Spaces:
Runtime error
Runtime error
Speed Increased by loading pipeline
Browse filesI increased speed of this demo by loading pipeline once instead of each generation.
app.py
CHANGED
@@ -33,11 +33,10 @@ ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
|
|
33 |
|
34 |
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
|
35 |
|
36 |
-
|
37 |
-
|
38 |
-
|
39 |
-
|
40 |
-
return StableDiffusion3Img2ImgPipeline.from_pretrained(model_path, torch_dtype=torch.float16)
|
41 |
|
42 |
def save_image(img):
|
43 |
unique_name = str(uuid.uuid4()) + ".png"
|
@@ -66,15 +65,13 @@ def generate(
|
|
66 |
use_resolution_binning: bool = True,
|
67 |
progress=gr.Progress(track_tqdm=True),
|
68 |
):
|
69 |
-
pipe = load_pipeline("text2img")
|
70 |
-
pipe.to(device)
|
71 |
seed = int(randomize_seed_fn(seed, randomize_seed))
|
72 |
generator = torch.Generator().manual_seed(seed)
|
73 |
|
74 |
if not use_negative_prompt:
|
75 |
negative_prompt = None # type: ignore
|
76 |
|
77 |
-
output =
|
78 |
prompt=prompt,
|
79 |
negative_prompt=negative_prompt,
|
80 |
width=width,
|
@@ -104,8 +101,6 @@ def img2img_generate(
|
|
104 |
use_resolution_binning: bool = True,
|
105 |
progress=gr.Progress(track_tqdm=True),
|
106 |
):
|
107 |
-
pipe = load_pipeline("img2img")
|
108 |
-
pipe.to(device)
|
109 |
seed = int(randomize_seed_fn(seed, randomize_seed))
|
110 |
generator = torch.Generator().manual_seed(seed)
|
111 |
|
@@ -114,7 +109,7 @@ def img2img_generate(
|
|
114 |
|
115 |
init_image = init_image.resize((768, 768))
|
116 |
|
117 |
-
output =
|
118 |
prompt=prompt,
|
119 |
image=init_image,
|
120 |
negative_prompt=negative_prompt,
|
|
|
33 |
|
34 |
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
|
35 |
|
36 |
+
pipe_t2i = StableDiffusion3Pipeline.from_pretrained(model_path, torch_dtype=torch.float16)
|
37 |
+
pipe_t2i.to(device)
|
38 |
+
pipe_i2i = StableDiffusion3Img2ImgPipeline.from_pretrained(model_path, torch_dtype=torch.float16)
|
39 |
+
pipe_i2i.tp(device)
|
|
|
40 |
|
41 |
def save_image(img):
|
42 |
unique_name = str(uuid.uuid4()) + ".png"
|
|
|
65 |
use_resolution_binning: bool = True,
|
66 |
progress=gr.Progress(track_tqdm=True),
|
67 |
):
|
|
|
|
|
68 |
seed = int(randomize_seed_fn(seed, randomize_seed))
|
69 |
generator = torch.Generator().manual_seed(seed)
|
70 |
|
71 |
if not use_negative_prompt:
|
72 |
negative_prompt = None # type: ignore
|
73 |
|
74 |
+
output = pipe_t2i(
|
75 |
prompt=prompt,
|
76 |
negative_prompt=negative_prompt,
|
77 |
width=width,
|
|
|
101 |
use_resolution_binning: bool = True,
|
102 |
progress=gr.Progress(track_tqdm=True),
|
103 |
):
|
|
|
|
|
104 |
seed = int(randomize_seed_fn(seed, randomize_seed))
|
105 |
generator = torch.Generator().manual_seed(seed)
|
106 |
|
|
|
109 |
|
110 |
init_image = init_image.resize((768, 768))
|
111 |
|
112 |
+
output = pipe_i2i(
|
113 |
prompt=prompt,
|
114 |
image=init_image,
|
115 |
negative_prompt=negative_prompt,
|