ford442 commited on
Commit
e9b19af
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1 Parent(s): 4e32b83

Update app.py

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Files changed (1) hide show
  1. app.py +6 -4
app.py CHANGED
@@ -18,7 +18,7 @@ from diffusers import AutoencoderKL, StableDiffusionXLPipeline, EulerAncestralDi
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  from typing import Tuple
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  #from transformers import AutoTokenizer, AutoModelForCausalLM
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  import paramiko
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-
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  #os.system("chmod +x ./cusparselt.sh")
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  #os.system("./cusparselt.sh")
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  #os.system("chmod +x ./cudnn.sh")
@@ -204,8 +204,8 @@ def generate(
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  options["use_resolution_binning"] = True
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  images = []
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- with torch.no_grad():
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- for i in range(0, num_images, BATCH_SIZE):
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  batch_options = options.copy()
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  batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
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  if "negative_prompt" in batch_options:
@@ -215,6 +215,8 @@ def generate(
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  images[0].save(sd_image_path,optimize=False,compress_level=0)
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  upload_to_ftp(sd_image_path)
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  image_paths = [save_image(img) for img in images]
 
 
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  return image_paths, seed
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  def generate_cpu(
@@ -238,7 +240,7 @@ def generate_cpu(
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  pipe.to("cpu")
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  seed = int(randomize_seed_fn(seed, randomize_seed))
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- generator = torch.Generator(device='cpu').manual_seed(seed)
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  prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
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  from typing import Tuple
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  #from transformers import AutoTokenizer, AutoModelForCausalLM
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  import paramiko
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+ import gc
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  #os.system("chmod +x ./cusparselt.sh")
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  #os.system("./cusparselt.sh")
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  #os.system("chmod +x ./cudnn.sh")
 
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  options["use_resolution_binning"] = True
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  images = []
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+ #with torch.no_grad():
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+ for i in range(0, num_images, BATCH_SIZE):
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  batch_options = options.copy()
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  batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
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  if "negative_prompt" in batch_options:
 
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  images[0].save(sd_image_path,optimize=False,compress_level=0)
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  upload_to_ftp(sd_image_path)
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  image_paths = [save_image(img) for img in images]
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+ torch.cuda.empty_cache()
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+ gc.collect()
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  return image_paths, seed
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  def generate_cpu(
 
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  pipe.to("cpu")
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  seed = int(randomize_seed_fn(seed, randomize_seed))
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+ generator = torch.Generator(device='cuda').manual_seed(seed)
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  prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
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