-neonpunk
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -737,8 +746,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/924f46a8f276011a0953d7988e90ee25.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-origami
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/924f46a8f276011a0953d7988e90ee25.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-origami
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -747,8 +756,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/924f46a8f276011a0953d7988e90ee25.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-origami
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/924f46a8f276011a0953d7988e90ee25.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-origami
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -757,8 +766,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/924f46a8f276011a0953d7988e90ee25.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-origami
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/924f46a8f276011a0953d7988e90ee25.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-origami
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -767,8 +776,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/a5ab89c0960be8c1216e65c98d92ae4a.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-pixelart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/a5ab89c0960be8c1216e65c98d92ae4a.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-pixelart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -777,8 +786,8 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/a5ab89c0960be8c1216e65c98d92ae4a.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-pixelart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/a5ab89c0960be8c1216e65c98d92ae4a.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-pixelart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket
   -
@@ -787,7 +796,7 @@ TUNERS:
     DESCRIPTION:
     SOURCE: sai
     BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/a5ab89c0960be8c1216e65c98d92ae4a.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-pixelart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/a5ab89c0960be8c1216e65c98d92ae4a.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-pixelart
     TUNER_TYPE: SwiftSCE
     PROMPT_EXAMPLE: a boy wearing green jacket

scepter/methods/studio/home/home.yaml

@@ -10,7 +10,7 @@ DESC_INFO:
     <table align="center">
       <tr>
       <td>
-        <img src="https://modelscope.cn/api/v1/models/damo/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_studio_banner.jpg">
+        <img src="https://modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_studio_banner.jpg">
         <h3><center>SCEPTER Studio是基于开源基模型和自研微调编辑算法构建的生成定制和编辑工具箱，提供围绕生成、微调、编辑、数据处理等一系列的工具和插件。</center><h3>
       </td>
       </tr>
@@ -22,7 +22,7 @@ DESC_INFO:
     <table align="center">
       <tr>
       <td>
-        <img src="https://modelscope.cn/api/v1/models/damo/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_studio_banner.jpg">
+        <img src="https://modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_studio_banner.jpg">
         <h3><center>SCEPTER Studio is a customized generation and editing toolkit built on the open-source base models and proprietary fine-tuning editing algorithms, offering a range of tools and plugins centered around generation, fine-tuning, editing, and data processing.</center><h3>
       </td>
       </tr>

scepter/methods/studio/inference/dit/pixart_alpha_pro.yaml

@@ -0,0 +1,120 @@
+NAME: PIXART_ALPHA
+IS_DEFAULT: False
+DEFAULT_PARAS:
+  PARAS:
+    RESOLUTIONS: [[1024, 1024]]
+  INPUT:
+    IMAGE:
+    ORIGINAL_SIZE_AS_TUPLE: [1024, 1024]
+    TARGET_SIZE_AS_TUPLE: [1024, 1024]
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    PROMPT_PREFIX: ""
+    SAMPLE: ddim
+    SAMPLE_STEPS: 20
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+    DISCRETIZATION: trailing
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: float32
+          INPUT: ["IMAGE"]
+        -
+          NAME: decode
+          DTYPE: float32
+          INPUT: ["LATENT"]
+      PARAS:
+        SCALE_FACTOR: 0.18215
+        SIZE_FACTOR: 8
+    DIFFUSION_MODEL:
+      FUNCTION:
+        -
+          NAME: forward
+          DTYPE: float16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE", "GUIDE_RESCALE", "DISCRETIZATION"]
+    COND_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: float32
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  PRETRAINED_MODEL:
+  DECODER_BIAS: 0.5
+  SCHEDULE:
+    PARAMETERIZATION: "eps"
+    TIMESTEPS: 1000
+    ZERO_TERMINAL_SNR: False
+    SCHEDULE_ARGS:
+      "NAME": "linear"
+      "BETA_MIN": 0.0001
+      "BETA_MAX": 0.02
+  #
+  DIFFUSION_MODEL:
+    NAME: PixArt
+    PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@PixArt-XL-2-1024-MS.pth
+    INPUT_SIZE: 128
+    PATCH_SIZE: 2
+    IN_CHANNELS: 4
+    HIDDEN_SIZE: 1152
+    DEPTH: 28
+    NUM_HEADS: 16
+    MLP_RATIO: 4.0
+    CLASS_DROPOUT_PROB: 0.1
+    PRED_SIGMA: True
+    DROP_PATH: 0.0
+    WINDOW_DIZE: 0
+    USE_REL_POS: False
+    CAPTION_CHANNELS: 4096
+    LEWEI_SCALE: 2
+    MODEL_MAX_LENGTH: 120
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKL
+    PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-2-base@512-base-ema.safetensors
+    EMBED_DIM: 4
+    IGNORE_KEYS: [ ]
+    BATCH_SIZE: 1
+    #
+    ENCODER:
+      NAME: Encoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    NAME: T5EmbedderHF
+    PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+    TOKENIZER_PATH: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+    LENGTH: 120
+    CLEAN: heavy
+    USE_GRAD: False

scepter/methods/studio/inference/dit/sd3_pro.yaml

@@ -0,0 +1,148 @@
+NAME: SD3
+IS_DEFAULT: False
+DEFAULT_PARAS:
+  PARAS:
+    RESOLUTIONS: [[1024, 1024]]
+  INPUT:
+    IMAGE:
+    ORIGINAL_SIZE_AS_TUPLE: [1024, 1024]
+    TARGET_SIZE_AS_TUPLE: [1024, 1024]
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    PROMPT_PREFIX: ""
+    SAMPLE: euler
+    SAMPLE_STEPS: 28
+    GUIDE_SCALE: 5.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: float32
+          INPUT: ["IMAGE"]
+        -
+          NAME: decode
+          DTYPE: float32
+          INPUT: ["LATENT"]
+      PARAS:
+        SCALE_FACTOR: 1.5305
+        SHIFT_FACTOR: 0.0609
+        SIZE_FACTOR: 8
+    DIFFUSION_MODEL:
+      FUNCTION:
+        -
+          NAME: forward
+          DTYPE: float16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE", "GUIDE_RESCALE", "DISCRETIZATION"]
+    COND_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: float32
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  PRETRAINED_MODEL:
+  SCHEDULE:
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 1.5305
+    SHIFT_FACTOR: 0.0609
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "shifted"
+      "SHIFT": 3
+    T_WEIGHT: uniform
+  #
+  DIFFUSION_MODEL:
+    NAME: MMDiT
+    PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+    IGNORE_KEYS: '^first_stage_model.'
+    IN_CHANNELS: 16
+    PATCH_SIZE: 2
+    OUT_CHANNELS: 16
+    DEPTH: 24
+    INPUT_SIZE:
+    ADM_IN_CHANNELS: 2048
+    CONTEXT_EMBEDDER_CONFIG: { 'target': 'torch.nn.Linear', 'params': { 'in_features': 4096, 'out_features': 1536 } }
+    NUM_PATCHES: 36864
+    POS_EMBED_MAX_SIZE: 192
+    POS_EMBED_SCALING_FACTOR:
+    USE_CHECKPOINT: True
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKL
+    PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+    EMBED_DIM: 16
+    IGNORE_KEYS: '^model.diffusion_model.'
+    BATCH_SIZE: 1
+    USE_CONV: False
+    #
+    ENCODER:
+      NAME: Encoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 16
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 16
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    NAME: SD3TextEmbedder
+    P_ZERO: 0.0
+    CLIP_L:
+      NAME: FrozenCLIPEmbedder2
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder
+      TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer
+      MAX_LENGTH: 77
+      FREEZE: True
+      LAYER: penultimate
+      RETURN_POOLED: True
+      USE_FINAL_LAYER_NORM: False
+      IS_TRAINABLE: False
+    CLIP_G:
+      NAME: FrozenCLIPEmbedder2
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_2
+      TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_2
+      MAX_LENGTH: 77
+      FREEZE: True
+      LAYER: penultimate
+      RETURN_POOLED: True
+      USE_FINAL_LAYER_NORM: False
+      IS_TRAINABLE: False
+    T5_XXL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_3
+      TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_3
+      LENGTH: 256
+      CLEAN: whitespace
+      USE_GRAD: False
+      T5_DTYPE: float16

scepter/methods/studio/inference/edit/stylebooth_tb_pro.yaml

@@ -2,7 +2,7 @@ NAME: EDIT
 IS_DEFAULT: False
 DEFAULT_PARAS:
   PARAS:
-    RESOLUTIONS: [[1024, 1024]]
+    RESOLUTIONS: [[512, 512], [1024, 1024]]
   INPUT:
     IMAGE:
     PROMPT: ""
@@ -49,7 +49,7 @@ DEFAULT_PARAS:
           INPUT: ["PROMPT", "NEGATIVE_PROMPT"]
 
 MODEL:
-  PRETRAINED_MODEL: ms://damo/stylebooth@models/stylebooth-tb-5000-0.bin
+  PRETRAINED_MODEL: ms://iic/stylebooth@models/stylebooth-tb-5000-0.bin
   SCHEDULE:
     PARAMETERIZATION: "eps"
     TIMESTEPS: 1000

scepter/methods/studio/inference/inference.yaml

@@ -63,7 +63,8 @@ DIFFUSION_PARAS:
     MAX: 1.0
     DEFAULT: 0.15
   RESOLUTIONS:
-    VALUES: [[704, 1408], [704, 1344], [768, 1344],
+    VALUES: [ [512, 512], [768, 768],
+              [704, 1408], [704, 1344], [768, 1344],
              [720, 1280],
              [768, 1280], [832, 1216], [832, 1152],
              [896, 1152], [896, 1088], [960, 1088],
@@ -87,18 +88,18 @@ CONTROLABLE_ANNOTATORS:
     IS_DEFAULT: True
   -
     NAME: "HedAnnotator"
-    PRETRAINED_MODEL: "ms://damo/scepter_scedit@annotator/ckpts/ControlNetHED.pth"
+    PRETRAINED_MODEL: "ms://iic/scepter_scedit@annotator/ckpts/ControlNetHED.pth"
     TYPE: Hed
     IS_DEFAULT: False
   -
     NAME: "OpenposeAnnotator"
-    BODY_MODEL_PATH: "ms://damo/scepter_scedit@annotator/ckpts/body_pose_model.pth"
-    HAND_MODEL_PATH: "ms://damo/scepter_scedit@annotator/ckpts/hand_pose_model.pth"
+    BODY_MODEL_PATH: "ms://iic/scepter_scedit@annotator/ckpts/body_pose_model.pth"
+    HAND_MODEL_PATH: "ms://iic/scepter_scedit@annotator/ckpts/hand_pose_model.pth"
     TYPE: Openpose
     IS_DEFAULT: False
   -
     NAME: "MidasDetector"
-    PRETRAINED_MODEL: "ms://damo/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt"
+    PRETRAINED_MODEL: "ms://iic/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt"
     TYPE: Midas
     IS_DEFAULT: False
   -

scepter/methods/studio/inference/largen/largen_pro.yaml

@@ -68,7 +68,7 @@ DEFAULT_PARAS:
           INPUT: ["ORIGINAL_SIZE_AS_TUPLE", "AESTHETIC_SCORE", "NEGATIVE_AESTHETIC_SCORE", "CROP_COORDS_TOP_LEFT", "PROMPT", "NEGATIVE_PROMPT"]
 
 MODEL:
-  PRETRAINED_MODEL: ms://damo/LARGEN@models/largen_ckpt_s22k.pth
+  PRETRAINED_MODEL: ms://iic/LARGEN@models/largen_ckpt_s22k.pth
   # SCHEDULE_ARGS DESCRIPTION:  TYPE:  default: ''
   SCHEDULE:
     PARAMETERIZATION: "eps"
@@ -245,8 +245,8 @@ MODEL:
         LEGACY_UCG_VALUE:
       -
         NAME: IPAdapterPlusEmbedder
-        CLIP_DIR: ms://damo/LARGEN@models/clip_encoder/
-        PRETRAINED_MODEL: ms://damo/LARGEN@models/ip-adapter-plus_sdxl_vit-h.bin
+        CLIP_DIR: ms://iic/LARGEN@models/clip_encoder/
+        PRETRAINED_MODEL: ms://iic/LARGEN@models/ip-adapter-plus_sdxl_vit-h.bin
         INPUT_KEYS: [ "ref_ip", "ref_detail" ]
         IN_DIM: 1280
         HEADS: 20

scepter/methods/studio/scepter_ui.yaml

@@ -48,11 +48,11 @@ BANNER: |
       </div>
       <div class="qr-codes">
           <div class="qr-code-container">
-              <img src="https://modelscope.cn/api/v1/models/damo/scepter/repo?Revision=master&FilePath=assets/scepter_studio/ms_scepter_studio_qr.png" alt="ms_scepter_studio_qr">
+              <img src="https://modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets/scepter_studio/ms_scepter_studio_qr.png" alt="ms_scepter_studio_qr">
               <div class="caption"><a href="https://www.modelscope.cn/studios/iic/scepter_studio">Modelscope Studio</a></div>
           </div>
           <div class="qr-code-container">
-              <img src="https://modelscope.cn/api/v1/models/damo/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_github_qr.png" alt="scepter_github_qr">
+              <img src="https://modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_github_qr.png" alt="scepter_github_qr">
               <div class="caption"><a href="https://github.com/modelscope/scepter">Github</a></div>
           </div>
       </div>

scepter/methods/studio/self_train/dit/pixart_alpha_pro.yaml

@@ -0,0 +1,264 @@
+ENV:
+  BACKEND: nccl
+META:
+  VERSION: 'PIXART_ALPHA'
+  DESCRIPTION: "PIXART ALPHA"
+  IS_DEFAULT: False
+  IS_SHARE: True
+  INFERENCE_PARAS:
+    INFERENCE_BATCH_SIZE: 1
+    INFERENCE_PREFIX: ""
+    DEFAULT_SAMPLER: "ddim"
+    DEFAULT_SAMPLE_STEPS: 20
+    INFERENCE_N_PROMPT: ""
+    RESOLUTION: [1024, 1024]
+  PARAS:
+    -
+      TRAIN_BATCH_SIZE: 2
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [1024, 1024]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 0.0001
+      IS_DEFAULT: False
+      TUNER: FULL
+    -
+      TRAIN_BATCH_SIZE: 2
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [1024, 1024]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 0.0001
+      IS_DEFAULT: False
+      TUNER: LORA
+  #
+  TUNERS:
+    LORA:
+      -
+        NAME: SwiftLoRA
+        R: 256
+        LORA_ALPHA: 256
+        LORA_DROPOUT: 0.0
+        BIAS: "none"
+        TARGET_MODULES: "model.*(.q|.k|.v|.o|mlp.fc1|mlp.fc2)$"
+#
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 1000
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: -1
+  RESCALE_LR: False
+  #
+  WORK_DIR: cache/scepter_ui/self_train/dit/pixart_alpha_pro
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  FREEZE:
+  #
+  TUNER:
+  #
+  MODEL:
+    NAME: LatentDiffusionPixart
+    PARAMETERIZATION: eps
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 0.18215
+    SIZE_FACTOR: 8
+    DECODER_BIAS: 0.5
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "linear"
+      "BETA_MIN": 0.0001
+      "BETA_MAX": 0.02
+    USE_EMA: False
+    LOAD_REFINER: False
+    #
+    DIFFUSION_MODEL:
+      NAME: PixArt
+      PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@PixArt-XL-2-1024-MS.pth
+      INPUT_SIZE: 128
+      PATCH_SIZE: 2
+      IN_CHANNELS: 4
+      HIDDEN_SIZE: 1152
+      DEPTH: 28
+      NUM_HEADS: 16
+      MLP_RATIO: 4.0
+      CLASS_DROPOUT_PROB: 0.1
+      PRED_SIGMA: True
+      DROP_PATH: 0.0
+      WINDOW_DIZE: 0
+      USE_REL_POS: False
+      CAPTION_CHANNELS: 4096
+      LEWEI_SCALE: 2
+      MODEL_MAX_LENGTH: 120
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-2-base@512-base-ema.safetensors
+      EMBED_DIM: 4
+      IGNORE_KEYS: [ ]
+      BATCH_SIZE: 1
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+      TOKENIZER_PATH: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+      LENGTH: 120
+      CLEAN: heavy
+      USE_GRAD: False
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 20
+    SEED: 2024
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+    DISCRETIZATION: trailing
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 0.0001
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a boy wearing a jacket", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 0
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'

scepter/methods/studio/self_train/dit/sd3_pro.yaml

@@ -0,0 +1,284 @@
+ENV:
+  BACKEND: nccl
+META:
+  VERSION: 'SD3'
+  DESCRIPTION: "SD3 ALPHA"
+  IS_DEFAULT: False
+  IS_SHARE: True
+  INFERENCE_PARAS:
+    INFERENCE_BATCH_SIZE: 1
+    INFERENCE_PREFIX: ""
+    DEFAULT_SAMPLER: "euler"
+    DEFAULT_SAMPLE_STEPS: 28
+    INFERENCE_N_PROMPT: ""
+    RESOLUTION: [1024, 1024]
+  PARAS:
+    -
+      TRAIN_BATCH_SIZE: 2
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [1024, 1024]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 1e-5
+      IS_DEFAULT: False
+      TUNER: FULL
+    -
+      TRAIN_BATCH_SIZE: 2
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [1024, 1024]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 5e-5
+      IS_DEFAULT: True
+      TUNER: LORA
+  #
+  TUNERS:
+    LORA:
+      -
+        NAME: SwiftLoRA
+        R: 128
+        LORA_ALPHA: 128
+        LORA_DROPOUT: 0.0
+        BIAS: "none"
+        TARGET_MODULES: "model.*(.attn.qkv|.attn.proj|mlp.fc1|mlp.fc2)$"
+#
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 1000
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: -1
+  RESCALE_LR: False
+  #
+  WORK_DIR: cache/scepter_ui/self_train/dit/sd3
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    - NAME: "ModelscopeFs"
+      TEMP_DIR: "./cache/cache_data"
+  #
+  FREEZE:
+  #
+  TUNER:
+  #
+  MODEL:
+    NAME: LatentDiffusionSD3
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 1.5305
+    SHIFT_FACTOR: 0.0609
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "shifted"
+      "SHIFT": 3
+    USE_EMA: False
+    T_WEIGHT: uniform
+    #
+    DIFFUSION_MODEL:
+      NAME: MMDiT
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      IGNORE_KEYS: '^first_stage_model.'
+      IN_CHANNELS: 16
+      PATCH_SIZE: 2
+      OUT_CHANNELS: 16
+      DEPTH: 24
+      INPUT_SIZE:
+      ADM_IN_CHANNELS: 2048
+      CONTEXT_EMBEDDER_CONFIG: { 'target': 'torch.nn.Linear', 'params': { 'in_features': 4096, 'out_features': 1536 } }
+      NUM_PATCHES: 36864
+      POS_EMBED_MAX_SIZE: 192
+      POS_EMBED_SCALING_FACTOR:
+      USE_CHECKPOINT: True
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      EMBED_DIM: 16
+      IGNORE_KEYS: '^model.diffusion_model.'
+      BATCH_SIZE: 1
+      USE_CONV: False
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: SD3TextEmbedder
+      P_ZERO: 0.0
+      CLIP_L:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      CLIP_G:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_2
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_2
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      T5_XXL:
+        NAME: T5EmbedderHF
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_3
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_3
+        LENGTH: 256
+        CLEAN: whitespace
+        USE_GRAD: False
+        T5_DTYPE: float16
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: euler
+    SAMPLE_STEPS: 28
+    SEED: 1749023094
+    GUIDE_SCALE: 5.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 5e-5
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a cat holds a blackboard that writes \"hello world\"", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 1
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'

scepter/methods/studio/self_train/edit/stylebooth_tb_pro.yaml

@@ -0,0 +1,377 @@
+ENV:
+  BACKEND: nccl
+META:
+  VERSION: 'EDIT'
+  DESCRIPTION: "EDIT"
+  IS_DEFAULT: False
+  IS_SHARE: True
+  INFERENCE_PARAS:
+    INFERENCE_BATCH_SIZE: 1
+    INFERENCE_PREFIX: ""
+    DEFAULT_SAMPLER: "ddim"
+    DEFAULT_SAMPLE_STEPS: 40
+    INFERENCE_N_PROMPT: ""
+    RESOLUTION: [512, 512]
+  PARAS:
+    -
+      TASK: 'Image Editing'
+      TRAIN_BATCH_SIZE: 1
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [512, 512]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 0.0001
+      IS_DEFAULT: False
+      TUNER: FULL
+    -
+      TASK: 'Image Editing'
+      TRAIN_BATCH_SIZE: 1
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [512, 512]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 0.0001
+      IS_DEFAULT: True
+      TUNER: LORA
+    -
+      TASK: 'Image Editing'
+      TRAIN_BATCH_SIZE: 1
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [512, 512]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 0.0001
+      IS_DEFAULT: False
+      TUNER: SCE
+
+    -
+      TASK: 'Image Editing'
+      TRAIN_BATCH_SIZE: 1
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [512, 512]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 0.0001
+      IS_DEFAULT: False
+      TUNER: TEXT_SCE
+
+    -
+      TASK: 'Image Editing'
+      TRAIN_BATCH_SIZE: 4
+      TRAIN_PREFIX: ""
+      TRAIN_N_PROMPT: ""
+      RESOLUTION: [512, 512]
+      MEMORY: 29000
+      EPOCHS: 50
+      SAVE_INTERVAL: 25
+      EPSEC: 0.818
+      LEARNING_RATE: 0.0001
+      IS_DEFAULT: False
+      TUNER: TEXT_LORA
+
+  TUNERS:
+    LORA:
+      -
+        NAME: SwiftLoRA
+        R: 256
+        LORA_ALPHA: 256
+        LORA_DROPOUT: 0.0
+        BIAS: "none"
+        TARGET_MODULES: "model.*(to_q|to_k|to_v|to_out.0|net.0.proj|net.2)$"
+    TEXT_LORA:
+      -
+        NAME: SwiftLoRA
+        R: 256
+        LORA_ALPHA: 256
+        LORA_DROPOUT: 0.0
+        BIAS: "none"
+        TARGET_MODULES: "(cond_stage_model.*(q_proj|k_proj|v_proj|out_proj|mlp.fc1|mlp.fc2))|(model.*(to_q|to_k|to_v|to_out.0|net.0.proj|net.2))$"
+    SCE:
+      -
+        NAME: SwiftSCETuning
+        DIMS: [1280, 1280, 1280, 1280, 1280, 640, 640, 640, 320, 320, 320, 320]
+        DOWN_RATIO: 1.0
+        TARGET_MODULES: model.lsc_identity\.\d+$
+        TUNER_MODE: identity
+    TEXT_SCE:
+      -
+        NAME: SwiftSCETuning
+        DIMS: [ 1280, 1280, 1280, 1280, 1280, 640, 640, 640, 320, 320, 320, 320 ]
+        DOWN_RATIO: 1.0
+        TARGET_MODULES: model.lsc_identity\.\d+$
+        TUNER_MODE: identity
+      -
+        NAME: SwiftLoRA
+        R: 256
+        LORA_ALPHA: 256
+        LORA_DROPOUT: 0.0
+        BIAS: "none"
+        TARGET_MODULES: "cond_stage_model.*(q_proj|k_proj|v_proj|out_proj|mlp.fc1|mlp.fc2)$"
+
+  MODIFY_PARAS:
+    TEXT_LORA:
+      TRAIN:
+        SOLVER.MODEL.COND_STAGE_MODEL.USE_GRAD: True
+    TEXT_SCE:
+      TRAIN:
+        SOLVER.MODEL.COND_STAGE_MODEL.USE_GRAD: True
+
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 1000
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: -1
+  RESCALE_LR: False
+  #
+  WORK_DIR:
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  FREEZE:
+  #
+  TUNER:
+  #
+  MODEL:
+    NAME: LatentDiffusionEdit
+    PARAMETERIZATION: eps
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL: ms://iic/stylebooth@models/stylebooth-tb-5000-0.bin
+    IGNORE_KEYS: [ ]
+    CONCAT_NO_SCALE_FACTOR: True
+    SCALE_FACTOR: 0.18215
+    SIZE_FACTOR: 8
+    # DEFAULT_N_PROMPT: 'lowres, error, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "scaled_linear"
+      "BETA_MIN": 0.00085
+      "BETA_MAX": 0.012
+    USE_EMA: False
+    #
+    DIFFUSION_MODEL:
+      NAME: DiffusionUNet
+      IN_CHANNELS: 8
+      OUT_CHANNELS: 4
+      MODEL_CHANNELS: 320
+      NUM_HEADS: 8
+      NUM_RES_BLOCKS: 2
+      ATTENTION_RESOLUTIONS: [ 4, 2, 1 ]
+      CHANNEL_MULT: [ 1, 2, 4, 4 ]
+      CONV_RESAMPLE: True
+      DIMS: 2
+      USE_CHECKPOINT: False
+      USE_SCALE_SHIFT_NORM: False
+      RESBLOCK_UPDOWN: False
+      USE_SPATIAL_TRANSFORMER: True
+      TRANSFORMER_DEPTH: 1
+      CONTEXT_DIM: 768
+      DISABLE_MIDDLE_SELF_ATTN: False
+      USE_LINEAR_IN_TRANSFORMER: False
+      IGNORE_KEYS: []
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      EMBED_DIM: 4
+      IGNORE_KEYS: []
+      BATCH_SIZE: 4
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    TOKENIZER:
+      NAME: ClipTokenizer
+      PRETRAINED_PATH: ms://AI-ModelScope/clip-vit-large-patch14
+      LENGTH: 77
+      CLEAN: True
+    #
+    COND_STAGE_MODEL:
+      NAME: FrozenCLIPEmbedder
+      FREEZE: True
+      USE_GRAD: False
+      LAYER: last
+      PRETRAINED_MODEL: ms://AI-ModelScope/clip-vit-large-patch14
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 50
+    SEED: 2023
+    GUIDE_SCALE: #7.5
+      image: 1.5
+      text: 7.5
+    GUIDE_RESCALE: 0.5
+    DISCRETIZATION: trailing
+    IMAGE_SIZE: [512, 512]
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 0.0001
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: ./cache/cache_data/delogo/
+    MS_DATASET_NAMESPACE: ""
+    MS_DATASET_SPLIT: "train"
+    MS_DATASET_SUBNAME: ""
+    PROMPT_PREFIX: ""
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFileList
+        FILE_KEYS: ['img_path', 'src_path']
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'image', 'condition_cat' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'condition_cat', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 0
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [  ]
+    IMAGE_SIZE: [ 512, 512 ]
+    FIELDS: [ "prompt", "src_path" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: LoadImageFromFileList
+        FILE_KEYS: [ 'src_path' ]
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'condition_cat' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'condition_cat', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'

scepter/methods/studio/self_train/sd_xl/sdxl_pro.yaml

@@ -147,6 +147,7 @@ SOLVER:
   MAX_EPOCHS: -1
   # NUM_FOLDS DESCRIPTION: Num folds for training. TYPE: int default: 1
   NUM_FOLDS: 1
+  RESCALE_LR: False
   #
   EVAL_INTERVAL: -1
   # WORK_DIR DESCRIPTION: Save dir of the training log or model. TYPE: str default: ''
@@ -155,7 +156,7 @@ SOLVER:
   LOG_FILE: std_log.txt
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   TUNER:
   # MODEL DESCRIPTION:  TYPE:  default: ''
   MODEL:
@@ -538,7 +539,7 @@ SOLVER:
   OPTIMIZER:
     # NAME DESCRIPTION:  TYPE:  default: ''
     NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
     EPS: 1e-8
     AMSGRAD: False
   #

scepter/methods/studio/self_train/stable_diffusion/sd15_pro.yaml

@@ -137,13 +137,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: -1
+  RESCALE_LR: False
   #
   WORK_DIR:
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
   #
@@ -249,7 +250,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/studio/self_train/stable_diffusion/sd21_pro.yaml

@@ -80,13 +80,14 @@ SOLVER:
   NUM_FOLDS: 1
   ACCU_STEP: 1
   EVAL_INTERVAL: -1
+  RESCALE_LR: False
   #
   WORK_DIR:
   LOG_FILE: std_log.txt
   #
   FILE_SYSTEM:
     NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
   #
   FREEZE:
   #
@@ -191,7 +192,7 @@ SOLVER:
   #
   OPTIMIZER:
     NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
     BETAS: [ 0.9, 0.999 ]
     EPS: 1e-8
     WEIGHT_DECAY: 1e-2

scepter/methods/studio/tuner_manager/readme_en.md

@@ -1,7 +1,7 @@
 ---
 frameworks:
 - Pytorch
-license: Apache License 2.0
+license: apache-2.0
 tasks:
 - efficient-diffusion-tuning
 ---

scepter/methods/studio/tuner_manager/readme_zh.md

@@ -1,7 +1,7 @@
 ---
 frameworks:
 - Pytorch
-license: Apache License 2.0
+license: apache-2.0
 tasks:
 - efficient-diffusion-tuning
 ---

scepter/methods/studio/tuner_manager/tuner_manager.yaml

@@ -1,14 +1,15 @@
 WORK_DIR: "tuner_manager"
-SELF_TRAIN_DIR: "self_train"
 EXPORT_DIR: "export_model"
 TUNER_LIST_YAML: "tuner_list.yaml"
 README_EN: "scepter/methods/studio/tuner_manager/readme_en.md"
 README_ZH: "scepter/methods/studio/tuner_manager/readme_zh.md"
 
 BASE_MODEL_VERSION:
-  - BASE_MODEL: 'SD_XL1.0'
-    TUNER_TYPE: [ 'TEXT_SCE', 'SCE', 'LORA', 'TEXT_LORA', 'FULL' ]
   - BASE_MODEL: 'SD1.5'
-    TUNER_TYPE: [ 'TEXT_SCE', 'SCE', 'LORA', 'TEXT_LORA', 'FULL' ]
+    TUNER_TYPE: [ 'TEXT_LORA', 'TEXT_SCE', 'LORA', 'SCE', 'FULL' ]
+  - BASE_MODEL: 'SD_XL1.0'
+    TUNER_TYPE: [ 'TEXT_LORA', 'TEXT_SCE', 'LORA', 'SCE', 'FULL' ]
   - BASE_MODEL: 'SD2.1'
-    TUNER_TYPE: [ 'SCE', 'LORA', 'FULL' ]
+    TUNER_TYPE: [ 'LORA', 'SCE', 'FULL' ]
+  - BASE_MODEL: 'EDIT'
+    TUNER_TYPE: [ 'LORA', 'SCE', 'FULL' ]

scepter/modules/annotator/base_annotator.py

@@ -4,7 +4,6 @@ from abc import ABCMeta
 
 import torch
 import torch.nn as nn
-
 from scepter.modules.annotator.registry import ANNOTATORS
 from scepter.modules.model.base_model import BaseModel
 from scepter.modules.utils.config import dict_to_yaml

scepter/modules/annotator/canny.py

@@ -6,7 +6,6 @@ import cv2
 import numpy as np
 import torch
 from PIL import Image
-
 from scepter.modules.annotator.base_annotator import BaseAnnotator
 from scepter.modules.annotator.registry import ANNOTATORS
 from scepter.modules.utils.config import dict_to_yaml

scepter/modules/annotator/color.py

@@ -6,7 +6,6 @@ import cv2
 import numpy as np
 import torch
 from PIL import Image
-
 from scepter.modules.annotator.base_annotator import BaseAnnotator
 from scepter.modules.annotator.registry import ANNOTATORS
 from scepter.modules.utils.config import dict_to_yaml

scepter/modules/annotator/hed.py

@@ -11,13 +11,14 @@ from abc import ABCMeta
 import cv2
 import numpy as np
 import torch
+import torchvision
 from einops import rearrange
-
 from scepter.modules.annotator.base_annotator import BaseAnnotator
 from scepter.modules.annotator.registry import ANNOTATORS
 from scepter.modules.utils.config import dict_to_yaml
 from scepter.modules.utils.distribute import we
 from scepter.modules.utils.file_system import FS
+from torchvision.transforms import InterpolationMode
 
 
 def nms(x, t, s):
@@ -123,6 +124,8 @@ class HedAnnotator(BaseAnnotator, metaclass=ABCMeta):
             if len(image.shape) == 3:
                 image = rearrange(image, 'h w c -> 1 c h w')
                 B, C, H, W = image.shape
+            elif len(image.shape) == 4:
+                B, C, H, W = image.shape
             else:
                 raise "Unsurpport input image's shape"
         elif isinstance(image, np.ndarray):
@@ -130,22 +133,22 @@ class HedAnnotator(BaseAnnotator, metaclass=ABCMeta):
             if len(image.shape) == 3:
                 image = rearrange(image, 'h w c -> 1 c h w')
                 B, C, H, W = image.shape
+            elif len(image.shape) == 4:
+                B, C, H, W = image.shape
             else:
                 raise "Unsurpport input image's shape"
         else:
             raise "Unsurpport input image's type"
+        transform = torchvision.transforms.Resize(
+            (H, W), interpolation=InterpolationMode.BILINEAR, antialias=True)
         edges = self.netNetwork(image.to(we.device_id))
-        edges = [
-            e.detach().cpu().numpy().astype(np.float32)[0, 0] for e in edges
-        ]
-        edges = [
-            cv2.resize(e, (W, H), interpolation=cv2.INTER_LINEAR)
-            for e in edges
-        ]
-        edges = np.stack(edges, axis=2)
-        edge = 1 / (1 + np.exp(-np.mean(edges, axis=2).astype(np.float64)))
-        edge = 255 - (edge * 255.0).clip(0, 255).astype(np.uint8)
-        return edge[..., None].repeat(3, 2)
+        edges = [transform(e) for e in edges]
+        edges = torch.cat(edges, dim=1)
+        edges = 1 / (1 +
+                     torch.exp(-torch.mean(edges, dim=1).type(torch.float)))
+        edges = edges.cpu().numpy()
+        edges = 255 - (edges * 255.0).clip(0, 255).astype(np.uint8)
+        return edges[..., None].repeat(3, -1)
 
     @staticmethod
     def get_config_template():

scepter/modules/annotator/midas/__init__.py

@@ -0,0 +1,2 @@
+# -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.

scepter/modules/annotator/midas/api.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 # based on https://github.com/isl-org/MiDaS
 
 import cv2

scepter/modules/annotator/midas/base_model.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import torch
 
 

scepter/modules/annotator/midas/blocks.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import torch
 import torch.nn as nn
 

scepter/modules/annotator/midas/dpt_depth.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import torch
 import torch.nn as nn
 

scepter/modules/annotator/midas/midas_net.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 """MidashNet: Network for monocular depth estimation trained by mixing several datasets.
 This file contains code that is adapted from
 https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py

scepter/modules/annotator/midas/midas_net_custom.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 """MidashNet: Network for monocular depth estimation trained by mixing several datasets.
 This file contains code that is adapted from
 https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py

scepter/modules/annotator/midas/transforms.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import math
 
 import cv2

scepter/modules/annotator/midas/utils.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 """Utils for monoDepth."""
 import re
 import sys

scepter/modules/annotator/midas/vit.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import math
 import types
 

scepter/modules/annotator/midas_op.py

@@ -9,7 +9,6 @@ import numpy as np
 import torch
 from einops import rearrange
 from PIL import Image
-
 from scepter.modules.annotator.base_annotator import BaseAnnotator
 from scepter.modules.annotator.midas.api import MiDaSInference
 from scepter.modules.annotator.registry import ANNOTATORS

scepter/modules/annotator/mlsd/__init__.py

@@ -0,0 +1,2 @@
+# -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.

scepter/modules/annotator/mlsd/mbv2_mlsd_large.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 
 import torch
 import torch.nn as nn

scepter/modules/annotator/mlsd/mbv2_mlsd_tiny.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 import torch
 import torch.nn as nn
 import torch.utils.model_zoo as model_zoo

scepter/modules/annotator/mlsd/utils.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 
 # modified by  lihaoweicv
 # pytorch version

scepter/modules/annotator/mlsd_op.py

@@ -11,7 +11,6 @@ import cv2
 import numpy as np
 import torch
 from PIL import Image
-
 from scepter.modules.annotator.base_annotator import BaseAnnotator
 from scepter.modules.annotator.mlsd.mbv2_mlsd_large import MobileV2_MLSD_Large
 from scepter.modules.annotator.mlsd.utils import pred_lines

scepter/modules/annotator/openpose.py

@@ -15,13 +15,12 @@ import numpy as np
 import torch
 import torch.nn as nn
 from PIL import Image
-from scipy.ndimage.filters import gaussian_filter
-from skimage.measure import label
-
 from scepter.modules.annotator.base_annotator import BaseAnnotator
 from scepter.modules.annotator.registry import ANNOTATORS
 from scepter.modules.utils.config import dict_to_yaml
 from scepter.modules.utils.file_system import FS
+from scipy.ndimage.filters import gaussian_filter
+from skimage.measure import label
 
 os.environ['KMP_DUPLICATE_LIB_OK'] = 'TRUE'
 

scepter/modules/annotator/utils.py

@@ -37,30 +37,30 @@ class AnnotatorProcessor():
     hed_cfg = {
         'NAME': 'HedAnnotator',
         'PRETRAINED_MODEL':
-        'ms://damo/scepter_scedit@annotator/ckpts/ControlNetHED.pth',
+        'ms://iic/scepter_scedit@annotator/ckpts/ControlNetHED.pth',
         'INPUT_KEYS': ['img'],
         'OUTPUT_KEYS': ['hed']
     }
     openpose_cfg = {
         'NAME': 'OpenposeAnnotator',
         'BODY_MODEL_PATH':
-        'ms://damo/scepter_scedit@annotator/ckpts/body_pose_model.pth',
+        'ms://iic/scepter_scedit@annotator/ckpts/body_pose_model.pth',
         'HAND_MODEL_PATH':
-        'ms://damo/scepter_scedit@annotator/ckpts/hand_pose_model.pth',
+        'ms://iic/scepter_scedit@annotator/ckpts/hand_pose_model.pth',
         'INPUT_KEYS': ['img'],
         'OUTPUT_KEYS': ['openpose']
     }
     midas_cfg = {
         'NAME': 'MidasDetector',
         'PRETRAINED_MODEL':
-        'ms://damo/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt',
+        'ms://iic/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt',
         'INPUT_KEYS': ['img'],
         'OUTPUT_KEYS': ['depth']
     }
     mlsd_cfg = {
         'NAME': 'MLSDdetector',
         'PRETRAINED_MODEL':
-        'ms://damo/scepter_scedit@annotator/ckpts/mlsd_large_512_fp32.pth',
+        'ms://iic/scepter_scedit@annotator/ckpts/mlsd_large_512_fp32.pth',
         'INPUT_KEYS': ['img'],
         'OUTPUT_KEYS': ['mlsd']
     }

scepter/modules/data/dataset/base_dataset.py

@@ -3,14 +3,13 @@
 
 from abc import ABCMeta, abstractmethod
 
-from torch.utils.data import Dataset
-
 from scepter.modules.transform.registry import TRANSFORMS, build_pipeline
 from scepter.modules.utils.config import dict_to_yaml
 from scepter.modules.utils.distribute import we
 from scepter.modules.utils.file_system import FS
 from scepter.modules.utils.logger import get_logger
 from scepter.modules.utils.registry import old_python_version
+from torch.utils.data import Dataset
 
 
 class BaseDataset(Dataset, metaclass=ABCMeta):

scepter/modules/data/dataset/dataset.py

@@ -8,7 +8,6 @@ from collections.abc import Iterable
 
 import numpy as np
 import torchvision
-
 from scepter.modules.data.dataset.base_dataset import BaseDataset
 from scepter.modules.data.dataset.registry import DATASETS
 from scepter.modules.utils.config import dict_to_yaml
@@ -272,6 +271,11 @@ class Text2ImageDataset(BaseDataset):
                     item['prompt'] = prompt_prefix + value
                 elif key in ['oss_key', 'path', 'img_path', 'target_img_path']:
                     item['meta']['img_path'] = os.path.join(path_prefix, value)
+                elif key in [
+                        'src_oss_key', 'src_path', 'src_img_path',
+                        'src_target_img_path'
+                ]:
+                    item['meta']['src_path'] = os.path.join(path_prefix, value)
                 elif key in ['width', 'height']:
                     item['meta'][key] = int(value)
                 else:

scepter/modules/data/dataset/ms_dataset.py

@@ -101,14 +101,13 @@ class ImageTextPairMSDataset(BaseDataset):
             if isinstance(self.output_size, numbers.Number):
                 self.output_size = [self.output_size, self.output_size]
         # Use modelscope dataset
-
         if not ms_dataset_name:
             raise (
                 'Your must set MS_DATASET_NAME as modelscope dataset or your local dataset orignized '
                 'as modelscope dataset.')
         if FS.exists(ms_dataset_name):
             ms_dataset_name = FS.get_dir_to_local_dir(ms_dataset_name)
-            ms_remap_path = ms_dataset_name
+            # ms_remap_path = ms_dataset_name
         try:
             self.data = MsDataset.load(str(ms_dataset_name),
                                        namespace=ms_dataset_namespace,
@@ -133,9 +132,11 @@ class ImageTextPairMSDataset(BaseDataset):
         if ms_remap_path:
 
             def map_func(example):
-                example['Target:FILE'] = os.path.join(ms_remap_path,
-                                                      example['Target:FILE'])
-                return example
+                return {
+                    k: os.path.join(ms_remap_path, v)
+                    if k.endswith(':FILE') else v
+                    for k, v in example.items()
+                }
 
             self.data = self.data.ds_instance.map(map_func)
         self.real_number = len(self.data)
@@ -149,9 +150,12 @@ class ImageTextPairMSDataset(BaseDataset):
     def _get(self, index: int):
         current_data = self.data[index % len(self.data)]
         # print(current_data.keys())
-        image_path = current_data['Target:FILE']
-        prompt = current_data['Prompt']
+        image_path = current_data[
+            'Target:FILE'] if 'Target:FILE' in current_data else ''
+        prompt = current_data.get('Prompt', current_data.get('prompt', ''))
         style = current_data['Style'] if 'Style' in current_data else ''
+        src_image_path = current_data[
+            'Source:FILE'] if 'Source:FILE' in current_data else ''
         # print(prompt, style)
         if self.replace_style and not style == '':
             prompt = prompt.replace(style, f'<{self.keywords_sign}>')
@@ -166,6 +170,7 @@ class ImageTextPairMSDataset(BaseDataset):
         ret_item = {
             'meta': {
                 'img_path': image_path,
+                'src_path': src_image_path,
                 'data_key': style,
                 'data_num': self.real_number
             },
@@ -173,6 +178,9 @@ class ImageTextPairMSDataset(BaseDataset):
         }
         if self.output_size is not None:
             ret_item['meta']['image_size'] = self.output_size
+        for key in current_data:
+            if key not in ret_item['meta']:
+                ret_item['meta'][key] = current_data[key]
         return ret_item
 
     @staticmethod
@@ -241,19 +249,18 @@ class ImageTextPairFolderDataset(BaseDataset):
         data_folder = FS.get_dir_to_local_dir(data_folder)
         all_lines = open(os.path.join(data_folder, 'train.csv'),
                          'r').read().split('\n')
-        assert all_lines[0] == 'Target:FILE,Prompt'
+        header = all_lines[0].split(',')
         self.data = []
         for line in all_lines[1:]:
             line = line.strip()
             if line == '':
                 continue
-            self.data.append({
-                'Target:FILE':
-                os.path.join(data_folder,
-                             line.split(',', 1)[0]),
-                'Prompt':
-                line.split(',', 1)[1]
-            })
+            record = dict(zip(header, line.split(',', len(header) - 1)))
+            record = {
+                k: os.path.join(data_folder, v) if k.endswith(':FILE') else v
+                for k, v in record.items()
+            }
+            self.data.append(record)
         self.real_number = len(self.data)
 
     def __len__(self):
@@ -265,9 +272,12 @@ class ImageTextPairFolderDataset(BaseDataset):
     def _get(self, index: int):
         current_data = self.data[index % len(self.data)]
         # print(current_data.keys())
-        image_path = current_data['Target:FILE']
-        prompt = current_data['Prompt']
+        image_path = current_data[
+            'Target:FILE'] if 'Target:FILE' in current_data else ''
+        prompt = current_data.get('Prompt', current_data.get('prompt', ''))
         style = current_data['Style'] if 'Style' in current_data else ''
+        src_image_path = current_data[
+            'Source:FILE'] if 'Source:FILE' in current_data else ''
         # print(prompt, style)
         if self.replace_style and not style == '':
             prompt = prompt.replace(style, f'<{self.keywords_sign}>')
@@ -282,6 +292,7 @@ class ImageTextPairFolderDataset(BaseDataset):
         ret_item = {
             'meta': {
                 'img_path': image_path,
+                'src_path': src_image_path,
                 'data_key': style,
                 'data_num': self.real_number
             },
@@ -289,6 +300,9 @@ class ImageTextPairFolderDataset(BaseDataset):
         }
         if self.output_size is not None:
             ret_item['meta']['image_size'] = self.output_size
+        for key in current_data:
+            if key not in ret_item['meta']:
+                ret_item['meta'][key] = current_data[key]
         return ret_item
 
     @staticmethod