aa

app.py

@@ -1,23 +1,34 @@
 import gradio as gr
 import requests
 import os
+import torch as th
+from torch import autocast
+from diffusers import StableDiffusionPipeline
 
-#fn_index=1
-# inputs:f
-# |-textbox
-# |-slider
-# |-slider
-# |-slider
-# |-slider
-# outputs:
-# |-gallery
-#API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
 HF_TOKEN = os.environ.get("diffuse_new") or True
+has_cuda = th.cuda.is_available()
+device = th.device('cpu' if not th.cuda.is_available() else 'cuda')
+print(f"device is :{device}")
+
+# init stable diffusion model
+pipe = StableDiffusionPipeline.from_pretrained(
+    "CompVis/stable-diffusion-v1-4",
+    use_auth_token= HF_TOKEN).to(device)
+
+def get_sd(translated_txt):
+    scale=7.5 
+    steps=45
+    with autocast('cpu' if not th.cuda.is_available() else 'cuda'):
+        image = pipe(translated_txt, guidance_scale=scale, num_inference_steps=steps)["sample"][0]
+        return image
+
+#API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
+#HF_TOKEN = os.environ.get("diffuse_new") or True
 #HF_TOKEN = os.environ["HF_TOKEN"]
 #headers = {"Authorization": f"Bearer {HF_TOKEN}"}
 sd_inf = gr.Blocks.load(name="spaces/stabilityai/stable-diffusion", use_auth_token=HF_TOKEN )#'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')
 
-def get_sd(translated_txt):
+def get_sd_old(translated_txt):
   print("******** Inside get_SD ********")
   print(f"translated_txt is : {translated_txt}")
   #sd_inf = gr.Blocks.load(name="spaces/stabilityai/stable-diffusion", use_auth_token='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')