From d380f939b5ab6a28bed6d1de3cf283e194255963 Mon Sep 17 00:00:00 2001
From: Leon Feng <523684+leon0707@users.noreply.github.com>
Date: Sat, 15 Jul 2023 23:31:59 -0400
Subject: [PATCH 1/2] Update shared.py
---
modules/shared.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/modules/shared.py b/modules/shared.py
index a08620554..564799bca 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -394,7 +394,7 @@ options_templates.update(options_section(('training', "Training"), {
}))
options_templates.update(options_section(('sd', "Stable Diffusion"), {
- "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
+ "sd_model_checkpoint": OptionInfo("", "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
"sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
"sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
"sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"),
From d6668347c8b85b11b696ac56777cc396e34ee1f9 Mon Sep 17 00:00:00 2001
From: Leon Feng <best.sum@gmail.com>
Date: Tue, 18 Jul 2023 04:19:58 -0400
Subject: [PATCH 2/2] remove duplicate
---
modules/textual_inversion/logging.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/modules/textual_inversion/logging.py b/modules/textual_inversion/logging.py
index 734a4b6f4..a822a7a5c 100644
--- a/modules/textual_inversion/logging.py
+++ b/modules/textual_inversion/logging.py
@@ -2,7 +2,7 @@ import datetime
import json
import os
-saved_params_shared = {"model_name", "model_hash", "initial_step", "num_of_dataset_images", "learn_rate", "batch_size", "clip_grad_mode", "clip_grad_value", "gradient_step", "data_root", "log_directory", "training_width", "training_height", "steps", "create_image_every", "template_file", "gradient_step", "latent_sampling_method"}
+saved_params_shared = {"model_name", "model_hash", "initial_step", "num_of_dataset_images", "learn_rate", "batch_size", "clip_grad_mode", "clip_grad_value", "data_root", "log_directory", "training_width", "training_height", "steps", "create_image_every", "template_file", "gradient_step", "latent_sampling_method"}
saved_params_ti = {"embedding_name", "num_vectors_per_token", "save_embedding_every", "save_image_with_stored_embedding"}
saved_params_hypernet = {"hypernetwork_name", "layer_structure", "activation_func", "weight_init", "add_layer_norm", "use_dropout", "save_hypernetwork_every"}
saved_params_all = saved_params_shared | saved_params_ti | saved_params_hypernet