File size: 4,283 Bytes
c9ea4f0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
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):
    @wraps(func)
    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):
    @wraps(func)
    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.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