






import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


lowerCamelCase__							=     50_0000

lowerCamelCase__		,			lowerCamelCase__							=     os.path.split(__file__)
lowerCamelCase__							=     os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))






@get_duration
def   UpperCamelCase  (       snake_case__     :   datasets.Dataset	,**snake_case__     :   int  ):




     '''simple docstring'''






     __snake_case			:List[str]          =						dataset.map(**snake_case__  )






@get_duration
def   UpperCamelCase  (       snake_case__     :   datasets.Dataset	,**snake_case__     :   Any  ):




     '''simple docstring'''






     __snake_case			:str          =						dataset.filter(**snake_case__  )






def   UpperCamelCase  (       ):




     '''simple docstring'''






     __snake_case			:Union[str, Any]          =						{"""num examples""": SPEED_TEST_N_EXAMPLES}
     with tempfile.TemporaryDirectory() as tmp_dir:
          __snake_case			:int          =						datasets.Features({"""text""": datasets.Value("""string"""  ), """numbers""": datasets.Value("""float32"""  )}  )
          __snake_case			:Any          =						generate_example_dataset(
              os.path.join(snake_case__	,"""dataset.arrow"""  )	,snake_case__	,num_examples=snake_case__  )

          __snake_case			:Union[str, Any]          =						transformers.AutoTokenizer.from_pretrained("""bert-base-cased"""	,use_fast=snake_case__  )

          def tokenize(snake_case__     :   Union[str, Any]  ):
               return tokenizer(examples["""text"""]  )

          __snake_case			:Optional[Any]          =						map(snake_case__  )

          __snake_case			:Tuple          =						map(snake_case__	,batched=snake_case__  )

          __snake_case			:Optional[Any]          =						map(snake_case__	,function=lambda snake_case__  : None	,batched=snake_case__  )

          with dataset.formatted_as(type="""numpy"""  ):
               __snake_case			:Tuple          =						map(snake_case__	,function=lambda snake_case__  : None	,batched=snake_case__  )

          with dataset.formatted_as(type="""pandas"""  ):
               __snake_case			:int          =						map(snake_case__	,function=lambda snake_case__  : None	,batched=snake_case__  )

          with dataset.formatted_as(type="""torch"""	,columns="""numbers"""  ):
               __snake_case			:List[Any]          =						map(snake_case__	,function=lambda snake_case__  : None	,batched=snake_case__  )

          with dataset.formatted_as(type="""tensorflow"""	,columns="""numbers"""  ):
               __snake_case			:Tuple          =						map(snake_case__	,function=lambda snake_case__  : None	,batched=snake_case__  )

          __snake_case			:List[Any]          =						map(snake_case__	,function=snake_case__	,batched=snake_case__  )

          __snake_case			:List[Any]          =						filter(snake_case__  )

          # Activate later when tokenizer support batched inputs
          # with dataset.formatted_as(type='numpy'):
          #     times[func.__name__ + " fast-tokenizer batched numpy"] = func(dataset, function=tokenize, batched=True)

     with open(snake_case__	,"""wb"""  ) as f:
          f.write(json.dumps(snake_case__  ).encode("""utf-8"""  )  )


if __name__ == "__main__":  # useful to run the profiler
     benchmark_map_filter()










import os






def   UpperCamelCase  (       ):




     '''simple docstring'''






     __snake_case			:List[str]          =						os.path.dirname(os.path.realpath(snake_case__  )  )
     __snake_case			:Union[str, Any]          =						os.path.join(snake_case__	,"""triangle.txt"""  )

     with open(snake_case__  ) as f:
          __snake_case			:int          =						f.readlines()

     __snake_case			:int          =						[]
     for line in triangle:
          __snake_case			:List[Any]          =						[]
          for number in line.strip().split(""" """  ):
               numbers_from_line.append(int(snake_case__  )  )
          a.append(snake_case__  )

     for i in range(1	,len(snake_case__  )  ):
          for j in range(len(a[i]  )  ):
               __snake_case			:Union[str, Any]          =						a[i - 1][j] if j != len(a[i - 1]  ) else 0
               __snake_case			:Dict          =						a[i - 1][j - 1] if j > 0 else 0
               a[i][j] += max(snake_case__	,snake_case__  )
     return max(a[-1]  )


if __name__ == "__main__":
     print(solution())


