Source code for deeppavlov.dataset_readers.multitask_reader

# 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
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#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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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