





'''simple docstring'''


from typing import TYPE_CHECKING

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


lowerCAmelCase_   :   List[str]       =					{
    "configuration_xlm_roberta": [
        "XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "XLMRobertaConfig",
        "XLMRobertaOnnxConfig",
    ],
}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase_   :   Union[str, Any]       =					["XLMRobertaTokenizer"]

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase_   :   Tuple       =					["XLMRobertaTokenizerFast"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase_   :   str       =					[
		    "XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "XLMRobertaForCausalLM",
		    "XLMRobertaForMaskedLM",
		    "XLMRobertaForMultipleChoice",
		    "XLMRobertaForQuestionAnswering",
		    "XLMRobertaForSequenceClassification",
		    "XLMRobertaForTokenClassification",
		    "XLMRobertaModel",
		    "XLMRobertaPreTrainedModel",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase_   :   Tuple       =					[
		    "TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "TFXLMRobertaForCausalLM",
		    "TFXLMRobertaForMaskedLM",
		    "TFXLMRobertaForMultipleChoice",
		    "TFXLMRobertaForQuestionAnswering",
		    "TFXLMRobertaForSequenceClassification",
		    "TFXLMRobertaForTokenClassification",
		    "TFXLMRobertaModel",
		    "TFXLMRobertaPreTrainedModel",
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase_   :   str       =					[
		    "FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "FlaxXLMRobertaForMaskedLM",
		    "FlaxXLMRobertaForCausalLM",
		    "FlaxXLMRobertaForMultipleChoice",
		    "FlaxXLMRobertaForQuestionAnswering",
		    "FlaxXLMRobertaForSequenceClassification",
		    "FlaxXLMRobertaForTokenClassification",
		    "FlaxXLMRobertaModel",
		    "FlaxXLMRobertaPreTrainedModel",
		]

if TYPE_CHECKING:
		from .configuration_xlm_roberta import (
		    XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    XLMRobertaConfig,
		    XLMRobertaOnnxConfig,
		)

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_xlm_roberta import XLMRobertaTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_xlm_roberta_fast import XLMRobertaTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_xlm_roberta import (
				    XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    XLMRobertaForCausalLM,
				    XLMRobertaForMaskedLM,
				    XLMRobertaForMultipleChoice,
				    XLMRobertaForQuestionAnswering,
				    XLMRobertaForSequenceClassification,
				    XLMRobertaForTokenClassification,
				    XLMRobertaModel,
				    XLMRobertaPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_xlm_roberta import (
				    TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFXLMRobertaForCausalLM,
				    TFXLMRobertaForMaskedLM,
				    TFXLMRobertaForMultipleChoice,
				    TFXLMRobertaForQuestionAnswering,
				    TFXLMRobertaForSequenceClassification,
				    TFXLMRobertaForTokenClassification,
				    TFXLMRobertaModel,
				    TFXLMRobertaPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_xlm_roberta import (
				    FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    FlaxXLMRobertaForCausalLM,
				    FlaxXLMRobertaForMaskedLM,
				    FlaxXLMRobertaForMultipleChoice,
				    FlaxXLMRobertaForQuestionAnswering,
				    FlaxXLMRobertaForSequenceClassification,
				    FlaxXLMRobertaForTokenClassification,
				    FlaxXLMRobertaModel,
				    FlaxXLMRobertaPreTrainedModel,
				)

else:
		import sys

		lowerCAmelCase_   :   Any       =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










'''simple docstring'''


import unittest

from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script






@require_cpu
class       UpperCamelCase__  (		unittest.TestCase     ):







	def 						__a   (				self			:   List[str]		):




				'''simple docstring'''
				debug_launcher(test_script.main		)







	def 						__a   (				self			:   Dict		):




				'''simple docstring'''
				debug_launcher(test_ops.main		)



