'''simple docstring'''




import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow


if is_torch_available():
 import torch

 from transformers import XLMRobertaModel


@require_sentencepiece
@require_tokenizers
@require_torch
class       UpperCAmelCase__  (       unittest.TestCase			):
   @slow
   def 		_lowerCamelCase (self				)    ->     Optional[int]:
        lowercase_					:       int     				=					XLMRobertaModel.from_pretrained('xlm-roberta-base'				)
        lowercase_					:       Union[str, Any]     				=					torch.tensor([[0, 581, 10_269, 83, 99_942, 136, 60_742, 23, 70, 80_583, 18_276, 2]]				)
        # The dog is cute and lives in the garden house

        lowercase_					:       str     				=					torch.Size((1, 12, 768)				)  # batch_size, sequence_length, embedding_vector_dim
        lowercase_					:       Union[str, Any]     				=					torch.tensor(
            [[-0.01_01, 0.12_18, -0.08_03, 0.08_01, 0.13_27, 0.07_76, -0.12_15, 0.23_83, 0.33_38, 0.31_06, 0.03_00, 0.02_52]]				)
        #  xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')
        #  xlmr.eval()
        #  expected_output_values_last_dim = xlmr.extract_features(input_ids[0])[:, :, -1]
        with torch.no_grad():
             lowercase_					:       Dict     				=					model(_a				)['last_hidden_state'].detach()
        self.assertEqual(output.shape       ,				_a				)
        # compare the actual values for a slice of last dim
        self.assertTrue(torch.allclose(output[:, :, -1]       ,				_a       ,				atol=1e-3				)				)





   @slow
   def 		_lowerCamelCase (self				)    ->     Optional[Any]:
        lowercase_					:       Union[str, Any]     				=					XLMRobertaModel.from_pretrained('xlm-roberta-large'				)
        lowercase_					:       Union[str, Any]     				=					torch.tensor([[0, 581, 10_269, 83, 99_942, 136, 60_742, 23, 70, 80_583, 18_276, 2]]				)
        # The dog is cute and lives in the garden house

        lowercase_					:       Dict     				=					torch.Size((1, 12, 1_024)				)  # batch_size, sequence_length, embedding_vector_dim
        lowercase_					:       Dict     				=					torch.tensor(
            [[-0.06_99, -0.03_18, 0.07_05, -0.12_41, 0.09_99, -0.05_20, 0.10_04, -0.18_38, -0.47_04, 0.14_37, 0.08_21, 0.01_26]]				)
        #  xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.large')
        #  xlmr.eval()
        #  expected_output_values_last_dim = xlmr.extract_features(input_ids[0])[:, :, -1]
        with torch.no_grad():
             lowercase_					:       List[str]     				=					model(_a				)['last_hidden_state'].detach()
        self.assertEqual(output.shape       ,				_a				)
        # compare the actual values for a slice of last dim
        self.assertTrue(torch.allclose(output[:, :, -1]       ,				_a       ,				atol=1e-3				)				)





'''simple docstring'''




import math
import os
import sys

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

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lexicon.pop(SCREAMING_SNAKE_CASE_							)
     lowercase_					:       Any     				=					last_match_id

     if math.loga(SCREAMING_SNAKE_CASE_							).is_integer():
          for curr_key in lexicon:
               lowercase_					:       Tuple     				=					'0' + lexicon[curr_key]

     lowercase_					:       Any     				=					bin(SCREAMING_SNAKE_CASE_							)[2:]

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       Dict     				=					{'0': '0', '1': '1'}
     lowercase_				,lowercase_					:       Any     				=					'', ''
     lowercase_					:       List[Any]     				=					len(SCREAMING_SNAKE_CASE_							)

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

          lowercase_					:       str     				=					lexicon[curr_string]
          result += last_match_id
          add_key_to_lexicon(SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							)
          index += 1
          lowercase_					:       List[Any]     				=					''

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

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

     return result

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       List[str]     				=					os.path.getsize(SCREAMING_SNAKE_CASE_							)
     lowercase_					:       Any     				=					bin(SCREAMING_SNAKE_CASE_							)[2:]
     lowercase_					:       Optional[Any]     				=					len(SCREAMING_SNAKE_CASE_							)

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

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       List[str]     				=					8
     try:
          with open(SCREAMING_SNAKE_CASE_  ,       'wb'							) as opened_file:
               lowercase_					:       List[Any]     				=					[
                   to_write[i : i + byte_length]
                   for i in range(0  ,       len(SCREAMING_SNAKE_CASE_							)  ,       SCREAMING_SNAKE_CASE_							)
               ]

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

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       List[str]     				=					read_file_binary(SCREAMING_SNAKE_CASE_							)
     lowercase_					:       List[str]     				=					compress_data(SCREAMING_SNAKE_CASE_							)
     lowercase_					:       Union[str, Any]     				=					add_file_length(SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							)
     write_file_binary(SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							)


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




