


'''simple docstring'''




from unittest.mock import Mock, patch

from file_transfer.send_file import send_file

@patch('socket.socket'				)
@patch('builtins.open'				)
def 			__UpperCamelCase    (    _A    :				Any					,   _A    :				Any				)    ->      List[Any]:




	"""simple docstring"""





	lowerCAmelCase					:    Tuple      							= Mock()
	lowerCAmelCase					:    List[Any]      							= conn, Mock()
	lowerCAmelCase					:    Any      							= iter([1, None]				)
	lowerCAmelCase					:    List[Any]      							= lambda _A				: next(__lowercase				)

	# ===== invoke =====
	send_file(filename='mytext.txt'					,   testing=__lowercase				)

	# ===== ensurance =====
	sock.assert_called_once()
	sock.return_value.bind.assert_called_once()
	sock.return_value.listen.assert_called_once()
	sock.return_value.accept.assert_called_once()
	conn.recv.assert_called_once()

	file.return_value.__enter__.assert_called_once()
	file.return_value.__enter__.return_value.read.assert_called()

	conn.send.assert_called_once()
	conn.close.assert_called_once()
	sock.return_value.shutdown.assert_called_once()
	sock.return_value.close.assert_called_once()




'''simple docstring'''




from typing import TYPE_CHECKING

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


_lowerCAmelCase  :		int		     =	{
    'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCAmelCase  :		Tuple		     =	[
				    'NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'NezhaForNextSentencePrediction',
				    'NezhaForMaskedLM',
				    'NezhaForPreTraining',
				    'NezhaForMultipleChoice',
				    'NezhaForQuestionAnswering',
				    'NezhaForSequenceClassification',
				    'NezhaForTokenClassification',
				    'NezhaModel',
				    'NezhaPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_nezha import (
								    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
								    NezhaForMaskedLM,
								    NezhaForMultipleChoice,
								    NezhaForNextSentencePrediction,
								    NezhaForPreTraining,
								    NezhaForQuestionAnswering,
								    NezhaForSequenceClassification,
								    NezhaForTokenClassification,
								    NezhaModel,
								    NezhaPreTrainedModel,
								)


else:
				import sys

				_lowerCAmelCase  :		str		     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
