


'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCAmelCase					       =							logging.get_logger(__name__)

__UpperCAmelCase					       =							{
    '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     Any					=   "gpt_neox"







							def __init__(	self      ,					lowerCamelCase_=5_04_32      ,					lowerCamelCase_=61_44      ,					lowerCamelCase_=44      ,					lowerCamelCase_=64      ,					lowerCamelCase_=2_45_76      ,					lowerCamelCase_="gelu"      ,					lowerCamelCase_=0.25      ,					lowerCamelCase_=1_00_00      ,					lowerCamelCase_=0.0      ,					lowerCamelCase_=0.0      ,					lowerCamelCase_=0.1      ,					lowerCamelCase_=20_48      ,					lowerCamelCase_=0.02      ,					lowerCamelCase_=1e-5      ,					lowerCamelCase_=True      ,					lowerCamelCase_=0      ,					lowerCamelCase_=2      ,					lowerCamelCase_=False      ,					lowerCamelCase_=True      ,					lowerCamelCase_=None      ,					**lowerCamelCase_      ,					) ->							Dict:
														super().__init__(bos_token_id=lowerCamelCase_      ,					eos_token_id=lowerCamelCase_      ,					**lowerCamelCase_     )
														lowerCAmelCase__      =			vocab_size
														lowerCAmelCase__      =			max_position_embeddings
														lowerCAmelCase__      =			hidden_size
														lowerCAmelCase__      =			num_hidden_layers
														lowerCAmelCase__      =			num_attention_heads
														lowerCAmelCase__      =			intermediate_size
														lowerCAmelCase__      =			hidden_act
														lowerCAmelCase__      =			rotary_pct
														lowerCAmelCase__      =			rotary_emb_base
														lowerCAmelCase__      =			attention_dropout
														lowerCAmelCase__      =			hidden_dropout
														lowerCAmelCase__      =			classifier_dropout
														lowerCAmelCase__      =			initializer_range
														lowerCAmelCase__      =			layer_norm_eps
														lowerCAmelCase__      =			use_cache
														lowerCAmelCase__      =			tie_word_embeddings
														lowerCAmelCase__      =			use_parallel_residual
														lowerCAmelCase__      =			rope_scaling
														self._rope_scaling_validation()

														if self.hidden_size % self.num_attention_heads != 0:
																					raise ValueError(
																					    '''The hidden size is not divisble by the number of attention heads! Make sure to update them!'''     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Optional[int]:
														if self.rope_scaling is None:
																					return

														if not isinstance(self.rope_scaling      ,					lowerCamelCase_     ) or len(self.rope_scaling     ) != 2:
																					raise ValueError(
																					    '''`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, '''
																					    F"""got {self.rope_scaling}"""     )
														lowerCAmelCase__      =			self.rope_scaling.get('''type'''      ,					lowerCamelCase_     )
														lowerCAmelCase__      =			self.rope_scaling.get('''factor'''      ,					lowerCamelCase_     )
														if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
																					raise ValueError(
																					    F"""`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"""     )
														if rope_scaling_factor is None or not isinstance(lowerCamelCase_      ,					lowerCamelCase_     ) or rope_scaling_factor <= 1.0:
																					raise ValueError(F"""`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"""     )



'''simple docstring'''






import numpy as np
import qiskit


def       _snake_case     (  A = 8				,					A = None )		->					str:
							lowerCAmelCase__      =			np.random.default_rng(seed=A )

							# Roughly 25% of the qubits will contribute to the key.
							# So we take more than we need.
							lowerCAmelCase__      =			6 * key_len
							# Measurement basis for Alice's qubits.
							lowerCAmelCase__      =			rng.integers(2				,					size=A )
							# The set of states Alice will prepare.
							lowerCAmelCase__      =			rng.integers(2				,					size=A )
							# Measurement basis for Bob's qubits.
							lowerCAmelCase__      =			rng.integers(2				,					size=A )

							# Quantum Circuit to simulate BB84
							lowerCAmelCase__      =			qiskit.QuantumCircuit(A				,					name='''BB84''' )

							# Alice prepares her qubits according to rules above.
							for index, _ in enumerate(A ):
														if alice_state[index] == 1:
																					bbaa_circ.x(A )
														if alice_basis[index] == 1:
																					bbaa_circ.h(A )
							bbaa_circ.barrier()

							# Bob measures the received qubits according to rules above.
							for index, _ in enumerate(A ):
														if bob_basis[index] == 1:
																					bbaa_circ.h(A )

							bbaa_circ.barrier()
							bbaa_circ.measure_all()

							# Simulate the quantum circuit.
							lowerCAmelCase__      =			qiskit.Aer.get_backend('''aer_simulator''' )
							# We only need to run one shot because the key is unique.
							# Multiple shots will produce the same key.
							lowerCAmelCase__      =			qiskit.execute(A				,					A				,					shots=1				,					seed_simulator=A )
							# Returns the result of measurement.
							lowerCAmelCase__      =			job.result().get_counts(A ).most_frequent()

							# Extracting the generated key from the simulation results.
							# Only keep measurement results where Alice and Bob chose the same basis.
							lowerCAmelCase__      =			''''''.join(
							    [
							        result_bit
							        for alice_basis_bit, bob_basis_bit, result_bit in zip(
							            A				,					A				,					A )
							        if alice_basis_bit == bob_basis_bit
							    ] )

							# Get final key. Pad with 0 if too short, otherwise truncate.
							lowerCAmelCase__      =			gen_key[:key_len] if len(A ) >= key_len else gen_key.ljust(A				,					'''0''' )
							return key


if __name__ == "__main__":
		print(f"""The generated key is : {bbaa(8, seed=0)}""")
		from doctest import testmod

		testmod()