
from typing import TYPE_CHECKING

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


UpperCAmelCase__				:  Tuple       					=				{
    '''configuration_mpnet''': ['''MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MPNetConfig'''],
    '''tokenization_mpnet''': ['''MPNetTokenizer'''],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__				:  Dict       					=				['''MPNetTokenizerFast''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__				:  List[str]       					=				[
							    '''MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''MPNetForMaskedLM''',
							    '''MPNetForMultipleChoice''',
							    '''MPNetForQuestionAnswering''',
							    '''MPNetForSequenceClassification''',
							    '''MPNetForTokenClassification''',
							    '''MPNetLayer''',
							    '''MPNetModel''',
							    '''MPNetPreTrainedModel''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__				:  int       					=				[
							    '''TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFMPNetEmbeddings''',
							    '''TFMPNetForMaskedLM''',
							    '''TFMPNetForMultipleChoice''',
							    '''TFMPNetForQuestionAnswering''',
							    '''TFMPNetForSequenceClassification''',
							    '''TFMPNetForTokenClassification''',
							    '''TFMPNetMainLayer''',
							    '''TFMPNetModel''',
							    '''TFMPNetPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
							from .tokenization_mpnet import MPNetTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_mpnet_fast import MPNetTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mpnet import (
														    MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MPNetForMaskedLM,
														    MPNetForMultipleChoice,
														    MPNetForQuestionAnswering,
														    MPNetForSequenceClassification,
														    MPNetForTokenClassification,
														    MPNetLayer,
														    MPNetModel,
														    MPNetPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_mpnet import (
														    TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFMPNetEmbeddings,
														    TFMPNetForMaskedLM,
														    TFMPNetForMultipleChoice,
														    TFMPNetForQuestionAnswering,
														    TFMPNetForSequenceClassification,
														    TFMPNetForTokenClassification,
														    TFMPNetMainLayer,
														    TFMPNetModel,
														    TFMPNetPreTrainedModel,
														)

else:
							import sys

							UpperCAmelCase__				:  int       					=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





def       _lowercase					(      __SCREAMING_SNAKE_CASE = "mytext.txt"				,    __SCREAMING_SNAKE_CASE = False )	->     None:
			import socket

			UpperCamelCase__    :		Tuple     =				1_2312  # Reserve a port for your service.
			UpperCamelCase__    :		Optional[int]     =				socket.socket()  # Create a socket object
			UpperCamelCase__    :		Optional[int]     =				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:
						UpperCamelCase__   ,			UpperCamelCase__    :		Optional[int]     =				sock.accept()  # Establish connection with client.
						print(F"""Got connection from {addr}""" )
						UpperCamelCase__    :		Union[str, Any]     =				conn.recv(1024 )
						print(F"""Server received: {data = }""" )

						with open(__SCREAMING_SNAKE_CASE				,    'rb' ) as in_file:
									UpperCamelCase__    :		Tuple     =				in_file.read(1024 )
									while data:
												conn.send(__SCREAMING_SNAKE_CASE )
												print(F"""Sent {data!r}""" )
												UpperCamelCase__    :		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()



