code: 
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_tf_available,
      is_torch_available,
  )
  
  
  _A							    =	{
      """auto_factory""": ["""get_values"""],
      """configuration_auto""": ["""ALL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CONFIG_MAPPING""", """MODEL_NAMES_MAPPING""", """AutoConfig"""],
      """feature_extraction_auto""": ["""FEATURE_EXTRACTOR_MAPPING""", """AutoFeatureExtractor"""],
      """image_processing_auto""": ["""IMAGE_PROCESSOR_MAPPING""", """AutoImageProcessor"""],
      """processing_auto""": ["""PROCESSOR_MAPPING""", """AutoProcessor"""],
      """tokenization_auto""": ["""TOKENIZER_MAPPING""", """AutoTokenizer"""],
  }
  
  try:
  			if not is_torch_available():
  						raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  			pass
  else:
  			_A							    =	[
  			    """MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING""",
  			    """MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING""",
  			    """MODEL_FOR_AUDIO_XVECTOR_MAPPING""",
  			    """MODEL_FOR_BACKBONE_MAPPING""",
  			    """MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING""",
  			    """MODEL_FOR_CAUSAL_LM_MAPPING""",
  			    """MODEL_FOR_CTC_MAPPING""",
  			    """MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING""",
  			    """MODEL_FOR_DEPTH_ESTIMATION_MAPPING""",
  			    """MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING""",
  			    """MODEL_FOR_IMAGE_SEGMENTATION_MAPPING""",
  			    """MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING""",
  			    """MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING""",
  			    """MODEL_FOR_MASKED_LM_MAPPING""",
  			    """MODEL_FOR_MASK_GENERATION_MAPPING""",
  			    """MODEL_FOR_MULTIPLE_CHOICE_MAPPING""",
  			    """MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING""",
  			    """MODEL_FOR_OBJECT_DETECTION_MAPPING""",
  			    """MODEL_FOR_PRETRAINING_MAPPING""",
  			    """MODEL_FOR_QUESTION_ANSWERING_MAPPING""",
  			    """MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING""",
  			    """MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING""",
  			    """MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING""",
  			    """MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING""",
  			    """MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING""",
  			    """MODEL_FOR_TEXT_ENCODING_MAPPING""",
  			    """MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING""",
  			    """MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING""",
  			    """MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING""",
  			    """MODEL_FOR_VISION_2_SEQ_MAPPING""",
  			    """MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING""",
  			    """MODEL_MAPPING""",
  			    """MODEL_WITH_LM_HEAD_MAPPING""",
  			    """MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING""",
  			    """MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING""",
  			    """AutoModel""",
  			    """AutoBackbone""",
  			    """AutoModelForAudioClassification""",
  			    """AutoModelForAudioFrameClassification""",
  			    """AutoModelForAudioXVector""",
  			    """AutoModelForCausalLM""",
  			    """AutoModelForCTC""",
  			    """AutoModelForDepthEstimation""",
  			    """AutoModelForImageClassification""",
  			    """AutoModelForImageSegmentation""",
  			    """AutoModelForInstanceSegmentation""",
  			    """AutoModelForMaskGeneration""",
  			    """AutoModelForTextEncoding""",
  			    """AutoModelForMaskedImageModeling""",
  			    """AutoModelForMaskedLM""",
  			    """AutoModelForMultipleChoice""",
  			    """AutoModelForNextSentencePrediction""",
  			    """AutoModelForObjectDetection""",
  			    """AutoModelForPreTraining""",
  			    """AutoModelForQuestionAnswering""",
  			    """AutoModelForSemanticSegmentation""",
  			    """AutoModelForSeq2SeqLM""",
  			    """AutoModelForSequenceClassification""",
  			    """AutoModelForSpeechSeq2Seq""",
  			    """AutoModelForTableQuestionAnswering""",
  			    """AutoModelForTokenClassification""",
  			    """AutoModelForUniversalSegmentation""",
  			    """AutoModelForVideoClassification""",
  			    """AutoModelForVision2Seq""",
  			    """AutoModelForVisualQuestionAnswering""",
  			    """AutoModelForDocumentQuestionAnswering""",
  			    """AutoModelWithLMHead""",
  			    """AutoModelForZeroShotImageClassification""",
  			    """AutoModelForZeroShotObjectDetection""",
  			]
  
  try:
  			if not is_tf_available():
  						raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  			pass
  else:
  			_A							    =	[
  			    """TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING""",
  			    """TF_MODEL_FOR_CAUSAL_LM_MAPPING""",
  			    """TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING""",
  			    """TF_MODEL_FOR_MASK_GENERATION_MAPPING""",
  			    """TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING""",
  			    """TF_MODEL_FOR_MASKED_LM_MAPPING""",
  			    """TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING""",
  			    """TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING""",
  			    """TF_MODEL_FOR_PRETRAINING_MAPPING""",
  			    """TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING""",
  			    """TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING""",
  			    """TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING""",
  			    """TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING""",
  			    """TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING""",
  			    """TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING""",
  			    """TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING""",
  			    """TF_MODEL_FOR_TEXT_ENCODING_MAPPING""",
  			    """TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING""",
  			    """TF_MODEL_FOR_VISION_2_SEQ_MAPPING""",
  			    """TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING""",
  			    """TF_MODEL_MAPPING""",
  			    """TF_MODEL_WITH_LM_HEAD_MAPPING""",
  			    """TFAutoModel""",
  			    """TFAutoModelForAudioClassification""",
  			    """TFAutoModelForCausalLM""",
  			    """TFAutoModelForImageClassification""",
  			    """TFAutoModelForMaskedImageModeling""",
  			    """TFAutoModelForMaskedLM""",
  			    """TFAutoModelForMaskGeneration""",
  			    """TFAutoModelForMultipleChoice""",
  			    """TFAutoModelForNextSentencePrediction""",
  			    """TFAutoModelForPreTraining""",
  			    """TFAutoModelForDocumentQuestionAnswering""",
  			    """TFAutoModelForQuestionAnswering""",
  			    """TFAutoModelForSemanticSegmentation""",
  			    """TFAutoModelForSeq2SeqLM""",
  			    """TFAutoModelForSequenceClassification""",
  			    """TFAutoModelForSpeechSeq2Seq""",
  			    """TFAutoModelForTableQuestionAnswering""",
  			    """TFAutoModelForTextEncoding""",
  			    """TFAutoModelForTokenClassification""",
  			    """TFAutoModelForVision2Seq""",
  			    """TFAutoModelForZeroShotImageClassification""",
  			    """TFAutoModelWithLMHead""",
  			]
  
  try:
  			if not is_flax_available():
  						raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  			pass
  else:
  			_A							    =	[
  			    """FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING""",
  			    """FLAX_MODEL_FOR_CAUSAL_LM_MAPPING""",
  			    """FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING""",
  			    """FLAX_MODEL_FOR_MASKED_LM_MAPPING""",
  			    """FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING""",
  			    """FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING""",
  			    """FLAX_MODEL_FOR_PRETRAINING_MAPPING""",
  			    """FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING""",
  			    """FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING""",
  			    """FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING""",
  			    """FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING""",
  			    """FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING""",
  			    """FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING""",
  			    """FLAX_MODEL_MAPPING""",
  			    """FlaxAutoModel""",
  			    """FlaxAutoModelForCausalLM""",
  			    """FlaxAutoModelForImageClassification""",
  			    """FlaxAutoModelForMaskedLM""",
  			    """FlaxAutoModelForMultipleChoice""",
  			    """FlaxAutoModelForNextSentencePrediction""",
  			    """FlaxAutoModelForPreTraining""",
  			    """FlaxAutoModelForQuestionAnswering""",
  			    """FlaxAutoModelForSeq2SeqLM""",
  			    """FlaxAutoModelForSequenceClassification""",
  			    """FlaxAutoModelForSpeechSeq2Seq""",
  			    """FlaxAutoModelForTokenClassification""",
  			    """FlaxAutoModelForVision2Seq""",
  			]
  
  
  if TYPE_CHECKING:
  			from .auto_factory import get_values
  			from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, CONFIG_MAPPING, MODEL_NAMES_MAPPING, AutoConfig
  			from .feature_extraction_auto import FEATURE_EXTRACTOR_MAPPING, AutoFeatureExtractor
  			from .image_processing_auto import IMAGE_PROCESSOR_MAPPING, AutoImageProcessor
  			from .processing_auto import PROCESSOR_MAPPING, AutoProcessor
  			from .tokenization_auto import TOKENIZER_MAPPING, AutoTokenizer
  
  			try:
  						if not is_torch_available():
  									raise OptionalDependencyNotAvailable()
  			except OptionalDependencyNotAvailable:
  						pass
  			else:
  						from .modeling_auto import (
  						    MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
  						    MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING,
  						    MODEL_FOR_AUDIO_XVECTOR_MAPPING,
  						    MODEL_FOR_BACKBONE_MAPPING,
  						    MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING,
  						    MODEL_FOR_CAUSAL_LM_MAPPING,
  						    MODEL_FOR_CTC_MAPPING,
  						    MODEL_FOR_DEPTH_ESTIMATION_MAPPING,
  						    MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
  						    MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
  						    MODEL_FOR_IMAGE_SEGMENTATION_MAPPING,
  						    MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING,
  						    MODEL_FOR_MASK_GENERATION_MAPPING,
  						    MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
  						    MODEL_FOR_MASKED_LM_MAPPING,
  						    MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
  						    MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
  						    MODEL_FOR_OBJECT_DETECTION_MAPPING,
  						    MODEL_FOR_PRETRAINING_MAPPING,
  						    MODEL_FOR_QUESTION_ANSWERING_MAPPING,
  						    MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
  						    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
  						    MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
  						    MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
  						    MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
  						    MODEL_FOR_TEXT_ENCODING_MAPPING,
  						    MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
  						    MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING,
  						    MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING,
  						    MODEL_FOR_VISION_2_SEQ_MAPPING,
  						    MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING,
  						    MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
  						    MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING,
  						    MODEL_MAPPING,
  						    MODEL_WITH_LM_HEAD_MAPPING,
  						    AutoBackbone,
  						    AutoModel,
  						    AutoModelForAudioClassification,
  						    AutoModelForAudioFrameClassification,
  						    AutoModelForAudioXVector,
  						    AutoModelForCausalLM,
  						    AutoModelForCTC,
  						    AutoModelForDepthEstimation,
  						    AutoModelForDocumentQuestionAnswering,
  						    AutoModelForImageClassification,
  						    AutoModelForImageSegmentation,
  						    AutoModelForInstanceSegmentation,
  						    AutoModelForMaskedImageModeling,
  						    AutoModelForMaskedLM,
  						    AutoModelForMaskGeneration,
  						    AutoModelForMultipleChoice,
  						    AutoModelForNextSentencePrediction,
  						    AutoModelForObjectDetection,
  						    AutoModelForPreTraining,
  						    AutoModelForQuestionAnswering,
  						    AutoModelForSemanticSegmentation,
  						    AutoModelForSeqaSeqLM,
  						    AutoModelForSequenceClassification,
  						    AutoModelForSpeechSeqaSeq,
  						    AutoModelForTableQuestionAnswering,
  						    AutoModelForTextEncoding,
  						    AutoModelForTokenClassification,
  						    AutoModelForUniversalSegmentation,
  						    AutoModelForVideoClassification,
  						    AutoModelForVisionaSeq,
  						    AutoModelForVisualQuestionAnswering,
  						    AutoModelForZeroShotImageClassification,
  						    AutoModelForZeroShotObjectDetection,
  						    AutoModelWithLMHead,
  						)
  
  			try:
  						if not is_tf_available():
  									raise OptionalDependencyNotAvailable()
  			except OptionalDependencyNotAvailable:
  						pass
  			else:
  						from .modeling_tf_auto import (
  						    TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
  						    TF_MODEL_FOR_CAUSAL_LM_MAPPING,
  						    TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
  						    TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
  						    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
  						    TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
  						    TF_MODEL_FOR_MASKED_LM_MAPPING,
  						    TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
  						    TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
  						    TF_MODEL_FOR_PRETRAINING_MAPPING,
  						    TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
  						    TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
  						    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
  						    TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
  						    TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
  						    TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
  						    TF_MODEL_FOR_TEXT_ENCODING_MAPPING,
  						    TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
  						    TF_MODEL_FOR_VISION_2_SEQ_MAPPING,
  						    TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
  						    TF_MODEL_MAPPING,
  						    TF_MODEL_WITH_LM_HEAD_MAPPING,
  						    TFAutoModel,
  						    TFAutoModelForAudioClassification,
  						    TFAutoModelForCausalLM,
  						    TFAutoModelForDocumentQuestionAnswering,
  						    TFAutoModelForImageClassification,
  						    TFAutoModelForMaskedImageModeling,
  						    TFAutoModelForMaskedLM,
  						    TFAutoModelForMaskGeneration,
  						    TFAutoModelForMultipleChoice,
  						    TFAutoModelForNextSentencePrediction,
  						    TFAutoModelForPreTraining,
  						    TFAutoModelForQuestionAnswering,
  						    TFAutoModelForSemanticSegmentation,
  						    TFAutoModelForSeqaSeqLM,
  						    TFAutoModelForSequenceClassification,
  						    TFAutoModelForSpeechSeqaSeq,
  						    TFAutoModelForTableQuestionAnswering,
  						    TFAutoModelForTextEncoding,
  						    TFAutoModelForTokenClassification,
  						    TFAutoModelForVisionaSeq,
  						    TFAutoModelForZeroShotImageClassification,
  						    TFAutoModelWithLMHead,
  						)
  
  			try:
  						if not is_flax_available():
  									raise OptionalDependencyNotAvailable()
  			except OptionalDependencyNotAvailable:
  						pass
  			else:
  						from .modeling_flax_auto import (
  						    FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
  						    FLAX_MODEL_FOR_CAUSAL_LM_MAPPING,
  						    FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
  						    FLAX_MODEL_FOR_MASKED_LM_MAPPING,
  						    FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
  						    FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
  						    FLAX_MODEL_FOR_PRETRAINING_MAPPING,
  						    FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
  						    FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
  						    FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
  						    FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
  						    FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
  						    FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING,
  						    FLAX_MODEL_MAPPING,
  						    FlaxAutoModel,
  						    FlaxAutoModelForCausalLM,
  						    FlaxAutoModelForImageClassification,
  						    FlaxAutoModelForMaskedLM,
  						    FlaxAutoModelForMultipleChoice,
  						    FlaxAutoModelForNextSentencePrediction,
  						    FlaxAutoModelForPreTraining,
  						    FlaxAutoModelForQuestionAnswering,
  						    FlaxAutoModelForSeqaSeqLM,
  						    FlaxAutoModelForSequenceClassification,
  						    FlaxAutoModelForSpeechSeqaSeq,
  						    FlaxAutoModelForTokenClassification,
  						    FlaxAutoModelForVisionaSeq,
  						)
  
  else:
  			import sys
  
  			_A							    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  def 						lowerCAmelCase_       (	__a = "mytext.txt"	,	__a = False )       ->			None:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							import socket
  
  							SCREAMING_SNAKE_CASE			: int	     =12312  # Reserve a port for your service.
  							SCREAMING_SNAKE_CASE			: Dict	     =socket.socket()  # Create a socket object
  							SCREAMING_SNAKE_CASE			: Any	     =socket.gethostname()  # Get local machine name
  							sock.bind((host, port) )  # Bind to the port
  							sock.listen(5 )  # Now wait for client connection.
  
  							print('''Server listening....''' )
  
  							while True:
  														SCREAMING_SNAKE_CASE     ,							SCREAMING_SNAKE_CASE			: Optional[int]	     =sock.accept()  # Establish connection with client.
  														print(f'Got connection from {addr}' )
  														SCREAMING_SNAKE_CASE			: List[str]	     =conn.recv(1024 )
  														print(f'Server received: {data = }' )
  
  														with open(__a	,	'''rb''' ) as in_file:
  																					SCREAMING_SNAKE_CASE			: Dict	     =in_file.read(1024 )
  																					while data:
  																												conn.send(__a )
  																												print(f'Sent {data!r}' )
  																												SCREAMING_SNAKE_CASE			: str	     =in_file.read(1024 )
  
  														print('''Done sending''' )
  														conn.close()
  														if testing:  # Allow the test to complete
  																					break
  
  							sock.shutdown(1 )
  							sock.close()
  
  
  if __name__ == "__main__":
  							send_file()
  
  
  
  
  
  
  