
import math

import qiskit


def    a      ( a = 1		,						a = 1		,						a = 1	)     ->qiskit.result.counts.Counts:




			'''simple docstring'''


			if (
			    isinstance(a		,						a	)
			    or isinstance(a		,						a	)
			    or isinstance(a		,						a	)
			):
						raise TypeError('''inputs must be integers.'''	)

			if (input_a < 0) or (input_a < 0) or (carry_in < 0):
						raise ValueError('''inputs must be positive.'''	)

			if (
			    (math.floor(a	) != input_a)
			    or (math.floor(a	) != input_a)
			    or (math.floor(a	) != carry_in)
			):
						raise ValueError('''inputs must be exact integers.'''	)

			if (input_a > 2) or (input_a > 2) or (carry_in > 2):
						raise ValueError('''inputs must be less or equal to 2.'''	)

			# build registers
			SCREAMING_SNAKE_CASE     						= qiskit.QuantumRegister(4		,						'''qr'''	)
			SCREAMING_SNAKE_CASE     						= qiskit.ClassicalRegister(2		,						'''cr'''	)
			# list the entries
			SCREAMING_SNAKE_CASE     						= [input_a, input_a, carry_in]

			SCREAMING_SNAKE_CASE     						= qiskit.QuantumCircuit(a		,						a	)

			for i in range(0		,						3	):
						if entry[i] == 2:
									quantum_circuit.h(a	)  # for hadamard entries
						elif entry[i] == 1:
									quantum_circuit.x(a	)  # for 1 entries
						elif entry[i] == 0:
									quantum_circuit.i(a	)  # for 0 entries

    # build the circuit
			quantum_circuit.ccx(0		,						1		,						3	)  # ccx = toffoli gate
			quantum_circuit.cx(0		,						1	)
			quantum_circuit.ccx(1		,						2		,						3	)
			quantum_circuit.cx(1		,						2	)
			quantum_circuit.cx(0		,						1	)

			quantum_circuit.measure([2, 3]		,						a	)  # measure the last two qbits

			SCREAMING_SNAKE_CASE     						= qiskit.Aer.get_backend('''aer_simulator'''	)
			SCREAMING_SNAKE_CASE     						= qiskit.execute(a		,						a		,						shots=1000	)

			return job.result().get_counts(a	)


if __name__ == "__main__":
							print(F'''Total sum count for state is: {quantum_full_adder(1, 1, 1)}''')

import os
from argparse import ArgumentParser
from typing import List

import torch.utils.data

from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node


__lowerCAmelCase					   =       4
__lowerCAmelCase					   =       3





class     lowerCamelCase      (       __lowerCamelCase					):
	pass



def    a      ( a	)     ->Union[str, Any]:




			'''simple docstring'''


			for shard in shards:
						for i in range(a	):
									yield {"i": i, "shard": shard}


def    a      ( )     ->List[str]:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= int(os.environ['''RANK''']	)
			SCREAMING_SNAKE_CASE     						= int(os.environ['''WORLD_SIZE''']	)

			SCREAMING_SNAKE_CASE     						= ArgumentParser()
			parser.add_argument('''--streaming'''		,						type=a	)
			parser.add_argument('''--local_rank'''		,						type=a	)
			parser.add_argument('''--num_workers'''		,						type=a		,						default=0	)
			SCREAMING_SNAKE_CASE     						= parser.parse_args()
			SCREAMING_SNAKE_CASE     						= args.streaming
			SCREAMING_SNAKE_CASE     						= args.num_workers

			SCREAMING_SNAKE_CASE     						= {'''shards''': [F"""shard_{shard_idx}""" for shard_idx in range(a	)]}
			SCREAMING_SNAKE_CASE     						= IterableDataset.from_generator(a		,						gen_kwargs=a	)
			if not streaming:
						SCREAMING_SNAKE_CASE     						= Dataset.from_list(list(a	)	)

			SCREAMING_SNAKE_CASE     						= split_dataset_by_node(a		,						rank=a		,						world_size=a	)
			SCREAMING_SNAKE_CASE     						= torch.utils.data.DataLoader(a		,						num_workers=a	)

			SCREAMING_SNAKE_CASE     						= NUM_SHARDS * NUM_ITEMS_PER_SHARD
			SCREAMING_SNAKE_CASE     						= full_size // world_size
			expected_local_size += int(rank < (full_size % world_size)	)

			SCREAMING_SNAKE_CASE     						= sum(1 for _ in dataloader	)
			if local_size != expected_local_size:
						raise FailedTestError(F"""local_size {local_size} != expected_local_size {expected_local_size}"""	)


if __name__ == "__main__":
							main()