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Running
on
Zero
File size: 2,702 Bytes
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from __future__ import annotations
import sys
import gradio as gr
import PIL.Image
import torch
sys.path.append('Attend-and-Excite')
from config import RunConfig
from pipeline_attend_and_excite import AttendAndExcitePipeline
from run import run_on_prompt
from utils.ptp_utils import AttentionStore
class Model:
def __init__(self):
self.device = torch.device(
'cuda:0' if torch.cuda.is_available() else 'cpu')
self.model_id = ''
self.model = None
self.tokenizer = None
self.load_model('CompVis/stable-diffusion-v1-4')
def load_model(self, model_id: str) -> None:
if model_id == self.model_id:
return
self.model = AttendAndExcitePipeline.from_pretrained(model_id).to(
self.device)
self.tokenizer = self.model.tokenizer
self.model_id = model_id
def get_token_table(self, model_id: str, prompt: str):
self.load_model(model_id)
tokens = [
self.tokenizer.decode(t)
for t in self.tokenizer(prompt)['input_ids']
]
tokens = tokens[1:-1]
return list(enumerate(tokens, start=1))
def run(
self,
model_id: str,
prompt: str,
indices_to_alter_str: str,
seed: int,
apply_attend_and_excite: bool,
num_steps: int,
guidance_scale: float,
scale_factor: int = 20,
thresholds: dict[int, float] = {
10: 0.5,
20: 0.8
},
max_iter_to_alter: int = 25,
) -> tuple[list[tuple[int, str]], PIL.Image.Image]:
generator = torch.Generator(device=self.device).manual_seed(seed)
try:
indices_to_alter = list(map(int, indices_to_alter_str.split(',')))
except:
raise gr.Error('Invalid token indices.')
self.load_model(model_id)
token_table = self.get_token_table(model_id, prompt)
controller = AttentionStore()
config = RunConfig(prompt=prompt,
n_inference_steps=num_steps,
guidance_scale=guidance_scale,
run_standard_sd=not apply_attend_and_excite,
scale_factor=scale_factor,
thresholds=thresholds,
max_iter_to_alter=max_iter_to_alter)
image = run_on_prompt(model=self.model,
prompt=[prompt],
controller=controller,
token_indices=indices_to_alter,
seed=generator,
config=config)
return token_table, image
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