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#!/usr/bin/env python3
import logging
import torch
import diffusers
log = logging.getLogger("test")
log.setLevel(logging.DEBUG)
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s | %(name)s | %(levelname)s | %(module)s | %(message)s')
log.info(f'loaded: torch={torch.__version__} diffusers={diffusers.__version__}')
prompt_positive = 'futuristic city'
prompt_negative = 'grass'
seeds = [42]
model_path = "runwayml/stable-diffusion-v1-5"
embedding_path_ok = "sd15_text_inv.pt"
# embedding_path_err = "./sd21_text_inv.pt"
device = 'cuda:0'
load_args = {
"low_cpu_mem_usage": True,
"torch_dtype": torch.float16,
"variant": 'fp16',
"safety_checker": None,
"load_safety_checker": False,
# "local_files_only": False,
}
pipe = diffusers.StableDiffusionPipeline.from_pretrained(model_path, **load_args)
pipe.set_progress_bar_config(bar_format='Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m', ncols=80, colour='#327fba')
pipe.enable_model_cpu_offload()
args = {
'prompt': [prompt_positive],
'negative_prompt': [prompt_negative],
'guidance_scale': 6,
'generator': [torch.Generator(device).manual_seed(s) for s in seeds],
'output_type': 'pil',
'num_inference_steps': 10,
'eta': 0.0,
'guidance_rescale': 0.7,
'height': 512,
'width': 512,
}
# pipe.load_lora_weights(embedding_path_ok, **load_args)
try:
pipe.load_lora_weights(embedding_path_ok, **load_args)
except Exception as e:
log.error(f'failed to load embeddings: {e}')
output = pipe(**args)
log.info(f'output: {output}') # this works fine
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