from config import howManyModelsToUse,num_models,max_images,inference_timeout,MAX_SEED,thePrompt,preSetPrompt,negPreSetPrompt def load_fn(models): global models_load models_load = {} for model in models: if model not in models_load.keys(): try: m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN) except Exception as error: print(error) m = gr.Interface(lambda: None, ['text'], ['image']) models_load.update({model: m}) async def infer(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, timeout=inference_timeout): kwargs = {} if height > 0: kwargs["height"] = height if width > 0: kwargs["width"] = width if steps > 0: kwargs["num_inference_steps"] = steps if cfg > 0: cfg = kwargs["guidance_scale"] = cfg if seed == -1: theSeed = randomize_seed() else: theSeed = seed kwargs["seed"] = theSeed task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, prompt=prompt, negative_prompt=nprompt, **kwargs, token=HF_TOKEN)) await asyncio.sleep(0) try: result = await asyncio.wait_for(task, timeout=timeout) except asyncio.TimeoutError as e: print(e) print(f"infer: Task timed out: {model_str}") if not task.done(): task.cancel() result = None raise Exception(f"Task timed out: {model_str}") from e except Exception as e: print(e) print(f"infer: exception: {model_str}") if not task.done(): task.cancel() result = None raise Exception() from e if task.done() and result is not None and not isinstance(result, tuple): with lock: png_path = model_str.replace("/", "_") + " - " + get_current_time() + "_" + str(theSeed) + ".png" image = save_image(result, png_path, model_str, prompt, nprompt, height, width, steps, cfg, theSeed) return image return None def gen_fn(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1): try: loop = asyncio.new_event_loop() result = loop.run_until_complete(infer(model_str, prompt, nprompt, height, width, steps, cfg, seed, inference_timeout)) except (Exception, asyncio.CancelledError) as e: print(e) print(f"gen_fn: Task aborted: {model_str}") result = None raise gr.Error(f"Task aborted: {model_str}, Error: {e}") finally: loop.close() return result