



'''simple docstring'''

import fire
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save



def 	__lowerCamelCase	( lowerCAmelCase_		,     lowerCAmelCase_		,     lowerCAmelCase_=1024		,     lowerCAmelCase_=1024		,     lowerCAmelCase_=False		,     **lowerCAmelCase_    )     -> Any:
		_a	: List[Any]								=				AutoTokenizer.from_pretrained(lowerCAmelCase_    )
		_a	: List[Any]								=				SeqaSeqDataset(lowerCAmelCase_		,     lowerCAmelCase_		,     lowerCAmelCase_		,     lowerCAmelCase_		,     type_path='train'		,     **lowerCAmelCase_    )
		_a	: Union[str, Any]								=				tok.pad_token_id

		def get_lens(lowerCAmelCase_    ):
				_a	: Any								=				tqdm(
				    DataLoader(lowerCAmelCase_		,     batch_size=512		,     num_workers=8		,     shuffle=lowerCAmelCase_		,     collate_fn=ds.collate_fn    )		,     desc=str(ds.len_file    )		,     )
				_a	: int								=				[]
				for batch in dl:
						_a	: List[Any]								=				batch['input_ids'].ne(lowerCAmelCase_    ).sum(1    ).tolist()
						_a	: Any								=				batch['labels'].ne(lowerCAmelCase_    ).sum(1    ).tolist()
						if consider_target:
								for src, tgt in zip(lowerCAmelCase_		,     lowerCAmelCase_    ):
										max_lens.append(max(lowerCAmelCase_		,     lowerCAmelCase_    )    )
						else:
								max_lens.extend(lowerCAmelCase_    )
				return max_lens

		_a	: Dict								=				get_lens(lowerCAmelCase_    )
		_a	: List[Any]								=				SeqaSeqDataset(lowerCAmelCase_		,     lowerCAmelCase_		,     lowerCAmelCase_		,     lowerCAmelCase_		,     type_path='val'		,     **lowerCAmelCase_    )
		_a	: Tuple								=				get_lens(lowerCAmelCase_    )
		pickle_save(lowerCAmelCase_		,     train_ds.len_file    )
		pickle_save(lowerCAmelCase_		,     val_ds.len_file    )


if __name__ == "__main__":
							fire.Fire(save_len_file)









'''simple docstring'''

# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

__lowerCAmelCase		     =  TypeVar('''T''')

class       __magic_name__		(       Generic[T]  ):







							def __init__(				self   :			int      ,_UpperCAmelCase   :			bool = True						):
									_a	: dict[T, list[T]]								=				{}  # dictionary of lists
									_a	: Tuple								=				directed







							def 				__lowercase     (				self   :			Union[str, Any]      ,_UpperCAmelCase   :			T      ,_UpperCAmelCase   :			T						):

									if not self.directed:  # For undirected graphs
											# if both source vertex and destination vertex are both present in the
											# adjacency list, add destination vertex to source vertex list of adjacent
											# vertices and add source vertex to destination vertex list of adjacent
											# vertices.
											if source_vertex in self.adj_list and destination_vertex in self.adj_list:
													self.adj_list[source_vertex].append(_UpperCAmelCase						)
													self.adj_list[destination_vertex].append(_UpperCAmelCase						)
											# if only source vertex is present in adjacency list, add destination vertex
											# to source vertex list of adjacent vertices, then create a new vertex with
											# destination vertex as key and assign a list containing the source vertex
											# as it's first adjacent vertex.
											elif source_vertex in self.adj_list:
													self.adj_list[source_vertex].append(_UpperCAmelCase						)
													_a	: Optional[Any]								=				[source_vertex]
											# if only destination vertex is present in adjacency list, add source vertex
											# to destination vertex list of adjacent vertices, then create a new vertex
											# with source vertex as key and assign a list containing the source vertex
											# as it's first adjacent vertex.
											elif destination_vertex in self.adj_list:
													self.adj_list[destination_vertex].append(_UpperCAmelCase						)
													_a	: Union[str, Any]								=				[destination_vertex]
											# if both source vertex and destination vertex are not present in adjacency
											# list, create a new vertex with source vertex as key and assign a list
											# containing the destination vertex as it's first adjacent vertex also
											# create a new vertex with destination vertex as key and assign a list
											# containing the source vertex as it's first adjacent vertex.
											else:
													_a	: Union[str, Any]								=				[destination_vertex]
													_a	: Optional[int]								=				[source_vertex]
									else:  # For directed graphs
											# if both source vertex and destination vertex are present in adjacency
											# list, add destination vertex to source vertex list of adjacent vertices.
											if source_vertex in self.adj_list and destination_vertex in self.adj_list:
													self.adj_list[source_vertex].append(_UpperCAmelCase						)
											# if only source vertex is present in adjacency list, add destination
											# vertex to source vertex list of adjacent vertices and create a new vertex
											# with destination vertex as key, which has no adjacent vertex
											elif source_vertex in self.adj_list:
													self.adj_list[source_vertex].append(_UpperCAmelCase						)
													_a	: int								=				[]
											# if only destination vertex is present in adjacency list, create a new
											# vertex with source vertex as key and assign a list containing destination
											# vertex as first adjacent vertex
											elif destination_vertex in self.adj_list:
													_a	: Tuple								=				[destination_vertex]
											# if both source vertex and destination vertex are not present in adjacency
											# list, create a new vertex with source vertex as key and a list containing
											# destination vertex as it's first adjacent vertex. Then create a new vertex
											# with destination vertex as key, which has no adjacent vertex
											else:
													_a	: Tuple								=				[destination_vertex]
													_a	: str								=				[]

									return self







							def __repr__(				self   :			int						):
									return pformat(self.adj_list						)




