





'''simple docstring'''







import math
import os
import sys





def   _lowerCAmelCase		(		lowercase      )   ->   Dict:
			__lowerCAmelCase   		=							""""""
			try:
						with open(UpperCamelCase_   ,      """rb"""      ) as binary_file:
									__lowerCAmelCase   		=							binary_file.read()
						for dat in data:
									__lowerCAmelCase   		=							f'{dat:08b}'
									result += curr_byte
						return result
			except OSError:
						print("""File not accessible"""      )
						sys.exit()





def   _lowerCAmelCase		(		lowercase   ,      lowercase   ,      lowercase   ,      lowercase      )   ->   List[str]:
			lexicon.pop(UpperCamelCase_      )
			__lowerCAmelCase   		=							last_match_id

			if math.loga(UpperCamelCase_      ).is_integer():
						for curr_key in lexicon:
									__lowerCAmelCase   		=							"""0""" + lexicon[curr_key]

			__lowerCAmelCase   		=							bin(UpperCamelCase_      )[2:]





def   _lowerCAmelCase		(		lowercase      )   ->   Optional[Any]:
			__lowerCAmelCase   		=							{"""0""": """0""", """1""": """1"""}
			__lowerCAmelCase		,			__lowerCAmelCase   		=							"""""", """"""
			__lowerCAmelCase   		=							len(UpperCamelCase_      )

			for i in range(len(UpperCamelCase_      )      ):
						curr_string += data_bits[i]
						if curr_string not in lexicon:
									continue

						__lowerCAmelCase   		=							lexicon[curr_string]
						result += last_match_id
						add_key_to_lexicon(UpperCamelCase_   ,      UpperCamelCase_   ,      UpperCamelCase_   ,      UpperCamelCase_      )
						index += 1
						__lowerCAmelCase   		=							""""""

			while curr_string != "" and curr_string not in lexicon:
						curr_string += "0"

			if curr_string != "":
						__lowerCAmelCase   		=							lexicon[curr_string]
						result += last_match_id

			return result





def   _lowerCAmelCase		(		lowercase   ,      lowercase      )   ->   Optional[Any]:
			__lowerCAmelCase   		=							os.path.getsize(UpperCamelCase_      )
			__lowerCAmelCase   		=							bin(UpperCamelCase_      )[2:]
			__lowerCAmelCase   		=							len(UpperCamelCase_      )

			return "0" * (length_length - 1) + file_length_binary + compressed





def   _lowerCAmelCase		(		lowercase   ,      lowercase      )   ->   Any:
			__lowerCAmelCase   		=							8
			try:
						with open(UpperCamelCase_   ,      """wb"""      ) as opened_file:
									__lowerCAmelCase   		=							[
									    to_write[i : i + byte_length]
									    for i in range(0   ,      len(UpperCamelCase_      )   ,      UpperCamelCase_      )
									]

									if len(result_byte_array[-1]      ) % byte_length == 0:
												result_byte_array.append("""10000000"""      )
									else:
												result_byte_array[-1] += "1" + "0" * (
												    byte_length - len(result_byte_array[-1]      ) - 1
												)

									for elem in result_byte_array:
												opened_file.write(int(UpperCamelCase_   ,      2      ).to_bytes(1   ,      byteorder="""big"""      )      )
			except OSError:
						print("""File not accessible"""      )
						sys.exit()





def   _lowerCAmelCase		(		lowercase   ,      lowercase      )   ->   Optional[Any]:
			__lowerCAmelCase   		=							read_file_binary(UpperCamelCase_      )
			__lowerCAmelCase   		=							compress_data(UpperCamelCase_      )
			__lowerCAmelCase   		=							add_file_length(UpperCamelCase_   ,      UpperCamelCase_      )
			write_file_binary(UpperCamelCase_   ,      UpperCamelCase_      )


if __name__ == "__main__":
	compress(sys.argv[1], sys.argv[2])





'''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 					__lowerCAmelCase   (   unittest.TestCase						):

						"""simple docstring"""






						@slow
						def 				_UpperCAmelCase       (  self							:      Dict	):
													for model_name in ["bert-base-cased", "bert-large-uncased"]:
																				with self.subTest(lowerCAmelCase	):
																											A_			    =		AutoConfig.from_pretrained(lowerCAmelCase	)
																											self.assertIsNotNone(lowerCAmelCase	)
																											self.assertIsInstance(lowerCAmelCase ,  lowerCAmelCase	)

																											A_			    =		FlaxAutoModel.from_pretrained(lowerCAmelCase	)
																											self.assertIsNotNone(lowerCAmelCase	)
																											self.assertIsInstance(lowerCAmelCase ,  lowerCAmelCase	)






						@slow
						def 				_UpperCAmelCase       (  self							:      Union[str, Any]	):
													for model_name in ["roberta-base", "roberta-large"]:
																				with self.subTest(lowerCAmelCase	):
																											A_			    =		AutoConfig.from_pretrained(lowerCAmelCase	)
																											self.assertIsNotNone(lowerCAmelCase	)
																											self.assertIsInstance(lowerCAmelCase ,  lowerCAmelCase	)

																											A_			    =		FlaxAutoModel.from_pretrained(lowerCAmelCase	)
																											self.assertIsNotNone(lowerCAmelCase	)
																											self.assertIsInstance(lowerCAmelCase ,  lowerCAmelCase	)






						@slow
						def 				_UpperCAmelCase       (  self							:      List[Any]	):
													for model_name in ["bert-base-cased", "bert-large-uncased"]:
																				A_			    =		AutoTokenizer.from_pretrained(lowerCAmelCase	)
																				A_			    =		FlaxBertModel.from_pretrained(lowerCAmelCase	)
																				A_			    =		tokenizer("Do you support jax jitted function?" ,  return_tensors=TensorType.JAX	)

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

																				eval(**lowerCAmelCase	).block_until_ready()






						@slow
						def 				_UpperCAmelCase       (  self							:      str	):
													for model_name in ["roberta-base", "roberta-large"]:
																				A_			    =		AutoTokenizer.from_pretrained(lowerCAmelCase	)
																				A_			    =		FlaxRobertaModel.from_pretrained(lowerCAmelCase	)
																				A_			    =		tokenizer("Do you support jax jitted function?" ,  return_tensors=TensorType.JAX	)

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

																				eval(**lowerCAmelCase	).block_until_ready()






						def 				_UpperCAmelCase       (  self							:      List[Any]	):
													with self.assertRaisesRegex(
													    lowerCAmelCase ,  "bert-base is not a local folder and is not a valid model identifier"	):
																				A_			    =		FlaxAutoModel.from_pretrained("bert-base"	)






						def 				_UpperCAmelCase       (  self							:      Any	):
													with self.assertRaisesRegex(
													    lowerCAmelCase ,  r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"	):
																				A_			    =		FlaxAutoModel.from_pretrained(lowerCAmelCase ,  revision="aaaaaa"	)






						def 				_UpperCAmelCase       (  self							:      Dict	):
													with self.assertRaisesRegex(
													    lowerCAmelCase ,  "hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack" ,  ):
																				A_			    =		FlaxAutoModel.from_pretrained("hf-internal-testing/config-no-model"	)






						def 				_UpperCAmelCase       (  self							:      Any	):
													with self.assertRaisesRegex(lowerCAmelCase ,  "Use `from_pt=True` to load this model"	):
																				A_			    =		FlaxAutoModel.from_pretrained("hf-internal-testing/tiny-bert-pt-only"	)





