<reponame>khakhulin/DeepPavlov
"""
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.
"""
from overrides import overrides

from deeppavlov.core.common.registry import register
from deeppavlov.core.models.component import Component
from deeppavlov.core.common.log import get_logger

log = get_logger(__name__)


@register('char_splitter')
class CharSplitter(Component):
    def __init__(self, **kwargs):
        pass

    @overrides
    def __call__(self, batch, *args, **kwargs):
        char_batch = []
        for tokens_sequence in batch:
            char_batch.append([list(tok) for tok in tokens_sequence])
        return char_batch

"""
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.
"""
from overrides import overrides

from deeppavlov.core.common.registry import register
from deeppavlov.core.models.component import Component
from deeppavlov.core.common.log import get_logger

log = get_logger(__name__)


@register('char_splitter')
class CharSplitter(Component):
    def __init__(self, **kwargs):
        pass

    @overrides
    def __call__(self, batch, *args, **kwargs):
        char_batch = []
        for tokens_sequence in batch:
            char_batch.append([list(tok) for tok in tokens_sequence])
        return char_batch
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.