| 84 | |
| 85 | |
| 86 | class MetricLogger(object): |
| 87 | def __init__(self, delimiter="\t"): |
| 88 | self.meters = defaultdict(SmoothedValue) |
| 89 | self.delimiter = delimiter |
| 90 | |
| 91 | def update(self, **kwargs): |
| 92 | for k, v in kwargs.items(): |
| 93 | if v is None: |
| 94 | continue |
| 95 | if isinstance(v, torch.Tensor): |
| 96 | v = v.item() |
| 97 | assert isinstance(v, (float, int)) |
| 98 | self.meters[k].update(v) |
| 99 | |
| 100 | def __getattr__(self, attr): |
| 101 | if attr in self.meters: |
| 102 | return self.meters[attr] |
| 103 | if attr in self.__dict__: |
| 104 | return self.__dict__[attr] |
| 105 | raise AttributeError("'{}' object has no attribute '{}'".format( |
| 106 | type(self).__name__, attr)) |
| 107 | |
| 108 | def __str__(self): |
| 109 | loss_str = [] |
| 110 | for name, meter in self.meters.items(): |
| 111 | loss_str.append( |
| 112 | "{}: {}".format(name, str(meter)) |
| 113 | ) |
| 114 | return self.delimiter.join(loss_str) |
| 115 | |
| 116 | def synchronize_between_processes(self): |
| 117 | for meter in self.meters.values(): |
| 118 | meter.synchronize_between_processes() |
| 119 | |
| 120 | def add_meter(self, name, meter): |
| 121 | self.meters[name] = meter |
| 122 | |
| 123 | def log_every(self, iterable, print_freq, header=None): |
| 124 | i = 0 |
| 125 | if not header: |
| 126 | header = '' |
| 127 | start_time = time.time() |
| 128 | end = time.time() |
| 129 | iter_time = SmoothedValue(fmt='{avg:.4f}') |
| 130 | data_time = SmoothedValue(fmt='{avg:.4f}') |
| 131 | space_fmt = ':' + str(len(str(len(iterable)))) + 'd' |
| 132 | log_msg = [ |
| 133 | header, |
| 134 | '[{0' + space_fmt + '}/{1}]', |
| 135 | 'eta: {eta}', |
| 136 | '{meters}', |
| 137 | 'time: {time}', |
| 138 | 'data: {data}' |
| 139 | ] |
| 140 | if torch.cuda.is_available(): |
| 141 | log_msg.append('max mem: {memory:.0f}') |
| 142 | log_msg = self.delimiter.join(log_msg) |
| 143 | MB = 1024.0 * 1024.0 |
nothing calls this directly
no outgoing calls
no test coverage detected