


import math
import sys


def 		lowercase_	(  _UpperCamelCase	):


			'''simple docstring'''







			__lowercase			       = ''''''
			try:
						with open(_UpperCamelCase							,      '''rb'''	) as binary_file:
									__lowercase			       = binary_file.read()
						for dat in data:
									__lowercase			       = F'{dat:08b}'
									result += curr_byte
						return result
			except OSError:
						print('''File not accessible'''	)
						sys.exit()


def 		lowercase_	(  _UpperCamelCase	):


			'''simple docstring'''







			__lowercase			       = {'''0''': '''0''', '''1''': '''1'''}
			__lowercase			       = '''''', ''''''
			__lowercase			       = len(_UpperCamelCase	)

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

						__lowercase			       = lexicon[curr_string]
						result += last_match_id
						__lowercase			       = last_match_id + '''0'''

						if math.loga(_UpperCamelCase	).is_integer():
									__lowercase			       = {}
									for curr_key in list(_UpperCamelCase	):
												__lowercase			       = lexicon.pop(_UpperCamelCase	)
									__lowercase			       = new_lex

						__lowercase			       = last_match_id + '''1'''
						index += 1
						__lowercase			       = ''''''
			return result


def 		lowercase_	(  _UpperCamelCase							,      _UpperCamelCase	):


			'''simple docstring'''







			__lowercase			       = 8
			try:
						with open(_UpperCamelCase							,      '''wb'''	) as opened_file:
									__lowercase			       = [
									    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[:-1]:
												opened_file.write(int(_UpperCamelCase							,      2	).to_bytes(1							,      byteorder='''big'''	)	)
			except OSError:
						print('''File not accessible'''	)
						sys.exit()


def 		lowercase_	(  _UpperCamelCase	):


			'''simple docstring'''







			__lowercase			       = 0
			for letter in data_bits:
						if letter == "1":
									break
						counter += 1

			__lowercase			       = data_bits[counter:]
			__lowercase			       = data_bits[counter + 1 :]
			return data_bits


def 		lowercase_	(  _UpperCamelCase							,      _UpperCamelCase	):


			'''simple docstring'''







			__lowercase			       = read_file_binary(_UpperCamelCase	)
			__lowercase			       = remove_prefix(_UpperCamelCase	)
			__lowercase			       = decompress_data(_UpperCamelCase	)
			write_file_binary(_UpperCamelCase							,      _UpperCamelCase	)


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





'''simple docstring'''





import re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


UpperCamelCase_    						=       logging.get_logger(__name__)






def 				_lowerCAmelCase			(   __magic_name__						:     List[str]						)				->  Dict:
						lowercase :							List[str]    		=R'''\w+[.]\d+'''
						lowercase :							List[str]    		=re.findall(__magic_name__   , __magic_name__						)
						for pat in pats:
												lowercase :							Optional[int]    		=key.replace(__magic_name__   , '''_'''.join(pat.split('''.'''						)						)						)
						return key






def 				_lowerCAmelCase			(   __magic_name__						:     List[str]   , __magic_name__						:     Union[str, Any]   , __magic_name__						:     Dict						)				->  str:
						lowercase :							Dict    		=pt_tuple_key[:-1] + ('''scale''',)
						if (
						    any('''norm''' in str_ for str_ in pt_tuple_key						)
						    and (pt_tuple_key[-1] == "bias")
						    and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
						    and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
						):
												lowercase :							str    		=pt_tuple_key[:-1] + ('''scale''',)
												return renamed_pt_tuple_key, pt_tensor
						elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
												lowercase :							str    		=pt_tuple_key[:-1] + ('''scale''',)
												return renamed_pt_tuple_key, pt_tensor

						# embedding
						if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
												lowercase :							Dict    		=pt_tuple_key[:-1] + ('''embedding''',)
												return renamed_pt_tuple_key, pt_tensor

						# conv layer
						lowercase :							Tuple    		=pt_tuple_key[:-1] + ('''kernel''',)
						if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
												lowercase :							Tuple    		=pt_tensor.transpose(2   , 3   , 1   , 0						)
												return renamed_pt_tuple_key, pt_tensor

						# linear layer
						lowercase :							str    		=pt_tuple_key[:-1] + ('''kernel''',)
						if pt_tuple_key[-1] == "weight":
												lowercase :							Optional[Any]    		=pt_tensor.T
												return renamed_pt_tuple_key, pt_tensor

						# old PyTorch layer norm weight
						lowercase :							Dict    		=pt_tuple_key[:-1] + ('''weight''',)
						if pt_tuple_key[-1] == "gamma":
												return renamed_pt_tuple_key, pt_tensor

						# old PyTorch layer norm bias
						lowercase :							Union[str, Any]    		=pt_tuple_key[:-1] + ('''bias''',)
						if pt_tuple_key[-1] == "beta":
												return renamed_pt_tuple_key, pt_tensor

						return pt_tuple_key, pt_tensor







def 				_lowerCAmelCase			(   __magic_name__						:     int   , __magic_name__						:     Optional[Any]   , __magic_name__						:     Union[str, Any]=42						)				->  List[str]:
						# Step 1: Convert pytorch tensor to numpy
						lowercase :							Optional[Any]    		={k: v.numpy() for k, v in pt_state_dict.items()}

						# Step 2: Since the model is stateless, get random Flax params
						lowercase :							str    		=flax_model.init_weights(PRNGKey(__magic_name__						)						)

						lowercase :							Dict    		=flatten_dict(__magic_name__						)
						lowercase :							Dict    		={}

						# Need to change some parameters name to match Flax names
						for pt_key, pt_tensor in pt_state_dict.items():
												lowercase :							Dict    		=rename_key(__magic_name__						)
												lowercase :							Optional[int]    		=tuple(renamed_pt_key.split('''.'''						)						)

												# Correctly rename weight parameters
												lowercase		,	lowercase :							Any    		=rename_key_and_reshape_tensor(__magic_name__   , __magic_name__   , __magic_name__						)

												if flax_key in random_flax_state_dict:
																		if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
																								raise ValueError(
																								    f'''PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape '''
																								    f'''{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}.'''						)

        # also add unexpected weight so that warning is thrown
												lowercase :							Tuple    		=jnp.asarray(__magic_name__						)

						return unflatten_dict(__magic_name__						)





