



import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_snake_case		=  5_0000
_snake_case		=  5000

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






@get_duration
def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							for i in range(A__  ):
														_lowerCAmelCase     :							List[Any]    =    dataset[i]






@get_duration
def 				A				(					_lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							for i in range(0				, len(A__  )				, A__  ):
														_lowerCAmelCase     :							Dict    =    dataset[i : i + batch_size]






@get_duration
def 				A				(					_lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							with dataset.formatted_as(type=A__  ):
														for i in range(A__  ):
																					_lowerCAmelCase     :							List[Any]    =    dataset[i]






@get_duration
def 				A				(					_lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							with dataset.formatted_as(type=A__  ):
														for i in range(0				, A__				, A__  ):
																					_lowerCAmelCase     :							List[Any]    =    dataset[i : i + batch_size]






def 				A				(					):





							'''simple docstring'''




							_lowerCAmelCase     :							Dict    =    {"num examples": SPEED_TEST_N_EXAMPLES}
							_lowerCAmelCase     :							List[Any]    =    [
							    (read, {"length": SMALL_TEST}),
							    (read, {"length": SPEED_TEST_N_EXAMPLES}),
							    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 10}),
							    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 100}),
							    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 1_000}),
							    (read_formatted, {"type": "numpy", "length": SMALL_TEST}),
							    (read_formatted, {"type": "pandas", "length": SMALL_TEST}),
							    (read_formatted, {"type": "torch", "length": SMALL_TEST}),
							    (read_formatted, {"type": "tensorflow", "length": SMALL_TEST}),
							    (read_formatted_batch, {"type": "numpy", "length": SMALL_TEST, "batch_size": 10}),
							    (read_formatted_batch, {"type": "numpy", "length": SMALL_TEST, "batch_size": 1_000}),
							]

							_lowerCAmelCase     :							str    =    [
							    (read, {"length": SMALL_TEST}),
							    (read, {"length": SPEED_TEST_N_EXAMPLES}),
							    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 10}),
							    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 100}),
							    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 1_000}),
							    (read_formatted, {"type": "numpy", "length": SMALL_TEST}),
							    (read_formatted_batch, {"type": "numpy", "length": SMALL_TEST, "batch_size": 10}),
							    (read_formatted_batch, {"type": "numpy", "length": SMALL_TEST, "batch_size": 1_000}),
							]
							with tempfile.TemporaryDirectory() as tmp_dir:
														print("generating dataset"  )
														_lowerCAmelCase     :							str    =    datasets.Features(
														    {"list": datasets.Sequence(datasets.Value("float32"  )  ), "numbers": datasets.Value("float32"  )}  )
														_lowerCAmelCase     :							int    =    generate_example_dataset(
														    os.path.join(A__				, "dataset.arrow"  )				, A__				, num_examples=A__				, seq_shapes={"list": (100,)}				, )
														print("first set of iterations"  )
														for func, kwargs in functions:
																					print(func.__name__				, str(A__  )  )
																					_lowerCAmelCase     :							Union[str, Any]    =    func(A__				, **A__  )

														print("shuffling dataset"  )
														_lowerCAmelCase     :							Union[str, Any]    =    dataset.shuffle()
														print("Second set of iterations (after shuffling"  )
														for func, kwargs in functions_shuffled:
																					print("shuffled "				, func.__name__				, str(A__  )  )
																					_lowerCAmelCase     :							List[str]    =    func(
																					    A__				, **A__  )

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


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





'''simple docstring'''


import math

class  SCREAMING_SNAKE_CASE :






    """simple docstring"""





    def __init__(  self      :					Union[str, Any]  ,						UpperCamelCase__      :					Optional[Any]=0 ):  # a graph with Node 0,1,...,N-1


       """simple docstring"""







       UpperCamelCase					=  n
       UpperCamelCase					=  [
           [math.inf for j in range(0  ,						UpperCamelCase__ )] for i in range(0  ,						UpperCamelCase__ )
       ]  # adjacency matrix for weight
       UpperCamelCase					=  [
           [math.inf for j in range(0  ,						UpperCamelCase__ )] for i in range(0  ,						UpperCamelCase__ )
       ]  # dp[i][j] stores minimum distance from i to j






    def  A       (  self      :					Optional[Any]  ,						UpperCamelCase__      :					Union[str, Any]  ,						UpperCamelCase__      :					Union[str, Any]  ,						UpperCamelCase__      :					Tuple ):


       """simple docstring"""







       UpperCamelCase					=  w






    def  A       (  self      :					str ):


       """simple docstring"""







       for k in range(0  ,						self.n ):
          for i in range(0  ,						self.n ):
             for j in range(0  ,						self.n ):
                UpperCamelCase					=  min(self.dp[i][j]  ,						self.dp[i][k] + self.dp[k][j] )






    def  A       (  self      :					Optional[Any]  ,						UpperCamelCase__      :					str  ,						UpperCamelCase__      :					List[Any] ):


       """simple docstring"""







       return self.dp[u][v]


if __name__ == "__main__":
   _lowerCamelCase	:       List[str]      	=	Graph(5)
   graph.add_edge(0, 2, 9)
   graph.add_edge(0, 4, 10)
   graph.add_edge(1, 3, 5)
   graph.add_edge(2, 3, 7)
   graph.add_edge(3, 0, 10)
   graph.add_edge(3, 1, 2)
   graph.add_edge(3, 2, 1)
   graph.add_edge(3, 4, 6)
   graph.add_edge(4, 1, 3)
   graph.add_edge(4, 2, 4)
   graph.add_edge(4, 3, 9)
   graph.floyd_warshall()
   graph.show_min(1, 4)
   graph.show_min(0, 3)

