Update Scripts/mainpaperspacev1.py

Scripts/mainpaperspacev1.py

@@ -38,7 +38,7 @@ def Deps(force_reinstall):
         print('Modules and notebooks updated, dependencies already installed')
 
     else:
-        print('Installing the dependencies...')
+        print('Installing the dependencies...')
         call("pip install --root-user-action=ignore --no-deps -q accelerate==0.12.0", shell=True, stdout=open('/dev/null', 'w'))
         if not os.path.exists('/usr/local/lib/python3.9/dist-packages/safetensors'):
             os.chdir('/usr/local/lib/python3.9/dist-packages')
@@ -141,7 +141,7 @@ def downloadmodel_pth(CKPT_Path):
       
   else:
     while not os.path.exists(str(CKPT_Path)):
-       print('Wrong path, use the colab file explorer to copy the path')
+       print('Wrong path, use the file explorer to copy the path')
        time.sleep(5)
        
        
@@ -205,7 +205,7 @@ def sess(Session_Name, Session_Link_optional, MODEL_NAME):
     WORKSPACE='/notebooks/Fast-Dreambooth'
 
     if Session_Link_optional !="":
-      print('Downloading session...')
+      print('Downloading session...')
 
       if Session_Link_optional != "":
         if not os.path.exists(str(WORKSPACE+'/Sessions')):
@@ -343,11 +343,6 @@ def uplder(Remove_existing_instance_images, Crop_images, Crop_size, IMAGES_FOLDE
 
 def upld(Remove_existing_instance_images, Crop_images, Crop_size, IMAGES_FOLDER_OPTIONAL, INSTANCE_DIR, CAPTIONS_DIR, uploader, ren):
 
-
-    if os.path.exists(CAPTIONS_DIR+"off"):
-      call('mv '+CAPTIONS_DIR+"off"+' '+CAPTIONS_DIR, shell=True)
-      time.sleep(2)    
-
     if Remove_existing_instance_images:
         if os.path.exists(str(INSTANCE_DIR)):
             call("rm -r " +INSTANCE_DIR, shell=True)
@@ -451,11 +446,7 @@ def upld(Remove_existing_instance_images, Crop_images, Crop_size, IMAGES_FOLDER_
 
 
 def caption(CAPTIONS_DIR, INSTANCE_DIR):
-
-  if os.path.exists(CAPTIONS_DIR+"off"):
-    call('mv '+CAPTIONS_DIR+"off"+' '+CAPTIONS_DIR, shell=True)
-    time.sleep(2)    
-    
+   
   paths=""
   out=""
   widgets_l=""
@@ -536,10 +527,6 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
         print('No model found, use the "Model Download" cell to download a model.')
         time.sleep(5) 
 
-    if os.path.exists(CAPTIONS_DIR+"off"):
-       call('mv '+CAPTIONS_DIR+"off"+' '+CAPTIONS_DIR, shell=True)
-       time.sleep(2)    
-
     MODELT_NAME=MODEL_NAME
 
     Seed=random.randint(1, 999999)
@@ -605,6 +592,7 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
     def dump_only_textenc(trnonltxt, MODELT_NAME, INSTANCE_DIR, OUTPUT_DIR, PT, Seed, precision, Training_Steps):
         call('accelerate launch /notebooks/diffusers/examples/dreambooth/train_dreambooth_pps.py \
         '+trnonltxt+' \
+        '+extrnlcptn+' \
         --train_text_encoder \
         --image_captions_filename \
         --dump_only_text_encoder \
@@ -619,14 +607,14 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
         --gradient_accumulation_steps=1 --gradient_checkpointing \
         --use_8bit_adam \
         --learning_rate='+str(Text_Encoder_Learning_Rate)+' \
-        --lr_scheduler="polynomial" \
+        --lr_scheduler="linear" \
         --lr_warmup_steps=0 \
         --max_train_steps='+str(Training_Steps), shell=True)
         
     def train_only_unet(stp, stpsv, SESSION_DIR, MODELT_NAME, INSTANCE_DIR, OUTPUT_DIR, Text_Encoder_Training_Steps, PT, Seed, Resolution, Style, extrnlcptn, precision, Training_Steps):
         clear_output()
         if resuming=="Yes":
-          print('Resuming Training...')    
+          print('Resuming Training...')
         print('Training the UNet...')
         call('accelerate launch /notebooks/diffusers/examples/dreambooth/train_dreambooth_pps.py \
         '+Style+' \
@@ -648,7 +636,7 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
         --gradient_accumulation_steps=1 '+GCUNET+' \
         --use_8bit_adam \
         --learning_rate='+str(UNet_Learning_Rate)+' \
-        --lr_scheduler="polynomial" \
+        --lr_scheduler="linear" \
         --lr_warmup_steps=0 \
         --max_train_steps='+str(Training_Steps), shell=True)
 
@@ -684,7 +672,7 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
     if UNet_Training_Steps!=0:
       train_only_unet(stp, stpsv, SESSION_DIR, MODELT_NAME, INSTANCE_DIR, OUTPUT_DIR, Text_Encoder_Training_Steps, PT, Seed, Resolution, Style, extrnlcptn, precision, Training_Steps=UNet_Training_Steps)
 
-    if UNet_Training_Steps==0 and Text_Encoder_Concept_Training_Steps==0 and External_Captions :
+    if UNet_Training_Steps==0 and Text_Encoder_Concept_Training_Steps==0 and Text_Encoder_Training_Steps==0 :
       print('Nothing to do')
     else:
         if os.path.exists(OUTPUT_DIR+'/unet/diffusion_pytorch_model.bin'):
@@ -798,7 +786,7 @@ def test(Custom_Path, Previous_Session_Name, Session_Name, User, Password, Use_l
     os.chdir('/notebooks/sd/stable-diffusion-webui')
     clear_output()
 
-    configf="--disable-console-progressbars --no-half-vae --disable-safe-unpickle --api --xformers --medvram --skip-version-check --ckpt "+path_to_trained_model+" "+auth+" "+share
+    configf="--disable-console-progressbars --no-half-vae --disable-safe-unpickle --api --xformers --enable-insecure-extension-access --medvram --skip-version-check --ckpt "+path_to_trained_model+" "+auth+" "+share
     
     return configf
 
@@ -885,7 +873,7 @@ def hf(Name_of_your_concept, Save_concept_to, hf_token_write, INSTANCE_NAME, OUT
         br="Uploading to HuggingFace : " '|'+'█' * prg + ' ' * (25-prg)+'| ' +str(prg*4)+ "%"
         return br
 
-    print("Loading...")
+    print("Loading...")
 
 
     os.chdir(OUTPUT_DIR)
@@ -893,7 +881,7 @@ def hf(Name_of_your_concept, Save_concept_to, hf_token_write, INSTANCE_NAME, OUT
     call('rm model_index.json', shell=True)
     call('git init', shell=True)
     call('git lfs install --system --skip-repo', shell=True)
-    call('git remote add -f origin  "https://USER:'+hf_token+'@huggingface.co/runwayml/stable-diffusion-v1-5"', shell=True)
+    call('git remote add -f origin https://huggingface.co/runwayml/stable-diffusion-v1-5', shell=True)
     call('git config core.sparsecheckout true', shell=True)
     call('echo -e "\nfeature_extractor\nsafety_checker\nmodel_index.json" > .git/info/sparse-checkout', shell=True)
     call('git pull origin main', shell=True)
@@ -909,10 +897,8 @@ def hf(Name_of_your_concept, Save_concept_to, hf_token_write, INSTANCE_NAME, OUT
     - text-to-image
     - stable-diffusion
     ---
-    ### {Name_of_your_concept} Dreambooth model trained by {api.whoami(token=hf_token)["name"]} with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
+    ### {Name_of_your_concept} Dreambooth model trained by {api.whoami(token=hf_token)["name"]} with TheLastBen's fast-DreamBooth notebook
 
-    Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb)
-    Or you can run your new concept via `diffusers` [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb)
     '''
     #Save the readme to a file
     readme_file = open("README.md", "w")