



"""simple docstring"""







from unittest.mock import Mock, patch

from file_transfer.send_file import send_file



@patch('''socket.socket'''	)
@patch('''builtins.open'''	)
def      __UpperCAmelCase      (    __lowerCamelCase						,     __lowerCamelCase	)							->      int:
		# ===== initialization =====
		lowercase__   :    List[str]				=			Mock()
		lowercase__   :    Any				=			conn, Mock()
		lowercase__   :    Optional[int]				=			iter([1, None]	)
		lowercase__   :    Union[str, Any]				=			lambda __lowerCamelCase	: next(__lowerCamelCase	)

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

		# ===== 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'''




import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
      import jax

      from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
      from transformers.models.bert.modeling_flax_bert import FlaxBertModel
      from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel





@require_flax
class  A				(							unittest.TestCase						):





     @slow
     def 				__lowerCAmelCase							(							self	) ->				List[Any]:






         """simple docstring"""






         for model_name in ["bert-base-cased", "bert-large-uncased"]:
             with self.subTest(SCREAMING_SNAKE_CASE	):
                 A       :   int					=						AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

                 A       :   List[str]					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				int:






         """simple docstring"""






         for model_name in ["roberta-base", "roberta-large"]:
             with self.subTest(SCREAMING_SNAKE_CASE	):
                 A       :   Any					=						AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

                 A       :   Any					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Any:






         """simple docstring"""






         for model_name in ["bert-base-cased", "bert-large-uncased"]:
             A       :   Optional[int]					=						AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   List[str]					=						FlaxBertModel.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   Optional[Any]					=						tokenizer('''Do you support jax jitted function?'''						,			return_tensors=TensorType.JAX	)

             @jax.jit
             def eval(**SCREAMING_SNAKE_CASE	):
                 return model(**SCREAMING_SNAKE_CASE	)

             eval(**SCREAMING_SNAKE_CASE	).block_until_ready()





     @slow
     def 				__lowerCAmelCase							(							self	) ->				List[str]:






         """simple docstring"""






         for model_name in ["roberta-base", "roberta-large"]:
             A       :   List[str]					=						AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   Union[str, Any]					=						FlaxRobertaModel.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   int					=						tokenizer('''Do you support jax jitted function?'''						,			return_tensors=TensorType.JAX	)

             @jax.jit
             def eval(**SCREAMING_SNAKE_CASE	):
                 return model(**SCREAMING_SNAKE_CASE	)

             eval(**SCREAMING_SNAKE_CASE	).block_until_ready()





     def 				__lowerCAmelCase							(							self	) ->				List[str]:






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			'''bert-base is not a local folder and is not a valid model identifier'''	):
             A       :   List[Any]					=						FlaxAutoModel.from_pretrained('''bert-base'''	)





     def 				__lowerCAmelCase							(							self	) ->				Tuple:






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''	):
             A       :   Optional[int]					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE						,			revision='''aaaaaa'''	)





     def 				__lowerCAmelCase							(							self	) ->				str:






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			'''hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'''						,			):
             A       :   List[str]					=						FlaxAutoModel.from_pretrained('''hf-internal-testing/config-no-model'''	)





     def 				__lowerCAmelCase							(							self	) ->				Optional[Any]:






         """simple docstring"""






         with self.assertRaisesRegex(SCREAMING_SNAKE_CASE						,			'''Use `from_pt=True` to load this model'''	):
             A       :   Any					=						FlaxAutoModel.from_pretrained('''hf-internal-testing/tiny-bert-pt-only'''	)




