commit

app.py

@@ -413,8 +413,7 @@ CHECKPOINTS = ESRGANUpscalerCheckpoints(
 
 device = DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 DTYPE = torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float32
-enhancer = ESRGANUpscaler(checkpoints=CHECKPOINTS, device=DEVICE, dtype=DTYPE)
-enhancer.to(device=DEVICE, dtype=DTYPE)
+enhancer = ESRGANUpscaler(checkpoints=CHECKPOINTS, device="cpu", dtype=DTYPE)
 
 # logging
 
@@ -435,8 +434,8 @@ pegasus_name = "google/pegasus-xsum"
 # precision data
 
 seq=512
-width=768
-height=768
+width=1500
+height=1500
 image_steps=8
 img_accu=0
 
@@ -511,7 +510,6 @@ pegasus_model = PegasusForConditionalGeneration.from_pretrained("google/pegasus-
 
 # functionality
 
-@spaces.GPU(duration=180)
 def upscaler(
     input_image: Image.Image,
     prompt: str = "Best-Quality Realistic Genuine Reasonable Highly-Detailed",
@@ -555,7 +553,6 @@ def upscaler(
 
     return enhanced_image
 
-@spaces.GPU(duration=180)
 def summarize_text(
     text, max_length=30, num_beams=4, early_stopping=True
 ):
@@ -573,7 +570,7 @@ def generate_random_string(length):
     characters = str(ascii_letters + digits)
     return ''.join(random.choice(characters) for _ in range(length))
 
-@spaces.GPU(duration=180)
+@spaces.GPU(duration=80)
 def pipe_generate(p1,p2):
     log(f'CALL pipe_generate')
     imgs = image_pipe(