Update Scripts/mainpaperspacev1.py

Scripts/mainpaperspacev1.py

@@ -508,7 +508,7 @@ def caption(CAPTIONS_DIR, INSTANCE_DIR):
   
 
     
-def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encoder_Training_Steps, Text_Encoder_Concept_Training_Steps, Text_Encoder_Learning_Rate, Style_Training, Resolution, MODEL_NAME, SESSION_DIR, INSTANCE_DIR, CONCEPT_DIR, CAPTIONS_DIR, External_Captions,  INSTANCE_NAME, Session_Name, OUTPUT_DIR, PT, resume, Save_Checkpoint_Every_n_Steps, Start_saving_from_the_step, Save_Checkpoint_Every):
+def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encoder_Training_Steps, Text_Encoder_Concept_Training_Steps, Text_Encoder_Learning_Rate, Offset_Noise, Resolution, MODEL_NAME, SESSION_DIR, INSTANCE_DIR, CONCEPT_DIR, CAPTIONS_DIR, External_Captions,  INSTANCE_NAME, Session_Name, OUTPUT_DIR, PT, resume, Save_Checkpoint_Every_n_Steps, Start_saving_from_the_step, Save_Checkpoint_Every):
 
     if os.path.exists(INSTANCE_DIR+"/.ipynb_checkpoints"):
       call('rm -r '+INSTANCE_DIR+'/.ipynb_checkpoints', shell=True)
@@ -536,20 +536,17 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
     MODELT_NAME=MODEL_NAME
 
     Seed=random.randint(1, 999999)
-    
-    Style=""
-    if Style_Training:
-      Style="--Style"
-      
+
+    ofstnse=""
+    if Offset_Noise:
+      ofstnse="--offset_noise"
+
     extrnlcptn=""
     if External_Captions:
       extrnlcptn="--external_captions"      
 
     precision="fp16"
     
-    GCUNET="--gradient_checkpointing"
-    if Resolution<=640:
-      GCUNET=""
 
     resuming=""
     if Resume_Training and os.path.exists(OUTPUT_DIR+'/unet/diffusion_pytorch_model.bin'):
@@ -599,18 +596,20 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
         call('accelerate launch /notebooks/diffusers/examples/dreambooth/train_dreambooth_pps.py \
         '+trnonltxt+' \
         '+extrnlcptn+' \
+        '+ofstnse+' \
         --train_text_encoder \
         --image_captions_filename \
         --dump_only_text_encoder \
         --pretrained_model_name_or_path='+MODELT_NAME+' \
         --instance_data_dir='+INSTANCE_DIR+' \
         --output_dir='+OUTPUT_DIR+' \
+        --captions_dir='+CAPTIONS_DIR+' \
         --instance_prompt='+PT+' \
         --seed='+str(Seed)+' \
-        --resolution=512 \
+        --resolution='+str(Resolution)+' \
         --mixed_precision='+str(precision)+' \
         --train_batch_size=1 \
-        --gradient_accumulation_steps=1 --gradient_checkpointing \
+        --gradient_accumulation_steps=1 \
         --use_8bit_adam \
         --learning_rate='+str(Text_Encoder_Learning_Rate)+' \
         --lr_scheduler="linear" \
@@ -623,8 +622,8 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
           print('Resuming Training...')
         print('Training the UNet...')
         call('accelerate launch /notebooks/diffusers/examples/dreambooth/train_dreambooth_pps.py \
-        '+Style+' \
         '+extrnlcptn+' \
+        '+ofstnse+' \
         --image_captions_filename \
         --train_only_unet \
         --Session_dir='+SESSION_DIR+' \
@@ -633,12 +632,13 @@ def dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encod
         --pretrained_model_name_or_path='+MODELT_NAME+' \
         --instance_data_dir='+INSTANCE_DIR+' \
         --output_dir='+OUTPUT_DIR+' \
+        --captions_dir='+CAPTIONS_DIR+' \
         --instance_prompt='+PT+' \
         --seed='+str(Seed)+' \
         --resolution='+str(Resolution)+' \
         --mixed_precision='+str(precision)+' \
         --train_batch_size=1 \
-        --gradient_accumulation_steps=1 '+GCUNET+' \
+        --gradient_accumulation_steps=1 \
         --use_8bit_adam \
         --learning_rate='+str(UNet_Learning_Rate)+' \
         --lr_scheduler="linear" \