| 338 | |
| 339 | |
| 340 | class MetricLogger(object): |
| 341 | def __init__(self, delimiter="\t"): |
| 342 | self.meters = defaultdict(SmoothedValue) |
| 343 | self.delimiter = delimiter |
| 344 | |
| 345 | def update(self, **kwargs): |
| 346 | for k, v in kwargs.items(): |
| 347 | if isinstance(v, torch.Tensor): |
| 348 | v = v.item() |
| 349 | assert isinstance(v, (float, int)) |
| 350 | self.meters[k].update(v) |
| 351 | |
| 352 | def __getattr__(self, attr): |
| 353 | if attr in self.meters: |
| 354 | return self.meters[attr] |
| 355 | if attr in self.__dict__: |
| 356 | return self.__dict__[attr] |
| 357 | raise AttributeError("'{}' object has no attribute '{}'".format( |
| 358 | type(self).__name__, attr)) |
| 359 | |
| 360 | def __str__(self): |
| 361 | loss_str = [] |
| 362 | for name, meter in self.meters.items(): |
| 363 | loss_str.append( |
| 364 | "{}: {}".format(name, str(meter)) |
| 365 | ) |
| 366 | return self.delimiter.join(loss_str) |
| 367 | |
| 368 | def add_meter(self, name, meter): |
| 369 | self.meters[name] = meter |
| 370 | |
| 371 | def log_every(self, iterable, print_freq, header=None): |
| 372 | i = 0 |
| 373 | if not header: |
| 374 | header = '' |
| 375 | |
| 376 | start_time = time.time() |
| 377 | end = time.time() |
| 378 | iter_time = SmoothedValue(fmt='{avg:.6f}') |
| 379 | data_time = SmoothedValue(fmt='{avg:.6f}') |
| 380 | space_fmt = ':' + str(len(str(len(iterable)))) + 'd' |
| 381 | if torch.cuda.is_available(): |
| 382 | log_msg = self.delimiter.join([ |
| 383 | header, |
| 384 | '[{0' + space_fmt + '}/{1}]', |
| 385 | 'eta: {eta}', |
| 386 | '{meters}', |
| 387 | 'time: {time}', |
| 388 | 'data: {data}', |
| 389 | 'mem: {memory:.0f} ' |
| 390 | 'mem reserved: {memory_res:.0f} ' |
| 391 | ]) |
| 392 | else: |
| 393 | log_msg = self.delimiter.join([ |
| 394 | header, |
| 395 | '[{0' + space_fmt + '}/{1}]', |
| 396 | 'eta: {eta}', |
| 397 | '{meters}', |
nothing calls this directly
no outgoing calls
no test coverage detected