This commit is contained in:
Qing
2023-02-07 21:00:19 +08:00
parent 3f6bc8fada
commit fbb278298b
3 changed files with 132 additions and 109 deletions

View File

@@ -4,8 +4,14 @@ import PIL.Image
import cv2
import numpy as np
import torch
from diffusers import PNDMScheduler, DDIMScheduler, LMSDiscreteScheduler, EulerDiscreteScheduler, \
EulerAncestralDiscreteScheduler, DPMSolverMultistepScheduler
from diffusers import (
PNDMScheduler,
DDIMScheduler,
LMSDiscreteScheduler,
EulerDiscreteScheduler,
EulerAncestralDiscreteScheduler,
DPMSolverMultistepScheduler,
)
from loguru import logger
from lama_cleaner.model.base import DiffusionInpaintModel
@@ -16,7 +22,7 @@ from lama_cleaner.schema import Config, SDSampler
class CPUTextEncoderWrapper:
def __init__(self, text_encoder, torch_dtype):
self.config = text_encoder.config
self.text_encoder = text_encoder.to(torch.device('cpu'), non_blocking=True)
self.text_encoder = text_encoder.to(torch.device("cpu"), non_blocking=True)
self.text_encoder = self.text_encoder.to(torch.float32, non_blocking=True)
self.torch_dtype = torch_dtype
del text_encoder
@@ -24,7 +30,15 @@ class CPUTextEncoderWrapper:
def __call__(self, x, **kwargs):
input_device = x.device
return [self.text_encoder(x.to(self.text_encoder.device), **kwargs)[0].to(input_device).to(self.torch_dtype)]
return [
self.text_encoder(x.to(self.text_encoder.device), **kwargs)[0]
.to(input_device)
.to(self.torch_dtype)
]
@property
def dtype(self):
return self.torch_dtype
class SD(DiffusionInpaintModel):
@@ -33,18 +47,23 @@ class SD(DiffusionInpaintModel):
def init_model(self, device: torch.device, **kwargs):
from diffusers.pipelines.stable_diffusion import StableDiffusionInpaintPipeline
fp16 = not kwargs.get('no_half', False)
model_kwargs = {"local_files_only": kwargs.get('local_files_only', kwargs['sd_run_local'])}
if kwargs['disable_nsfw'] or kwargs.get('cpu_offload', False):
fp16 = not kwargs.get("no_half", False)
model_kwargs = {
"local_files_only": kwargs.get("local_files_only", kwargs["sd_run_local"])
}
if kwargs["disable_nsfw"] or kwargs.get("cpu_offload", False):
logger.info("Disable Stable Diffusion Model NSFW checker")
model_kwargs.update(dict(
safety_checker=None,
feature_extractor=None,
requires_safety_checker=False
))
model_kwargs.update(
dict(
safety_checker=None,
feature_extractor=None,
requires_safety_checker=False,
)
)
use_gpu = device == torch.device('cuda') and torch.cuda.is_available()
use_gpu = device == torch.device("cuda") and torch.cuda.is_available()
torch_dtype = torch.float16 if use_gpu and fp16 else torch.float32
self.model = StableDiffusionInpaintPipeline.from_pretrained(
self.model_id_or_path,
@@ -57,18 +76,20 @@ class SD(DiffusionInpaintModel):
# https://huggingface.co/docs/diffusers/v0.7.0/en/api/pipelines/stable_diffusion#diffusers.StableDiffusionInpaintPipeline.enable_attention_slicing
self.model.enable_attention_slicing()
# https://huggingface.co/docs/diffusers/v0.7.0/en/optimization/fp16#memory-efficient-attention
if kwargs.get('enable_xformers', False):
if kwargs.get("enable_xformers", False):
self.model.enable_xformers_memory_efficient_attention()
if kwargs.get('cpu_offload', False) and use_gpu:
if kwargs.get("cpu_offload", False) and use_gpu:
# TODO: gpu_id
logger.info("Enable sequential cpu offload")
self.model.enable_sequential_cpu_offload(gpu_id=0)
else:
self.model = self.model.to(device)
if kwargs['sd_cpu_textencoder']:
if kwargs["sd_cpu_textencoder"]:
logger.info("Run Stable Diffusion TextEncoder on CPU")
self.model.text_encoder = CPUTextEncoderWrapper(self.model.text_encoder, torch_dtype)
self.model.text_encoder = CPUTextEncoderWrapper(
self.model.text_encoder, torch_dtype
)
self.callback = kwargs.pop("callback", None)