
"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_keras_nlp_available,
    is_tensorflow_text_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__magic_name__		       =				{
    '''configuration_gpt2''': ['''GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPT2Config''', '''GPT2OnnxConfig'''],
    '''tokenization_gpt2''': ['''GPT2Tokenizer'''],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__		       =				['''GPT2TokenizerFast''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__		       =				[
			    '''GPT2_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''GPT2DoubleHeadsModel''',
			    '''GPT2ForQuestionAnswering''',
			    '''GPT2ForSequenceClassification''',
			    '''GPT2ForTokenClassification''',
			    '''GPT2LMHeadModel''',
			    '''GPT2Model''',
			    '''GPT2PreTrainedModel''',
			    '''load_tf_weights_in_gpt2''',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__		       =				[
			    '''TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''TFGPT2DoubleHeadsModel''',
			    '''TFGPT2ForSequenceClassification''',
			    '''TFGPT2LMHeadModel''',
			    '''TFGPT2MainLayer''',
			    '''TFGPT2Model''',
			    '''TFGPT2PreTrainedModel''',
			]

try:
			if not is_keras_nlp_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__		       =				['''TFGPT2Tokenizer''']

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__		       =				['''FlaxGPT2LMHeadModel''', '''FlaxGPT2Model''', '''FlaxGPT2PreTrainedModel''']

if TYPE_CHECKING:
			from .configuration_gpta import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTaConfig, GPTaOnnxConfig
			from .tokenization_gpta import GPTaTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_gpta_fast import GPTaTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_gpta import (
						    GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    GPTaDoubleHeadsModel,
						    GPTaForQuestionAnswering,
						    GPTaForSequenceClassification,
						    GPTaForTokenClassification,
						    GPTaLMHeadModel,
						    GPTaModel,
						    GPTaPreTrainedModel,
						    load_tf_weights_in_gpta,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_gpta import (
						    TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFGPTaDoubleHeadsModel,
						    TFGPTaForSequenceClassification,
						    TFGPTaLMHeadModel,
						    TFGPTaMainLayer,
						    TFGPTaModel,
						    TFGPTaPreTrainedModel,
						)

			try:
						if not is_keras_nlp_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_gpta_tf import TFGPTaTokenizer

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_gpta import FlaxGPTaLMHeadModel, FlaxGPTaModel, FlaxGPTaPreTrainedModel

else:
			import sys

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






"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available


__magic_name__		       =				{}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__		       =				['''CpmTokenizer''']

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__		       =				['''CpmTokenizerFast''']


if TYPE_CHECKING:
			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_cpm import CpmTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_cpm_fast import CpmTokenizerFast

else:
			import sys

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




