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| from functools import wraps | |
| import html | |
| import time | |
| from modules import shared, progress, errors, devices, fifo_lock | |
| queue_lock = fifo_lock.FIFOLock() | |
| def wrap_queued_call(func): | |
| def f(*args, **kwargs): | |
| with queue_lock: | |
| res = func(*args, **kwargs) | |
| return res | |
| return f | |
| def wrap_gradio_gpu_call(func, extra_outputs=None): | |
| def f(*args, **kwargs): | |
| # if the first argument is a string that says "task(...)", it is treated as a job id | |
| if args and type(args[0]) == str and args[0].startswith("task(") and args[0].endswith(")"): | |
| id_task = args[0] | |
| progress.add_task_to_queue(id_task) | |
| else: | |
| id_task = None | |
| with queue_lock: | |
| shared.state.begin(job=id_task) | |
| progress.start_task(id_task) | |
| try: | |
| res = func(*args, **kwargs) | |
| progress.record_results(id_task, res) | |
| finally: | |
| progress.finish_task(id_task) | |
| shared.state.end() | |
| return res | |
| return wrap_gradio_call(f, extra_outputs=extra_outputs, add_stats=True) | |
| def wrap_gradio_call(func, extra_outputs=None, add_stats=False): | |
| def f(*args, extra_outputs_array=extra_outputs, **kwargs): | |
| run_memmon = shared.opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled and add_stats | |
| if run_memmon: | |
| shared.mem_mon.monitor() | |
| t = time.perf_counter() | |
| try: | |
| res = list(func(*args, **kwargs)) | |
| except Exception as e: | |
| # When printing out our debug argument list, | |
| # do not print out more than a 100 KB of text | |
| max_debug_str_len = 131072 | |
| message = "Error completing request" | |
| arg_str = f"Arguments: {args} {kwargs}"[:max_debug_str_len] | |
| if len(arg_str) > max_debug_str_len: | |
| arg_str += f" (Argument list truncated at {max_debug_str_len}/{len(arg_str)} characters)" | |
| errors.report(f"{message}\n{arg_str}", exc_info=True) | |
| shared.state.job = "" | |
| shared.state.job_count = 0 | |
| if extra_outputs_array is None: | |
| extra_outputs_array = [None, ''] | |
| error_message = f'{type(e).__name__}: {e}' | |
| res = extra_outputs_array + [f"<div class='error'>{html.escape(error_message)}</div>"] | |
| devices.torch_gc() | |
| shared.state.skipped = False | |
| shared.state.interrupted = False | |
| shared.state.stopping_generation = False | |
| shared.state.job_count = 0 | |
| if not add_stats: | |
| return tuple(res) | |
| elapsed = time.perf_counter() - t | |
| elapsed_m = int(elapsed // 60) | |
| elapsed_s = elapsed % 60 | |
| elapsed_text = f"{elapsed_s:.1f} sec." | |
| if elapsed_m > 0: | |
| elapsed_text = f"{elapsed_m} min. "+elapsed_text | |
| if run_memmon: | |
| mem_stats = {k: -(v//-(1024*1024)) for k, v in shared.mem_mon.stop().items()} | |
| active_peak = mem_stats['active_peak'] | |
| reserved_peak = mem_stats['reserved_peak'] | |
| sys_peak = mem_stats['system_peak'] | |
| sys_total = mem_stats['total'] | |
| sys_pct = sys_peak/max(sys_total, 1) * 100 | |
| toltip_a = "Active: peak amount of video memory used during generation (excluding cached data)" | |
| toltip_r = "Reserved: total amout of video memory allocated by the Torch library " | |
| toltip_sys = "System: peak amout of video memory allocated by all running programs, out of total capacity" | |
| text_a = f"<abbr title='{toltip_a}'>A</abbr>: <span class='measurement'>{active_peak/1024:.2f} GB</span>" | |
| text_r = f"<abbr title='{toltip_r}'>R</abbr>: <span class='measurement'>{reserved_peak/1024:.2f} GB</span>" | |
| text_sys = f"<abbr title='{toltip_sys}'>Sys</abbr>: <span class='measurement'>{sys_peak/1024:.1f}/{sys_total/1024:g} GB</span> ({sys_pct:.1f}%)" | |
| vram_html = f"<p class='vram'>{text_a}, <wbr>{text_r}, <wbr>{text_sys}</p>" | |
| else: | |
| vram_html = '' | |
| # last item is always HTML | |
| res[-1] += f"<div class='performance'><p class='time'>Time taken: <wbr><span class='measurement'>{elapsed_text}</span></p>{vram_html}</div>" | |
| return tuple(res) | |
| return f | |