Update Scripts/mainpaperspacev2.py

Scripts/mainpaperspacev2.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')
@@ -142,7 +142,7 @@ def downloadmodel_pthv2(CKPT_Path, Custom_Model_Version):
       
   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')
        os.chdir('/notebooks')
        time.sleep(5)
   
@@ -219,7 +219,7 @@ def sessv2(Session_Name, Session_Link_optional, Model_Version, MODEL_NAMEv2):
     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')):
@@ -363,10 +363,6 @@ 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)
@@ -469,11 +465,7 @@ 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=""
@@ -555,10 +547,6 @@ def dbtrainv2(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Enc
         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_NAMEv2
 
     Seed=random.randint(1, 999999)
@@ -624,6 +612,7 @@ def dbtrainv2(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Enc
     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 \
@@ -638,7 +627,7 @@ def dbtrainv2(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Enc
         --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)
         
@@ -667,7 +656,7 @@ def dbtrainv2(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Enc
         --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)
 
@@ -703,7 +692,7 @@ def dbtrainv2(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Enc
     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'):
@@ -817,7 +806,7 @@ 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
       
@@ -903,14 +892,14 @@ def hfv2(Name_of_your_concept, Save_concept_to, hf_token_write, INSTANCE_NAME, O
         br="Uploading to HuggingFace : " '|'+'█' * prg + ' ' * (25-prg)+'| ' +str(prg*4)+ "%"
         return br
 
-    print("Loading...")
+    print("Loading...")
 
     os.chdir(OUTPUT_DIR)
     call('rm -r feature_extractor .git', shell=True)
     clear_output()
     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/stabilityai/stable-diffusion-2-1"', shell=True)
+    call('git remote add -f origin https://huggingface.co/stabilityai/stable-diffusion-2-1', shell=True)
     call('git config core.sparsecheckout true', shell=True)
     call('echo -e "\nfeature_extractor" > .git/info/sparse-checkout', shell=True)
     call('git pull origin main', shell=True)
@@ -926,9 +915,8 @@ def hfv2(Name_of_your_concept, Save_concept_to, hf_token_write, INSTANCE_NAME, O
     - 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)    
     '''
     #Save the readme to a file
     readme_file = open("README.md", "w")