Merge branch 'dev2' into master

.github/workflows/typos.yaml

@@ -18,4 +18,4 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: typos-action
-        uses: crate-ci/[email protected].18
+        uses: crate-ci/[email protected].21

.release

@@ -1 +1 @@
-v22.1.0
+v22.1.1

README.md

@@ -241,7 +241,7 @@ To set up the project, follow these steps:
    .\setup.bat
    ```
 
-   During the accelerate config step use the default values as proposed during the configuration unless you know your hardware demand otherwise. Tfe amount of VRAM on your GPU does not have an impact on the values used.
+   During the accelerate config step use the default values as proposed during the configuration unless you know your hardware demand otherwise. The amount of VRAM on your GPU does not have an impact on the values used.
 
 #### Optional: CUDNN 8.6
 
@@ -368,6 +368,7 @@ If you prefer to use Docker, follow the instructions below:
    ```bash
    git clone https://github.com/bmaltais/kohya_ss.git
    cd kohya_ss
+   docker compose create
    docker compose build
    docker compose run --service-ports kohya-ss-gui
    ```
@@ -626,6 +627,8 @@ save_file(state_dict, file)
 ControlNet-LLLite, a novel method for ControlNet with SDXL, is added. See [documentation](./docs/train_lllite_README.md) for details.
 
 ## Change History
+* 2023/11/03 (v22.1.1)
+  - Implement headless support for tensorboard as proposed by @sammcj
 
 * 2023/10/10 (v22.1.0)
   - Remove support for torch 1 to align with kohya_ss sd-scripts code base.

docs/LoRA/top_level.md

@@ -8,7 +8,7 @@ Access EDG's tutorials here: https://ko-fi.com/post/EDGs-tutorials-P5P6KT5MT
 
 - Set the `Max resolution` to at least 1024x1024, as this is the standard resolution for SDXL.
 - Use a GPU that has at least 12GB memory for the LoRA training process.
-- We strongly recommend using the `--train_unet_only` option for SDXL LoRA to avoid unforeseen training results caused by dual text encoders in SDXL.
+- We strongly recommend using the `--network_train_unet_only` option for SDXL LoRA to avoid unforeseen training results caused by dual text encoders in SDXL.
 - PyTorch 2 tends to use less GPU memory than PyTorch 1.
 
 Here's an example configuration for the Adafactor optimizer with a fixed learning rate:

dreambooth_gui.py

@@ -780,7 +780,7 @@ def dreambooth_tab(
 
         button_start_tensorboard.click(
             start_tensorboard,
-            inputs=folders.logging_dir,
+            inputs=[dummy_headless, folders.logging_dir],
             show_progress=False,
         )
 

finetune_gui.py

@@ -906,7 +906,7 @@ def list_presets(path):
 
         button_start_tensorboard.click(
             start_tensorboard,
-            inputs=logging_dir,
+            inputs=[dummy_headless, logging_dir],
         )
 
         button_stop_tensorboard.click(

library/tensorboard_gui.py

@@ -15,8 +15,10 @@
 # Set the default tensorboard port
 DEFAULT_TENSORBOARD_PORT = 6006
 
-def start_tensorboard(logging_dir, wait_time=5):
+def start_tensorboard(headless, logging_dir, wait_time=5):
     global tensorboard_proc
+
+    headless_bool = True if headless.get('label') == 'True' else False
 
     # Read the TENSORBOARD_PORT from the environment, or use the default
     tensorboard_port = os.environ.get('TENSORBOARD_PORT', DEFAULT_TENSORBOARD_PORT)
@@ -51,13 +53,14 @@ def start_tensorboard(logging_dir, wait_time=5):
         log.error('Failed to start Tensorboard:', e)
         return
 
-    # Wait for some time to allow TensorBoard to start up
-    time.sleep(wait_time)
+    if not headless_bool:
+        # Wait for some time to allow TensorBoard to start up
+        time.sleep(wait_time)
 
-    # Open the TensorBoard URL in the default browser
-    tensorboard_url = f'http://localhost:{tensorboard_port}'
-    log.info(f'Opening TensorBoard URL in browser: {tensorboard_url}')
-    webbrowser.open(tensorboard_url)
+        # Open the TensorBoard URL in the default browser
+        tensorboard_url = f'http://localhost:{tensorboard_port}'
+        log.info(f'Opening TensorBoard URL in browser: {tensorboard_url}')
+        webbrowser.open(tensorboard_url)
 
 
 def stop_tensorboard():

lora_gui.py

@@ -1538,7 +1538,7 @@ def update_LoRA_settings(LoRA_type):
 
         button_start_tensorboard.click(
             start_tensorboard,
-            inputs=folders.logging_dir,
+            inputs=[dummy_headless, folders.logging_dir],
             show_progress=False,
         )
 

presets/finetune/SDXL - Essenz series by AI_Characters_Training v1.0.json

@@ -0,0 +1,88 @@
+{
+  "adaptive_noise_scale": 0,
+  "additional_parameters": "",
+  "batch_size": "1",
+  "block_lr": "",
+  "bucket_no_upscale": false,
+  "bucket_reso_steps": 64,
+  "cache_latents": true,
+  "cache_latents_to_disk": true,
+  "caption_dropout_every_n_epochs": 0.0,
+  "caption_dropout_rate": 0,
+  "caption_extension": ".txt",
+  "caption_metadata_filename": "meta_cap.json",
+  "clip_skip": "1",
+  "color_aug": false,
+  "dataset_repeats": "1",
+  "epoch": 1,
+  "flip_aug": false,
+  "full_bf16": false,
+  "full_fp16": false,
+  "full_path": true,
+  "generate_caption_database": true,
+  "generate_image_buckets": true,
+  "gradient_accumulation_steps": 1.0,
+  "gradient_checkpointing": true,
+  "image_folder": "/kohya_ss/dataset/1_/",
+  "keep_tokens": 0,
+  "latent_metadata_filename": "meta_lat.json",
+  "learning_rate": 1e-06,
+  "logging_dir": "/kohya_ss/output/SDXL1.0_Essenz-series-by-AI_Characters_Concept_Morphing-v1.0",
+  "lr_scheduler": "constant",
+  "lr_scheduler_args": "",
+  "lr_warmup": 0,
+  "max_bucket_reso": "4096",
+  "max_data_loader_n_workers": "0",
+  "max_resolution": "1024,1024",
+  "max_timestep": 1000,
+  "max_token_length": "75",
+  "max_train_epochs": "100",
+  "mem_eff_attn": false,
+  "min_bucket_reso": "64",
+  "min_snr_gamma": 0,
+  "min_timestep": 0,
+  "mixed_precision": "fp16",
+  "model_list": "stabilityai/stable-diffusion-xl-base-1.0",
+  "multires_noise_discount": 0,
+  "multires_noise_iterations": 0,
+  "noise_offset": 0,
+  "noise_offset_type": "Original",
+  "num_cpu_threads_per_process": 2,
+  "optimizer": "AdamW8bit",
+  "optimizer_args": "",
+  "output_dir": "/kohya_ss/output/SDXL1.0_Essenz-series-by-AI_Characters_Concept_Morphing-v1.0",
+  "output_name": "SDXL1.0_Essenz-series-by-AI_Characters_Concept_Morphing-v1.0",
+  "persistent_data_loader_workers": false,
+  "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0",
+  "random_crop": false,
+  "resume": "",
+  "sample_every_n_epochs": 0,
+  "sample_every_n_steps": 0,
+  "sample_prompts": "",
+  "sample_sampler": "k_dpm_2",
+  "save_every_n_epochs": 10,
+  "save_every_n_steps": 0,
+  "save_last_n_steps": 0,
+  "save_last_n_steps_state": 0,
+  "save_model_as": "safetensors",
+  "save_precision": "fp16",
+  "save_state": false,
+  "scale_v_pred_loss_like_noise_pred": false,
+  "sdxl_cache_text_encoder_outputs": false,
+  "sdxl_checkbox": true,
+  "sdxl_no_half_vae": true,
+  "seed": "",
+  "shuffle_caption": false,
+  "train_batch_size": 1,
+  "train_dir": "/kohya_ss/output/SDXL1.0_Essenz-series-by-AI_Characters_Concept_Morphing-v1.0",
+  "train_text_encoder": true,
+  "use_latent_files": "Yes",
+  "use_wandb": false,
+  "v2": false,
+  "v_parameterization": false,
+  "v_pred_like_loss": 0,
+  "vae_batch_size": 0,
+  "wandb_api_key": "",
+  "weighted_captions": false,
+  "xformers": "xformers"
+}

presets/lora/SDXL - LoRA aitrepreneur clothing v1.0.json

@@ -0,0 +1,97 @@
+{
+    "LoRA_type": "Standard",
+    "adaptive_noise_scale": 0,
+    "additional_parameters": "",
+    "block_alphas": "",
+    "block_dims": "",
+    "block_lr_zero_threshold": "",
+    "bucket_no_upscale": true,
+    "bucket_reso_steps": 64,
+    "cache_latents": true,
+    "cache_latents_to_disk": true,
+    "caption_dropout_every_n_epochs": 0.0,
+    "caption_dropout_rate": 0,
+    "caption_extension": ".txt",
+    "clip_skip": "1",
+    "color_aug": false,
+    "conv_alpha": 32,
+    "conv_block_alphas": "",
+    "conv_block_dims": "",
+    "conv_dim": 32,
+    "decompose_both": false,
+    "dim_from_weights": false,
+    "down_lr_weight": "",
+    "enable_bucket": true,
+    "epoch": 15,
+    "factor": -1,
+    "flip_aug": false,
+    "full_bf16": false,
+    "full_fp16": false,
+    "gradient_accumulation_steps": 2,
+    "gradient_checkpointing": true,
+    "keep_tokens": "0",
+    "learning_rate": 0.0009,
+    "lora_network_weights": "",
+    "lr_scheduler": "constant",
+    "lr_scheduler_args": "",
+    "lr_scheduler_num_cycles": "1",
+    "lr_scheduler_power": "",
+    "lr_warmup": 0,
+    "max_bucket_reso": 2048,
+    "max_data_loader_n_workers": "0",
+    "max_resolution": "1024,1024",
+    "max_timestep": 1000,
+    "max_token_length": "75",
+    "max_train_epochs": "",
+    "max_train_steps": "",
+    "mem_eff_attn": false,
+    "mid_lr_weight": "",
+    "min_bucket_reso": 256,
+    "min_snr_gamma": 0,
+    "min_timestep": 0,
+    "mixed_precision": "bf16",
+    "module_dropout": 0,
+    "multires_noise_discount": 0,
+    "multires_noise_iterations": 0,
+    "network_alpha": 1,
+    "network_dim": 128,
+    "network_dropout": 0,
+    "no_token_padding": false,
+    "noise_offset": 0,
+    "noise_offset_type": "Original",
+    "num_cpu_threads_per_process": 2,
+    "optimizer": "Adafactor",
+    "optimizer_args": "scale_parameter=False relative_step=False warmup_init=False",
+    "persistent_data_loader_workers": false,
+    "prior_loss_weight": 1.0,
+    "random_crop": false,
+    "rank_dropout": 0,
+    "save_every_n_epochs": 1,
+    "save_every_n_steps": 0,
+    "save_last_n_steps": 0,
+    "save_last_n_steps_state": 0,
+    "save_precision": "bf16",
+    "scale_v_pred_loss_like_noise_pred": false,
+    "scale_weight_norms": 0,
+    "sdxl": true,
+    "sdxl_cache_text_encoder_outputs": false,
+    "sdxl_no_half_vae": true,
+    "seed": "12345",
+    "shuffle_caption": false,
+    "stop_text_encoder_training": 0,
+    "text_encoder_lr": 0.0009,
+    "train_batch_size": 1,
+    "train_on_input": true,
+    "training_comment": "trigger: supergirl costume",
+    "unet_lr": 0.0009,
+    "unit": 1,
+    "up_lr_weight": "",
+    "use_cp": false,
+    "use_wandb": false,
+    "v2": false,
+    "v_parameterization": false,
+    "v_pred_like_loss": 0,
+    "vae_batch_size": 0,
+    "weighted_captions": false,
+    "xformers": "xformers"
+}

requirements_windows_torch2.txt

@@ -1,6 +1,6 @@
 torch==2.0.1+cu118 torchvision==0.15.2+cu118 --index-url https://download.pytorch.org/whl/cu118 # no_verify
 xformers==0.0.21
-bitsandbytes==0.35.0 # no_verify
+bitsandbytes==0.41.1 # no_verify
 # https://github.com/jllllll/bitsandbytes-windows-webui/releases/download/wheels/bitsandbytes-0.41.1-py3-none-win_amd64.whl # no_verify
 tensorboard==2.14.1 tensorflow==2.14.0
 -r requirements.txt

textual_inversion_gui.py

@@ -839,7 +839,7 @@ def ti_tab(
 
         button_start_tensorboard.click(
             start_tensorboard,
-            inputs=folders.logging_dir,
+            inputs=[dummy_headless, folders.logging_dir],
             show_progress=False,
         )