| |
| |
| |
| |
|
|
| from logging import getLogger |
| import torch |
|
|
| _GLOBAL_SEED = 0 |
| logger = getLogger() |
|
|
|
|
| def init_data( |
| batch_size, |
| transform=None, |
| shared_transform=None, |
| data="ImageNet", |
| collator=None, |
| pin_mem=True, |
| num_workers=8, |
| world_size=1, |
| rank=0, |
| root_path=None, |
| image_folder=None, |
| training=True, |
| drop_last=True, |
| subset_file=None, |
| clip_len=None, |
| dataset_fpcs=None, |
| frame_sample_rate=None, |
| duration=None, |
| fps=None, |
| num_clips=1, |
| random_clip_sampling=True, |
| allow_clip_overlap=False, |
| filter_short_videos=False, |
| filter_long_videos=int(1e9), |
| datasets_weights=None, |
| persistent_workers=False, |
| deterministic=True, |
| log_dir=None, |
| ): |
| if data.lower() == "imagenet": |
| from src.datasets.imagenet1k import make_imagenet1k |
|
|
| dataset, data_loader, dist_sampler = make_imagenet1k( |
| transform=transform, |
| batch_size=batch_size, |
| collator=collator, |
| pin_mem=pin_mem, |
| training=training, |
| num_workers=num_workers, |
| world_size=world_size, |
| rank=rank, |
| root_path=root_path, |
| image_folder=image_folder, |
| persistent_workers=persistent_workers, |
| drop_last=drop_last, |
| subset_file=subset_file, |
| ) |
|
|
| elif data.lower() == "videodataset": |
| from src.datasets.video_dataset import make_videodataset |
|
|
| dataset, data_loader, dist_sampler = make_videodataset( |
| data_paths=root_path, |
| batch_size=batch_size, |
| frames_per_clip=clip_len, |
| dataset_fpcs=dataset_fpcs, |
| frame_step=frame_sample_rate, |
| duration=duration, |
| fps=fps, |
| num_clips=num_clips, |
| random_clip_sampling=random_clip_sampling, |
| allow_clip_overlap=allow_clip_overlap, |
| filter_short_videos=filter_short_videos, |
| filter_long_videos=filter_long_videos, |
| shared_transform=shared_transform, |
| transform=transform, |
| datasets_weights=datasets_weights, |
| collator=collator, |
| num_workers=num_workers, |
| pin_mem=pin_mem, |
| persistent_workers=persistent_workers, |
| world_size=world_size, |
| rank=rank, |
| deterministic=deterministic, |
| log_dir=log_dir, |
| ) |
|
|
| return (data_loader, dist_sampler) |
|
|
|
|
| def init_data_miniimagenet( |
| batch_size, |
| path_miniimagenet, |
| transform=None, |
| shared_transform=None, |
| data="ImageNet", |
| collator=None, |
| pin_mem=True, |
| num_workers=8, |
| world_size=1, |
| rank=0, |
| root_path=None, |
| image_folder=None, |
| training=True, |
| drop_last=True, |
| subset_file=None, |
| clip_len=None, |
| dataset_fpcs=None, |
| frame_sample_rate=None, |
| duration=None, |
| fps=None, |
| num_clips=1, |
| random_clip_sampling=True, |
| allow_clip_overlap=False, |
| filter_short_videos=False, |
| filter_long_videos=int(1e9), |
| datasets_weights=None, |
| persistent_workers=False, |
| deterministic=True, |
| log_dir=None |
| ): |
| from src.datasets.video_dataset import MiniImagenetDataset, make_miniimagenet |
|
|
| dataset, data_loader, dist_sampler = make_miniimagenet( |
| path_miniimagenet, |
| batch_size, |
| transform=transform, |
| shared_transform=shared_transform, |
| data=data, |
| collator=collator, |
| pin_mem=pin_mem, |
| num_workers=num_workers, |
| world_size=world_size, |
| rank=rank, |
| root_path=root_path, |
| image_folder=image_folder, |
| training=training, |
| drop_last=drop_last, |
| subset_file=subset_file, |
| clip_len=clip_len, |
| dataset_fpcs=dataset_fpcs, |
| frame_sample_rate=frame_sample_rate, |
| duration=duration, |
| fps=fps, |
| num_clips=num_clips, |
| random_clip_sampling=random_clip_sampling, |
| allow_clip_overlap=allow_clip_overlap, |
| filter_short_videos=filter_short_videos, |
| filter_long_videos=filter_long_videos, |
| datasets_weights=datasets_weights, |
| persistent_workers=persistent_workers, |
| deterministic=deterministic, |
| log_dir=log_dir, |
| ) |
| |
| return (data_loader, dist_sampler) |
