Update app.py

app.py

@@ -6,6 +6,7 @@
 # copies of the Software, and to permit persons to whom the Software is
 import spaces
 import os
+os.environ["SAFETENSORS_FAST_GPU"] = "1"
 
 #import subprocess
 #subprocess.run(['sh', './conda.sh'])
@@ -59,6 +60,7 @@ from image_gen_aux import UpscaleWithModel
 import torch
 #import torch._dynamo
 #torch._dynamo.list_backends()
+import time 
 
 torch.backends.cuda.matmul.allow_tf32 = False
 torch.backends.cuda.matmul.allow_bf16_reduced_precision_reduction = False
@@ -380,8 +382,7 @@ def generate_30(
     filename = pyx.uploadNote(prompt,num_inference_steps,guidance_scale,timestamp)
     pyx.upload_to_ftp(filename) 
     batch_options = options.copy()
-    with torch.inference_mode():
-        rv_image = pipe(**batch_options).images[0]
+    rv_image = pipe(**batch_options).images[0]
     sd_image_path = f"rv_C_{timestamp}.png"
     rv_image.save(sd_image_path,optimize=False,compress_level=0)
     pyx.upload_to_ftp(sd_image_path)    
@@ -429,8 +430,8 @@ def generate_60(
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     uploadNote(prompt,num_inference_steps,guidance_scale,timestamp)
     batch_options = options.copy()
-    with torch.inference_mode():
-        rv_image = pipe(**batch_options).images[0]
+    time.sleep(2)
+    rv_image = pipe(**batch_options).images[0]
     sd_image_path = f"rv_C_{timestamp}.png"
     rv_image.save(sd_image_path,optimize=False,compress_level=0)
     upload_to_ftp(sd_image_path)    
@@ -471,8 +472,7 @@ def generate_90(
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     uploadNote(prompt,num_inference_steps,guidance_scale,timestamp)
     batch_options = options.copy()
-    with torch.inference_mode():
-        rv_image = pipe(**batch_options).images[0]
+    rv_image = pipe(**batch_options).images[0]
     sd_image_path = f"rv_C_{timestamp}.png"
     rv_image.save(sd_image_path,optimize=False,compress_level=0)
     upload_to_ftp(sd_image_path)