(self, loader, preprocess: Preprocess=None, queue_max_size=2)
| 75 | class _PreprocessSingleProcessDataLoaderIter(_BaseDataLoaderIter): |
| 76 | |
| 77 | def __init__(self, loader, preprocess: Preprocess=None, queue_max_size=2): |
| 78 | self._preprocess = preprocess |
| 79 | if self._preprocess is not None and self._preprocess.has_cpu_preprocess(): |
| 80 | org_create_fetcher = _DatasetKind.create_fetcher |
| 81 | _DatasetKind.create_fetcher = _create_fetcher_proxy(org_create_fetcher, self._preprocess) |
| 82 | |
| 83 | super(_PreprocessSingleProcessDataLoaderIter, self).__init__(loader) |
| 84 | |
| 85 | self._dataset_fetcher = _DatasetKind.create_fetcher( |
| 86 | self._dataset_kind, self._dataset, self._auto_collation, self._collate_fn, self._drop_last) |
| 87 | |
| 88 | if self._preprocess is not None and self._preprocess.has_cpu_preprocess(): |
| 89 | _DatasetKind.create_fetcher = org_create_fetcher |
| 90 | |
| 91 | self._timeout = self._timeout if self._timeout > 0 else (12 * _utils.MP_STATUS_CHECK_INTERVAL) |
| 92 | |
| 93 | if self._preprocess is not None and self._preprocess.has_gpu_preprocess(): |
| 94 | self._stopped = False |
| 95 | self._stream = torch.cuda.Stream() |
| 96 | print(f"xxxxxx _PreprocessSingleProcessDataLoaderIter queue_max_size: {queue_max_size}") |
| 97 | self._data_queue = queue.Queue(maxsize=queue_max_size) |
| 98 | self._device_id = torch.cuda.current_device() |
| 99 | self._preprocess_thread_done_event = threading.Event() |
| 100 | self._preprocess_thread = threading.Thread(target=self._preprocess_loop) |
| 101 | self._preprocess_thread.daemon = True |
| 102 | self._preprocess_thread.start() |
| 103 | |
| 104 | def _preprocess_loop(self): |
| 105 | # torch.set_num_threads(1) |
nothing calls this directly
no test coverage detected