chainer.datasets.ConcatenatedDataset¶
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class
chainer.datasets.
ConcatenatedDataset
(*datasets)[source]¶ Dataset which concatenates some base datasets.
This dataset wraps some base datasets and works as a concatenated dataset. For example, if a base dataset with 10 samples and another base dataset with 20 samples are given, this dataset works as a dataset which has 30 samples.
Parameters: datasets – The underlying datasets. Each dataset has to support __len__()
and__getitem__()
.Methods
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__getitem__
(index)[source]¶ Returns an example or a sequence of examples.
It implements the standard Python indexing and one-dimensional integer array indexing. It uses the
get_example()
method by default, but it may be overridden by the implementation to, for example, improve the slicing performance.Parameters: index (int, slice, list or numpy.ndarray) – An index of an example or indexes of examples. Returns: If index is int, returns an example created by get_example. If index is either slice or one-dimensional list or numpy.ndarray, returns a list of examples created by get_example. Example
>>> import numpy >>> from chainer import dataset >>> class SimpleDataset(dataset.DatasetMixin): ... def __init__(self, values): ... self.values = values ... def __len__(self): ... return len(self.values) ... def get_example(self, i): ... return self.values[i] ... >>> ds = SimpleDataset([0, 1, 2, 3, 4, 5]) >>> ds[1] # Access by int 1 >>> ds[1:3] # Access by slice [1, 2] >>> ds[[4, 0]] # Access by one-dimensional integer list [4, 0] >>> index = numpy.arange(3) >>> ds[index] # Access by one-dimensional integer numpy.ndarray [0, 1, 2]
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get_example
(i)[source]¶ Returns the i-th example.
Implementations should override it. It should raise
IndexError
if the index is invalid.Parameters: i (int) – The index of the example. Returns: The i-th example.
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