Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
|
@@ -6,7 +6,6 @@ import torch
|
|
| 6 |
import time
|
| 7 |
from diffusers import DiffusionPipeline, AutoencoderTiny
|
| 8 |
from custom_pipeline import FluxWithCFGPipeline
|
| 9 |
-
from diffusers.hooks import apply_group_offloading
|
| 10 |
|
| 11 |
# --- Torch Optimizations ---
|
| 12 |
torch.backends.cuda.matmul.allow_tf32 = True
|
|
@@ -31,46 +30,11 @@ pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtyp
|
|
| 31 |
|
| 32 |
pipe.to(device)
|
| 33 |
|
| 34 |
-
group_offloading = None
|
| 35 |
-
|
| 36 |
# --- Inference Function ---
|
| 37 |
@spaces.GPU
|
| 38 |
def generate_image(prompt: str, seed: int = 42, width: int = DEFAULT_WIDTH, height: int = DEFAULT_HEIGHT, randomize_seed: bool = False, num_inference_steps: int = DEFAULT_INFERENCE_STEPS, is_enhance: bool = False):
|
| 39 |
"""Generates an image using the FLUX pipeline with error handling."""
|
| 40 |
|
| 41 |
-
global group_offloading
|
| 42 |
-
if not group_offloading:
|
| 43 |
-
apply_group_offloading(
|
| 44 |
-
pipe.transformer,
|
| 45 |
-
offload_type="leaf_level",
|
| 46 |
-
offload_device=torch.device("cpu"),
|
| 47 |
-
onload_device=torch.device("cuda"),
|
| 48 |
-
use_stream=True,
|
| 49 |
-
)
|
| 50 |
-
apply_group_offloading(
|
| 51 |
-
pipe.text_encoder,
|
| 52 |
-
offload_device=torch.device("cpu"),
|
| 53 |
-
onload_device=torch.device("cuda"),
|
| 54 |
-
offload_type="leaf_level",
|
| 55 |
-
use_stream=True,
|
| 56 |
-
)
|
| 57 |
-
apply_group_offloading(
|
| 58 |
-
pipe.text_encoder_2,
|
| 59 |
-
offload_device=torch.device("cpu"),
|
| 60 |
-
onload_device=torch.device("cuda"),
|
| 61 |
-
offload_type="leaf_level",
|
| 62 |
-
use_stream=True,
|
| 63 |
-
)
|
| 64 |
-
apply_group_offloading(
|
| 65 |
-
pipe.vae,
|
| 66 |
-
offload_device=torch.device("cpu"),
|
| 67 |
-
onload_device=torch.device("cuda"),
|
| 68 |
-
offload_type="leaf_level",
|
| 69 |
-
use_stream=True,
|
| 70 |
-
)
|
| 71 |
-
|
| 72 |
-
group_offloading = True
|
| 73 |
-
|
| 74 |
if pipe is None:
|
| 75 |
raise gr.Error("Diffusion pipeline failed to load. Cannot generate images.")
|
| 76 |
|
|
|
|
| 6 |
import time
|
| 7 |
from diffusers import DiffusionPipeline, AutoencoderTiny
|
| 8 |
from custom_pipeline import FluxWithCFGPipeline
|
|
|
|
| 9 |
|
| 10 |
# --- Torch Optimizations ---
|
| 11 |
torch.backends.cuda.matmul.allow_tf32 = True
|
|
|
|
| 30 |
|
| 31 |
pipe.to(device)
|
| 32 |
|
|
|
|
|
|
|
| 33 |
# --- Inference Function ---
|
| 34 |
@spaces.GPU
|
| 35 |
def generate_image(prompt: str, seed: int = 42, width: int = DEFAULT_WIDTH, height: int = DEFAULT_HEIGHT, randomize_seed: bool = False, num_inference_steps: int = DEFAULT_INFERENCE_STEPS, is_enhance: bool = False):
|
| 36 |
"""Generates an image using the FLUX pipeline with error handling."""
|
| 37 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 38 |
if pipe is None:
|
| 39 |
raise gr.Error("Diffusion pipeline failed to load. Cannot generate images.")
|
| 40 |
|