update requirements .py and .ipynb

Deforum_Stable_Diffusion.py

@@ -47,7 +47,7 @@ Please read the full license here: https://huggingface.co/spaces/CompVis/stable-
 import subprocess
 sub_p_res = subprocess.run(['nvidia-smi', '--query-gpu=name,memory.total,memory.free', '--format=csv,noheader'], stdout=subprocess.PIPE).stdout.decode('utf-8')
 print("NVIDIA GPU:")
-print(f"  {sub_p_res[:-1]}")
+print(f"{sub_p_res[:-1]}")
 
 # %%
 # !! {"metadata":{
@@ -82,8 +82,8 @@ import os
 os.makedirs(models_path, exist_ok=True)
 os.makedirs(output_path, exist_ok=True)
 
-print(f"  models_path: {models_path}")
-print(f"  output_path: {output_path}")
+print(f"models_path: {models_path}")
+print(f"output_path: {output_path}")
 
 # %%
 # !! {"metadata":{
@@ -168,6 +168,9 @@ from ldm.util import instantiate_from_config
 from ldm.models.diffusion.ddim import DDIMSampler
 from ldm.models.diffusion.plms import PLMSSampler
 
+from transformers import logging
+logging.set_verbosity_error()
+
 def sanitize(prompt):
     whitelist = set('abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ')
     tmp = ''.join(filter(whitelist.__contains__, prompt))
@@ -1017,8 +1020,8 @@ else:
     ckpt_valid = False
     
 print("Config and Model Location:")
-print(f"  {ckpt_config_path}")
-print(f"  {ckpt_path}")
+print(f"{ckpt_config_path}")
+print(f"{ckpt_path}")
 
 if check_sha256 and model_checkpoint != "custom" and ckpt_valid:
     import hashlib
@@ -1036,21 +1039,23 @@ if check_sha256 and model_checkpoint != "custom" and ckpt_valid:
 if ckpt_valid:
     print(f"..using {ckpt_path}")
 
-def load_model_from_config(config, ckpt, verbose=False, device='cuda', half_precision=True):
+def load_model_from_config(config, ckpt, verbose=False, device='cuda', half_precision=True,print_flag=False):
     map_location = "cuda" #@param ["cpu", "cuda"]
     print(f"..loading model")
     pl_sd = torch.load(ckpt, map_location=map_location)
     if "global_step" in pl_sd:
-        print(f"Global Step: {pl_sd['global_step']}")
+    	if print_flag:
+    	    print(f"Global Step: {pl_sd['global_step']}")
     sd = pl_sd["state_dict"]
     model = instantiate_from_config(config.model)
     m, u = model.load_state_dict(sd, strict=False)
-    if len(m) > 0 and verbose:
-        print("missing keys:")
-        print(m)
-    if len(u) > 0 and verbose:
-        print("unexpected keys:")
-        print(u)
+    if print_flag:
+    	if len(m) > 0 and verbose:
+            print("missing keys:")
+            print(m)
+    	if len(u) > 0 and verbose:
+            print("unexpected keys:")
+            print(u)
 
     if half_precision:
         model = model.half().to(device)