(self, dataset, batch_size=1, shuffle=False, sampler=None, batch_sampler=None,
num_workers=0, collate_fn=default_collate, pin_memory=False, drop_last=False,
timeout=0, worker_init_fn=None)
| 381 | """ |
| 382 | |
| 383 | def __init__(self, dataset, batch_size=1, shuffle=False, sampler=None, batch_sampler=None, |
| 384 | num_workers=0, collate_fn=default_collate, pin_memory=False, drop_last=False, |
| 385 | timeout=0, worker_init_fn=None): |
| 386 | self.dataset = dataset |
| 387 | self.batch_size = batch_size |
| 388 | self.num_workers = num_workers |
| 389 | self.collate_fn = collate_fn |
| 390 | self.pin_memory = pin_memory |
| 391 | self.drop_last = drop_last |
| 392 | self.timeout = timeout |
| 393 | self.worker_init_fn = worker_init_fn |
| 394 | |
| 395 | if timeout < 0: |
| 396 | raise ValueError('timeout option should be non-negative') |
| 397 | |
| 398 | if batch_sampler is not None: |
| 399 | if batch_size > 1 or shuffle or sampler is not None or drop_last: |
| 400 | raise ValueError('batch_sampler is mutually exclusive with ' |
| 401 | 'batch_size, shuffle, sampler, and drop_last') |
| 402 | |
| 403 | if sampler is not None and shuffle: |
| 404 | raise ValueError('sampler is mutually exclusive with shuffle') |
| 405 | |
| 406 | if self.num_workers < 0: |
| 407 | raise ValueError('num_workers cannot be negative; ' |
| 408 | 'use num_workers=0 to disable multiprocessing.') |
| 409 | |
| 410 | if batch_sampler is None: |
| 411 | if sampler is None: |
| 412 | if shuffle: |
| 413 | sampler = RandomSampler(dataset) |
| 414 | else: |
| 415 | sampler = SequentialSampler(dataset) |
| 416 | batch_sampler = BatchSampler(sampler, batch_size, drop_last) |
| 417 | |
| 418 | self.sampler = sampler |
| 419 | self.batch_sampler = batch_sampler |
| 420 | |
| 421 | def __iter__(self): |
| 422 | return DataLoaderIter(self) |
nothing calls this directly
no test coverage detected