



'''simple docstring'''

from abc import ABC, abstractmethod
from typing import Optional, Union

from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike

class 	__magic_name__						(    _UpperCamelCase   ):







							def __init__(							self					:       int	,_UpperCAmelCase					:       Optional[NestedDataStructureLike[PathLike]] = None	,_UpperCAmelCase					:       Optional[NamedSplit] = None	,_UpperCAmelCase					:       Optional[Features] = None	,_UpperCAmelCase					:       str = None	,_UpperCAmelCase					:       bool = False	,_UpperCAmelCase					:       bool = False	,_UpperCAmelCase					:       Optional[int] = None	,**_UpperCAmelCase					:       Union[str, Any]	,):
									_a     :      int        =							path_or_paths
									_a     :      List[Any]        =							split if split or isinstance(_UpperCAmelCase	,_UpperCAmelCase		) else 'train'
									_a     :      Tuple        =							features
									_a     :      Optional[Any]        =							cache_dir
									_a     :      List[str]        =							keep_in_memory
									_a     :      Tuple        =							streaming
									_a     :      str        =							num_proc
									_a     :      int        =							kwargs







							@abstractmethod
							def 							__lowercase			(							self					:       Tuple		):
									pass

class 	__magic_name__						(    _UpperCamelCase   ):







							def __init__(							self					:       Optional[Any]	,_UpperCAmelCase					:       Optional[Features] = None	,_UpperCAmelCase					:       str = None	,_UpperCAmelCase					:       bool = False	,_UpperCAmelCase					:       bool = False	,_UpperCAmelCase					:       Optional[int] = None	,**_UpperCAmelCase					:       Optional[int]	,):
									_a     :      Union[str, Any]        =							features
									_a     :      List[str]        =							cache_dir
									_a     :      Optional[Any]        =							keep_in_memory
									_a     :      int        =							streaming
									_a     :      int        =							num_proc
									_a     :      List[str]        =							kwargs







							@abstractmethod
							def 							__lowercase			(							self					:       List[Any]		):
									pass









'''simple docstring'''

# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# 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 typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__lowerCAmelCase									=   {
    '''configuration_cpmant''': ['''CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CpmAntConfig'''],
    '''tokenization_cpmant''': ['''CpmAntTokenizer'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''CpmAntForCausalLM''',
							    '''CpmAntModel''',
							    '''CpmAntPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
							from .tokenization_cpmant import CpmAntTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_cpmant import (
														    CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CpmAntForCausalLM,
														    CpmAntModel,
														    CpmAntPreTrainedModel,
														)


else:
							import sys

							__lowerCAmelCase									=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




