def __init__(self,
dataset,
batch_size=128,
shuffle=False,
sampler=None,
batch_sampler=None,
num_workers=0,
collate_fn=my_collate,
pin_memory=False,
drop_last=False,
timeout=0,
worker_init_fn=None):
DataLoader.__init__(self,
dataset,
batch_size=128,
shuffle=False,
sampler=None,
batch_sampler=None,
num_workers=0,
collate_fn=my_collate,
pin_memory=False,
drop_last=False,
timeout=0,
worker_init_fn=None)
self.collate_fn = collate_fn
def __init__(self, dataset, batch_size, num_workers=0, shuffle=True):
DataLoader.__init__(self,
dataset,
batch_size,
num_workers=num_workers,
shuffle=shuffle,
drop_last=True)
def __init__(self, dtset, batch_size, shuffle=False):
"""Construtor
Parameters
----------
dtset : a dataset
batch_size : size of a minibatch
shuffle : bool, if we shuffle the data
"""
if batch_size <= 0:
batch_size = len(dtset)
self.dtset = dtset
if isinstance(dtset, subFactory):
sampler = SubsetRandomSampler(range(dtset.startind,
dtset.finalind))
DataLoader.__init__(self,
dtset,
batch_size,
shuffle=False,
sampler=sampler)
else:
DataLoader.__init__(self, dtset, batch_size, shuffle=shuffle)
if hasattr(dtset, 'xmean'):
self.xmean = dtset.xmean
self.xstd = dtset.xstd
if hasattr(dtset, 'ymean'):
self.ymean = dtset.ymean
self.ystd = dtset.ystd
if hasattr(dtset, '_xname'):
self._xname = dtset._xname
if hasattr(dtset, '_yname'):
self._yname = dtset._yname
def __init__(
self,
dataset: ConcatDataset,
batch_size=1,
shuffle=False,
drop_last=False,
device=None,
spawn=False,
pass_pid=False,
**otherconf
):
if spawn:
raise NotImplementedError
DeviceAwareness.__init__(self, device)
sampler_cls = ChainSubsetRandomSampler if shuffle else SequentialSampler
DataLoader.__init__(
self,
dataset,
batch_size,
**otherconf,
pin_memory=False,
drop_last=drop_last,
collate_fn=lambda x: fixCollate(x, pass_pid),
sampler=sampler_cls(dataset),
num_workers=mp.cpu_count() if spawn else 0,
)
def __init__(
self,
dataset: ConcatDataset,
distrib_title: str,
batchsize_k=1,
shuffle=False,
device=None,
spawn=False,
**otherconf
):
if spawn:
raise NotImplementedError
assert "drop_last" not in otherconf
DeviceAwareness.__init__(self, device)
DataLoader.__init__(
self,
dataset,
**otherconf,
pin_memory=False,
collate_fn=fixCollate,
num_workers=mp.cpu_count() if spawn else 0,
batch_sampler=DistributedSampler(
dataset, distrib_title, batchsize_k, device, shuffle
),
)
def __init__(self, dataset, batch_size=1, num_workers=0):
DataLoader.__init__(
self,
dataset,
batch_size=batch_size,
shuffle=True,
collate_fn=collate_as_tensor,
num_workers=num_workers,
drop_last=True,
)
def __init__(self, *args, **kwargs):
kwargs['collate_fn'] = collate_by_input_length
DataLoader.__init__(self, *args, **kwargs)
def __init__(self, dataset, batch_size=4, shuffle=True):
DataLoader.__init__(self,
dataset,
batch_size=batch_size,
shuffle=shuffle,
collate_fn=collate_fn)
def __init__(self, n_class, n_shot, n_query, *args, **kwargs):
self.n_class = n_class
self.n_shot = n_shot
self.n_query = n_query
DataLoader.__init__(self, *args, **kwargs)
