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hub / github.com/VincentHancoder/SSGD / build_dataloader

Function build_dataloader

mmdet/datasets/builder.py:87–206  ·  view source on GitHub ↗

Build PyTorch DataLoader. In distributed training, each GPU/process has a dataloader. In non-distributed training, there is only one dataloader for all GPUs. Args: dataset (Dataset): A PyTorch dataset. samples_per_gpu (int): Number of training samples on each GPU, i.e.,

(dataset,
                     samples_per_gpu,
                     workers_per_gpu,
                     num_gpus=1,
                     dist=True,
                     shuffle=True,
                     seed=None,
                     runner_type='EpochBasedRunner',
                     persistent_workers=False,
                     class_aware_sampler=None,
                     **kwargs)

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Callers 5

mainFunction · 0.90
mainFunction · 0.90
measure_inference_speedFunction · 0.90
mainFunction · 0.90
train_detectorFunction · 0.90

Calls 9

ClassAwareSamplerClass · 0.85
DistributedSamplerClass · 0.85
GroupSamplerClass · 0.85
digit_versionFunction · 0.85
getMethod · 0.80
popMethod · 0.80

Tested by 3

mainFunction · 0.72
mainFunction · 0.72
mainFunction · 0.72