'''simple docstring'''




def 							lowerCamelCase			(   )    ->   list[list[int]]:
       return [list(range(1000 - i   ,   -1000 - i   ,   -1				)				) for i in range(1000				)]


_lowercase		:				Optional[Any]	       =		generate_large_matrix()
_lowercase		:				Dict	       =		(
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)




def 							lowerCamelCase			(   UpperCAmelCase__ :      Optional[int]				)    ->   None:
       assert all(row == sorted(_lowerCAmelCase   ,   reverse=_lowerCAmelCase				) for row in grid				)
       assert all(list(_lowerCAmelCase				) == sorted(_lowerCAmelCase   ,   reverse=_lowerCAmelCase				) for col in zip(*_lowerCAmelCase				)				)




def 							lowerCamelCase			(   UpperCAmelCase__ :      Dict				)    ->   int:
       lowercase_      :    List[str]       		= 0
       lowercase_      :    Optional[Any]       		= len(_lowerCAmelCase				) - 1

       # Edge cases such as no values or all numbers are negative.
       if not array or array[0] < 0:
              return 0

       while right + 1 > left:
              lowercase_      :    int       		= (left + right) // 2
              lowercase_      :    List[Any]       		= array[mid]

              # Num must be negative and the index must be greater than or equal to 0.
              if num < 0 and array[mid - 1] >= 0:
                     return mid

              if num >= 0:
                     lowercase_      :    Optional[int]       		= mid + 1
              else:
                     lowercase_      :    Union[str, Any]       		= mid - 1
                      # No negative numbers so return the last index of the array + 1 which is the length.
       return len(_lowerCAmelCase				)




def 							lowerCamelCase			(   UpperCAmelCase__ :      Dict				)    ->   int:
       lowercase_      :    List[Any]       		= 0
       lowercase_      :    Any       		= len(grid[0]				)

       for i in range(len(_lowerCAmelCase				)				):
              lowercase_      :    Union[str, Any]       		= find_negative_index(grid[i][:bound]				)
              total += bound
       return (len(_lowerCAmelCase				) * len(grid[0]				)) - total




def 							lowerCamelCase			(   UpperCAmelCase__ :      Tuple				)    ->   int:
       return len([number for row in grid for number in row if number < 0]				)




def 							lowerCamelCase			(   UpperCAmelCase__ :      Optional[Any]				)    ->   int:
       lowercase_      :    List[str]       		= 0
       for row in grid:
              for i, number in enumerate(_lowerCAmelCase				):
                     if number < 0:
                            total += len(_lowerCAmelCase				) - i
                            break
       return total




def 							lowerCamelCase			(   )    ->   None:
       from timeit import timeit

       print("""Running benchmarks"""				)
       lowercase_      :    Dict       		= (
           "from __main__ import count_negatives_binary_search, "
           "count_negatives_brute_force, count_negatives_brute_force_with_break, grid"
       )
       for func in (
           "count_negatives_binary_search",  # took 0.7727 seconds
           "count_negatives_brute_force_with_break",  # took 4.6505 seconds
           "count_negatives_brute_force",  # took 12.8160 seconds
       ):
              lowercase_      :    List[str]       		= timeit(F'''{func}(grid=grid)'''   ,   setup=_lowerCAmelCase   ,   number=500				)
              print(F'''{func}() took {time:0.4f} seconds'''				)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      benchmark()






'''simple docstring'''




import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow





@require_torch
class 					__magic_name__		(					unittest.TestCase):







			def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]					):
										lowercase_      :    List[Any]       		= """ylacombe/bark-small"""
										lowercase_      :    List[str]       		= tempfile.mkdtemp()
										lowercase_      :    Tuple       		= """en_speaker_1"""
										lowercase_      :    Union[str, Any]       		= """This is a test string"""
										lowercase_      :    int       		= """speaker_embeddings_path.json"""
										lowercase_      :    Any       		= """speaker_embeddings"""







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple       ,    **lowercase_       :						Optional[int]					):
										return AutoTokenizer.from_pretrained(self.checkpoint       ,    **lowercase_					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						str					):
										shutil.rmtree(self.tmpdirname					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						List[str]					):
										lowercase_      :    Any       		= self.get_tokenizer()

										lowercase_      :    Optional[Any]       		= BarkProcessor(tokenizer=lowercase_					)

										processor.save_pretrained(self.tmpdirname					)
										lowercase_      :    Union[str, Any]       		= BarkProcessor.from_pretrained(self.tmpdirname					)

										self.assertEqual(processor.tokenizer.get_vocab()       ,    tokenizer.get_vocab()					)







			@slow
			def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]					):
										lowercase_      :    Any       		= BarkProcessor.from_pretrained(
										    pretrained_processor_name_or_path=self.checkpoint       ,    speaker_embeddings_dict_path=self.speaker_embeddings_dict_path       ,    )
										processor.save_pretrained(
										    self.tmpdirname       ,    speaker_embeddings_dict_path=self.speaker_embeddings_dict_path       ,    speaker_embeddings_directory=self.speaker_embeddings_directory       ,    )

										lowercase_      :    List[str]       		= self.get_tokenizer(bos_token="""(BOS)"""       ,    eos_token="""(EOS)"""					)

										lowercase_      :    Optional[Any]       		= BarkProcessor.from_pretrained(
										    self.tmpdirname       ,    self.speaker_embeddings_dict_path       ,    bos_token="""(BOS)"""       ,    eos_token="""(EOS)"""       ,    )

										self.assertEqual(processor.tokenizer.get_vocab()       ,    tokenizer_add_kwargs.get_vocab()					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[int]					):
										lowercase_      :    Optional[int]       		= BarkProcessor.from_pretrained(
										    pretrained_processor_name_or_path=self.checkpoint       ,    speaker_embeddings_dict_path=self.speaker_embeddings_dict_path       ,    )

										lowercase_      :    Optional[int]       		= 35
										lowercase_      :    int       		= 2
										lowercase_      :    Union[str, Any]       		= 8

										lowercase_      :    Union[str, Any]       		= {
										    """semantic_prompt""": np.ones(lowercase_					),
										    """coarse_prompt""": np.ones((nb_codebooks_coarse, seq_len)					),
										    """fine_prompt""": np.ones((nb_codebooks_total, seq_len)					),
										}

										# test providing already loaded voice_preset
										lowercase_      :    str       		= processor(text=self.input_string       ,    voice_preset=lowercase_					)

										lowercase_      :    Dict       		= inputs["""history_prompt"""]
										for key in voice_preset:
																	self.assertListEqual(voice_preset[key].tolist()       ,    processed_voice_preset.get(lowercase_       ,    np.array([]					)					).tolist()					)

										# test loading voice preset from npz file
										lowercase_      :    Any       		= os.path.join(self.tmpdirname       ,    """file.npz"""					)
										np.savez(lowercase_       ,    **lowercase_					)
										lowercase_      :    Optional[Any]       		= processor(text=self.input_string       ,    voice_preset=lowercase_					)
										lowercase_      :    List[Any]       		= inputs["""history_prompt"""]

										for key in voice_preset:
																	self.assertListEqual(voice_preset[key].tolist()       ,    processed_voice_preset.get(lowercase_       ,    np.array([]					)					).tolist()					)

										# test loading voice preset from the hub
										lowercase_      :    Union[str, Any]       		= processor(text=self.input_string       ,    voice_preset=self.voice_preset					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple					):
										lowercase_      :    List[str]       		= self.get_tokenizer()

										lowercase_      :    int       		= BarkProcessor(tokenizer=lowercase_					)

										lowercase_      :    Any       		= processor(text=self.input_string					)

										lowercase_      :    List[str]       		= tokenizer(
										    self.input_string       ,    padding="""max_length"""       ,    max_length=256       ,    add_special_tokens=lowercase_       ,    return_attention_mask=lowercase_       ,    return_token_type_ids=lowercase_       ,    )

										for key in encoded_tok.keys():
																	self.assertListEqual(encoded_tok[key]       ,    encoded_processor[key].squeeze().tolist()					)





