


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


_snake_case  :	Optional[int]			      =       logging.get_logger(__name__)

_snake_case  :	Optional[int]			      =       {
    "s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}

class        a	(_lowerCAmelCase   ):




							"""simple docstring"""


							__UpperCAmelCase					:							Union[str, Any]  						=						"open-llama"

							def __init__(							self :						Union[str, Any]					,			lowerCamelCase :						Dict=100000					,			lowerCamelCase :						List[Any]=4096					,			lowerCamelCase :						Any=11008					,			lowerCamelCase :						Optional[int]=32					,			lowerCamelCase :						Tuple=32					,			lowerCamelCase :						str="silu"					,			lowerCamelCase :						Tuple=2048					,			lowerCamelCase :						Tuple=0.02					,			lowerCamelCase :						Optional[Any]=1E-6					,			lowerCamelCase :						Union[str, Any]=True					,			lowerCamelCase :						str=0					,			lowerCamelCase :						Dict=1					,			lowerCamelCase :						int=2					,			lowerCamelCase :						str=False					,			lowerCamelCase :						Union[str, Any]=True					,			lowerCamelCase :						List[Any]=0.1					,			lowerCamelCase :						Union[str, Any]=0.1					,			lowerCamelCase :						Union[str, Any]=True					,			lowerCamelCase :						Tuple=True					,			lowerCamelCase :						List[str]=None					,			**lowerCamelCase :						Union[str, Any]					,			)			->					Union[str, Any]:
														__snake_case	:    Optional[Any]											=     vocab_size
														__snake_case	:    str											=     max_position_embeddings
														__snake_case	:    Union[str, Any]											=     hidden_size
														__snake_case	:    Union[str, Any]											=     intermediate_size
														__snake_case	:    Dict											=     num_hidden_layers
														__snake_case	:    Optional[int]											=     num_attention_heads
														__snake_case	:    Dict											=     hidden_act
														__snake_case	:    List[Any]											=     initializer_range
														__snake_case	:    int											=     rms_norm_eps
														__snake_case	:    Union[str, Any]											=     use_cache
														__snake_case	:    List[str]											=     kwargs.pop(
														    "use_memorry_efficient_attention"					,			lowerCamelCase       )
														__snake_case	:    Optional[int]											=     hidden_dropout_prob
														__snake_case	:    Union[str, Any]											=     attention_dropout_prob
														__snake_case	:    str											=     use_stable_embedding
														__snake_case	:    Any											=     shared_input_output_embedding
														__snake_case	:    Dict											=     rope_scaling
														self._rope_scaling_validation()

														super().__init__(
														    pad_token_id=lowerCamelCase					,			bos_token_id=lowerCamelCase					,			eos_token_id=lowerCamelCase					,			tie_word_embeddings=lowerCamelCase					,			**lowerCamelCase					,			)






							def 					__snake_case      (							self :						Any       )			->					Optional[Any]:
														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}'       )
														__snake_case	:    Optional[int]											=     self.rope_scaling.get("type"					,			lowerCamelCase       )
														__snake_case	:    Dict											=     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}'       )





from __future__ import annotations

_snake_case  :	Union[str, Any]			      =       {
    "A": ["B", "C", "E"],
    "B": ["A", "D", "E"],
    "C": ["A", "F", "G"],
    "D": ["B"],
    "E": ["A", "B", "D"],
    "F": ["C"],
    "G": ["C"],
}

class        a	:




							"""simple docstring"""


							def __init__(							self :						Tuple					,			lowerCamelCase :						dict[str, list[str]]					,			lowerCamelCase :						str       )			->					None:
														__snake_case	:    Tuple											=     graph
														# mapping node to its parent in resulting breadth first tree
														__snake_case	:    dict[str, str | None]											=     {}
														__snake_case	:    Dict											=     source_vertex

							def 					__snake_case      (							self :						Optional[int]       )			->					None:
														__snake_case	:    Dict											=     {self.source_vertex}
														__snake_case	:    List[str]											=     None
														__snake_case	:    Optional[Any]											=     [self.source_vertex]  # first in first out queue

														while queue:
																					__snake_case	:    List[Any]											=     queue.pop(0       )
																					for adjacent_vertex in self.graph[vertex]:
																												if adjacent_vertex not in visited:
																																			visited.add(lowerCamelCase       )
																																			__snake_case	:    Any											=     vertex
																																			queue.append(lowerCamelCase       )






							def 					__snake_case      (							self :						Optional[Any]					,			lowerCamelCase :						str       )			->					str:
														if target_vertex == self.source_vertex:
																					return self.source_vertex

														__snake_case	:    Optional[Any]											=     self.parent.get(lowerCamelCase       )
														if target_vertex_parent is None:
																					__snake_case	:    Optional[Any]											=     (
																					    F'No path from vertex: {self.source_vertex} to vertex: {target_vertex}'
																					)
																					raise ValueError(lowerCamelCase       )

														return self.shortest_path(lowerCamelCase       ) + F'->{target_vertex}'


if __name__ == "__main__":
			_snake_case  :	Optional[Any]			      =       Graph(graph, "G")
			g.breath_first_search()
			print(g.shortest_path("D"))
			print(g.shortest_path("G"))
			print(g.shortest_path("Foo"))

