



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase__     = {
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__     = ["LlamaTokenizer"]

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__     = ["LlamaTokenizerFast"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__     = [
							    "LlamaForCausalLM",
							    "LlamaModel",
							    "LlamaPreTrainedModel",
							    "LlamaForSequenceClassification",
							]


if TYPE_CHECKING:
							from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_llama import LlamaTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_llama_fast import LlamaTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
							import sys

							UpperCAmelCase__     = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





import qiskit





def 							A			(  _UpperCAmelCase       :     int							,     _UpperCAmelCase       :     int					)       ->				qiskit.result.counts.Counts:







			'''simple docstring'''
			_UpperCAmelCase	 =     qiskit.Aer.get_backend('aer_simulator'					)

			# Create a Quantum Circuit acting on the q register
			_UpperCAmelCase	 =     qiskit.QuantumCircuit(_UpperCAmelCase							,     _UpperCAmelCase					)

			# Apply X (NOT) Gate to Qubits 0 & 1
			circuit.x(0					)
			circuit.x(1					)

			# Map the quantum measurement to the classical bits
			circuit.measure([0, 1]							,     [0, 1]					)

			# Execute the circuit on the qasm simulator
			_UpperCAmelCase	 =     qiskit.execute(_UpperCAmelCase							,     _UpperCAmelCase							,     shots=1_000					)

			# Return the histogram data of the results of the experiment.
			return job.result().get_counts(_UpperCAmelCase					)


if __name__ == "__main__":
							UpperCAmelCase__     = single_qubit_measure(2, 2)
							print(f"""Total count for various states are: {counts}""")
