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# Copyright 2021 Piotr Żelasko
#
# See ../../LICENSE for clarification regarding multiple authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
from typing import List, Union
from lhotse import CutSet
from torch.utils.data import DataLoader
class DataModule:
"""
Contains dataset-related code. It is intended to read/construct Lhotse cuts,
and create Dataset/Sampler/DataLoader out of them.
There is a separate method to create each of train/valid/test DataLoader.
In principle, there might be multiple DataLoaders for each of
train/valid/test
(e.g. when a corpus has multiple test sets).
The API of this class allows to return lists of CutSets/DataLoaders.
"""
def __init__(self, args: argparse.Namespace):
self.args = args
@classmethod
def add_arguments(cls, parser: argparse.ArgumentParser):
pass
def train_cuts(self) -> Union[CutSet, List[CutSet]]:
raise NotImplementedError()
def valid_cuts(self) -> Union[CutSet, List[CutSet]]:
raise NotImplementedError()
def test_cuts(self) -> Union[CutSet, List[CutSet]]:
raise NotImplementedError()
def train_dataloaders(self) -> Union[DataLoader, List[DataLoader]]:
raise NotImplementedError()
def valid_dataloaders(self) -> Union[DataLoader, List[DataLoader]]:
raise NotImplementedError()
def test_dataloaders(self) -> Union[DataLoader, List[DataLoader]]:
raise NotImplementedError()