



"""simple docstring"""





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


lowerCamelCase  			=		50_000
lowerCamelCase  			=		5_000

lowerCamelCase			,		lowerCamelCase  			=		os.path.split(__file__)
lowerCamelCase  			=		os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))
@get_duration
def   a__      ( lowerCAmelCase__      ,     lowerCAmelCase__ ):
      for i in range(lowerCAmelCase__ ):
            UpperCAmelCase_     					=				dataset[i]
@get_duration
def   a__      ( lowerCAmelCase__      ,     lowerCAmelCase__      ,     lowerCAmelCase__ ):
      for i in range(0      ,     len(lowerCAmelCase__ )      ,     lowerCAmelCase__ ):
            UpperCAmelCase_     					=				dataset[i : i + batch_size]
@get_duration
def   a__      ( lowerCAmelCase__      ,     lowerCAmelCase__      ,     lowerCAmelCase__ ):
      with dataset.formatted_as(type=lowerCAmelCase__ ):
            for i in range(lowerCAmelCase__ ):
                  UpperCAmelCase_     					=				dataset[i]
@get_duration
def   a__      ( lowerCAmelCase__      ,     lowerCAmelCase__      ,     lowerCAmelCase__      ,     lowerCAmelCase__ ):
      with dataset.formatted_as(type=lowerCAmelCase__ ):
            for i in range(0      ,     lowerCAmelCase__      ,     lowerCAmelCase__ ):
                  UpperCAmelCase_     					=				dataset[i : i + batch_size]
def   a__      ( ):
      UpperCAmelCase_     					=				{"num examples": SPEED_TEST_N_EXAMPLES}
      UpperCAmelCase_     					=				[
          (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": 1000}),
          (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": 1000}),
      ]

      UpperCAmelCase_     					=				[
          (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": 1000}),
          (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": 1000}),
      ]
      with tempfile.TemporaryDirectory() as tmp_dir:
            print("generating dataset" )
            UpperCAmelCase_     					=				datasets.Features(
                {"list": datasets.Sequence(datasets.Value("float32" ) ), "numbers": datasets.Value("float32" )} )
            UpperCAmelCase_     					=				generate_example_dataset(
                os.path.join(lowerCAmelCase__      ,     "dataset.arrow" )      ,     lowerCAmelCase__      ,     num_examples=lowerCAmelCase__      ,     seq_shapes={"list": (100,)}      ,     )
            print("first set of iterations" )
            for func, kwargs in functions:
                  print(func.__name__      ,     str(lowerCAmelCase__ ) )
                  UpperCAmelCase_     					=				func(lowerCAmelCase__      ,     **lowerCAmelCase__ )

            print("shuffling dataset" )
            UpperCAmelCase_     					=				dataset.shuffle()
            print("Second set of iterations (after shuffling" )
            for func, kwargs in functions_shuffled:
                  print("shuffled "      ,     func.__name__      ,     str(lowerCAmelCase__ ) )
                  UpperCAmelCase_     					=				func(
                      lowerCAmelCase__      ,     **lowerCAmelCase__ )

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


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












'''simple docstring'''



def 				lowercase_					(     __A			:							int       ,   __A			:							int      )							->   int:



 """simple docstring"""




 return 1 if input_a == input_a else 0


def 				lowercase_					(     )							->   None:



 """simple docstring"""




 assert xnor_gate(0       ,   0      ) == 1
 assert xnor_gate(0       ,   1      ) == 0
 assert xnor_gate(1       ,   0      ) == 0
 assert xnor_gate(1       ,   1      ) == 1


if __name__ == "__main__":
      print(xnor_gate(0, 0))
      print(xnor_gate(0, 1))
      print(xnor_gate(1, 0))
      print(xnor_gate(1, 1))



