# Copyright 2017 Neural Networks and Deep Learning lab, MIPT
#
# 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 copy
from logging import getLogger
from typing import Dict
from deeppavlov.core.common.registry import get_model, register
from deeppavlov.core.data.dataset_reader import DatasetReader
log = getLogger(__name__)
[docs]@register('multitask_reader')
class MultiTaskReader(DatasetReader):
"""Class to read several datasets simultaneously."""
[docs] def read(self, tasks: Dict[str, Dict[str, dict]], task_defaults: dict = None, **kwargs):
"""Creates dataset readers for tasks and returns what task dataset readers `read()` methods return.
Args:
tasks: dictionary which keys are task names and values are dictionaries with param name - value pairs for
nested dataset readers initialization. If task has key-value pair ``'use_task_defaults': False``,
task_defaults for this task dataset reader will be ignored.
task_defaults: default task parameters.
Returns:
dictionary which keys are task names and values are what task readers `read()` methods returned.
"""
data = dict()
if task_defaults is None:
task_defaults = dict()
for task_name, task_params in tasks.items():
if task_params.pop('use_task_defaults', True) is True:
task_config = copy.deepcopy(task_defaults)
task_config.update(task_params)
else:
task_config = task_params
reader = get_model(task_config.pop('class_name'))()
data[task_name] = reader.read(**task_config)
return data