concepts.benchmark.vision_language.shapes3.dataset.Shapes3DatasetFilterableView#

class Shapes3DatasetFilterableView[source]#

Bases: FilterableDatasetView

Methods

`collect`(key_func)
`filter`(filter_func[, filter_name])
`filter_question_length`(length)
`get_metainfo`(index)
`make_dataloader`(batch_size, shuffle, ...)
`random_shuffle`()
`random_trim_length`(length)
`repeat`(nr_repeats)
`sort`(key[, key_name])
`split_kfold`(k)
`split_trainval`(split)
`trim_length`(length)
`trim_range`(begin[, end])

Attributes

`filter_func`
`filter_name`
`full_filter_name`
`unwrapped`

__add__(other)#

__getitem__(index)#

__init__(owner_dataset, indices=None, filter_name=None, filter_func=None)#

Parameters:

owner_dataset (Dataset) – the original dataset.
indices (List[int]) – a list of indices that was filterred out.
filter_name (str) – human-friendly name for the filter.
filter_func (Callable) – just for tracking.

__iter__()#

__len__()#

__new__(**kwargs)#

collect(key_func)#

filter(filter_func, filter_name=None)#

filter_question_length(length)[source]#

Parameters:: length (int)
Return type:: Shapes3DatasetFilterableView

get_metainfo(index)#

make_dataloader(batch_size, shuffle, drop_last, nr_workers)[source]#

Parameters:

batch_size (int)
shuffle (bool)
drop_last (bool)
nr_workers (int)

Return type:

JacDataLoader

random_shuffle()#

random_trim_length(length)#

repeat(nr_repeats)#

sort(key, key_name=None)#

split_kfold(k)#

split_trainval(split)#

trim_length(length)#

trim_range(begin, end=None)#

property filter_func#

property filter_name#

property full_filter_name#

property unwrapped#