


'''simple docstring'''



import math
import os
import sys







def 			_UpperCamelCase					(						UpperCamelCase__    ):
			UpperCAmelCase__     :    Optional[Any]         =   """"""
			try:
						with open(A__       ,					"""rb"""    ) as binary_file:
									UpperCAmelCase__     :    Optional[Any]         =   binary_file.read()
						for dat in data:
									UpperCAmelCase__     :    List[str]         =   f'''{dat:08b}'''
									result += curr_byte
						return result
			except OSError:
						print("""File not accessible"""    )
						sys.exit()







def 			_UpperCamelCase					(						UpperCamelCase__       ,					UpperCamelCase__       ,					UpperCamelCase__       ,					UpperCamelCase__    ):
			lexicon.pop(A__    )
			UpperCAmelCase__     :    int         =   last_match_id

			if math.loga(A__    ).is_integer():
						for curr_key in lexicon:
									UpperCAmelCase__     :    Optional[int]         =   """0""" + lexicon[curr_key]

			UpperCAmelCase__     :    Union[str, Any]         =   bin(A__    )[2:]







def 			_UpperCamelCase					(						UpperCamelCase__    ):
			UpperCAmelCase__     :    Optional[int]         =   {"""0""": """0""", """1""": """1"""}
			UpperCAmelCase__      ,				UpperCAmelCase__     :    int         =   """""", """"""
			UpperCAmelCase__     :    Union[str, Any]         =   len(A__    )

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

						UpperCAmelCase__     :    List[Any]         =   lexicon[curr_string]
						result += last_match_id
						add_key_to_lexicon(A__       ,					A__       ,					A__       ,					A__    )
						index += 1
						UpperCAmelCase__     :    str         =   """"""

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

			if curr_string != "":
						UpperCAmelCase__     :    Optional[Any]         =   lexicon[curr_string]
						result += last_match_id

			return result







def 			_UpperCamelCase					(						UpperCamelCase__       ,					UpperCamelCase__    ):
			UpperCAmelCase__     :    Dict         =   os.path.getsize(A__    )
			UpperCAmelCase__     :    Union[str, Any]         =   bin(A__    )[2:]
			UpperCAmelCase__     :    Tuple         =   len(A__    )

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







def 			_UpperCamelCase					(						UpperCamelCase__       ,					UpperCamelCase__    ):
			UpperCAmelCase__     :    Optional[int]         =   8
			try:
						with open(A__       ,					"""wb"""    ) as opened_file:
									UpperCAmelCase__     :    Tuple         =   [
									    to_write[i : i + byte_length]
									    for i in range(0       ,					len(A__    )       ,					A__    )
									]

									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(A__       ,					2    ).to_bytes(1       ,					byteorder="""big"""    )    )
			except OSError:
						print("""File not accessible"""    )
						sys.exit()







def 			_UpperCamelCase					(						UpperCamelCase__       ,					UpperCamelCase__    ):
			UpperCAmelCase__     :    Union[str, Any]         =   read_file_binary(A__    )
			UpperCAmelCase__     :    Union[str, Any]         =   compress_data(A__    )
			UpperCAmelCase__     :    Dict         =   add_file_length(A__       ,					A__    )
			write_file_binary(A__       ,					A__    )


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





from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch

from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch





@require_torch
@require_tf
class     lowerCamelCase__(					__lowerCamelCase):
      def 			lowerCAmelCase__						(				self: List[Any]   ):
             __lowerCamelCase   =						SMALL_MODEL_IDENTIFIER
             __lowerCamelCase   =						"""pt"""
             __lowerCamelCase   =						"""tf"""
      def 			lowerCAmelCase__						(				self: Optional[Any]    ,       UpperCamelCase_: Optional[Any]   ):
             __lowerCamelCase   =						AutoModel.from_pretrained(self.test_model   )
             model_pt.save_pretrained(UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: Tuple    ,       UpperCamelCase_: Union[str, Any]   ):
             __lowerCamelCase   =						TFAutoModel.from_pretrained(self.test_model    ,       from_pt=UpperCamelCase_   )
             model_tf.save_pretrained(UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: Union[str, Any]   ):
             __lowerCamelCase   =						"""mock_framework"""

             # Framework provided - return whatever the user provides
             __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model    ,       UpperCamelCase_   )
             self.assertEqual(UpperCamelCase_    ,       UpperCamelCase_   )

             # Local checkpoint and framework provided - return provided framework
             # PyTorch checkpoint
             with TemporaryDirectory() as local_pt_ckpt:
                    self._setup_pt_ckpt(UpperCamelCase_   )
                    __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_    ,       UpperCamelCase_   )
                    self.assertEqual(UpperCamelCase_    ,       UpperCamelCase_   )

             # TensorFlow checkpoint
             with TemporaryDirectory() as local_tf_ckpt:
                    self._setup_tf_ckpt(UpperCamelCase_   )
                    __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_    ,       UpperCamelCase_   )
                    self.assertEqual(UpperCamelCase_    ,       UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: int   ):
             # PyTorch checkpoint
             with TemporaryDirectory() as local_pt_ckpt:
                    self._setup_pt_ckpt(UpperCamelCase_   )
                    __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_pt   )

             # TensorFlow checkpoint
             with TemporaryDirectory() as local_tf_ckpt:
                    self._setup_tf_ckpt(UpperCamelCase_   )
                    __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_tf   )

             # Invalid local checkpoint
             with TemporaryDirectory() as local_invalid_ckpt:
                    with self.assertRaises(UpperCamelCase_   ):
                           __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_   )




      def 			lowerCAmelCase__						(				self: Optional[int]   ):
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             with patch("""transformers.onnx.features.is_tf_available"""    ,       UpperCamelCase_   ):
                    __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_pt   )

             # PyTorch not in environment -> use TensorFlow
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             with patch("""transformers.onnx.features.is_torch_available"""    ,       UpperCamelCase_   ):
                    __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_tf   )

             # Both in environment -> use PyTorch
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             with patch("""transformers.onnx.features.is_tf_available"""    ,       UpperCamelCase_   ), patch(
                 """transformers.onnx.features.is_torch_available"""    ,       UpperCamelCase_   ):
                    __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_pt   )

             # Both not in environment -> raise error
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             with patch("""transformers.onnx.features.is_tf_available"""    ,       UpperCamelCase_   ), patch(
                 """transformers.onnx.features.is_torch_available"""    ,       UpperCamelCase_   ):
                    with self.assertRaises(UpperCamelCase_   ):
                           __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model   )

