
"""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__		(			__snake_case,     __snake_case,     __snake_case=10_24,     __snake_case=10_24,     __snake_case=False,     **__snake_case	)							->		Union[str, Any]:


					"""simple docstring"""





					_UpperCamelCase							 =  AutoTokenizer.from_pretrained(__snake_case	)
					_UpperCamelCase							 =  SeqaSeqDataset(__snake_case,     __snake_case,     __snake_case,     __snake_case,     type_path='''train''',     **__snake_case	)
					_UpperCamelCase							 =  tok.pad_token_id

					def get_lens(__snake_case	):
										_UpperCamelCase							 =  tqdm(
										    DataLoader(__snake_case,     batch_size=5_12,     num_workers=8,     shuffle=__snake_case,     collate_fn=ds.collate_fn	),     desc=str(ds.len_file	),     )
										_UpperCamelCase							 =  []
										for batch in dl:
															_UpperCamelCase							 =  batch['''input_ids'''].ne(__snake_case	).sum(1	).tolist()
															_UpperCamelCase							 =  batch['''labels'''].ne(__snake_case	).sum(1	).tolist()
															if consider_target:
																				for src, tgt in zip(__snake_case,     __snake_case	):
																									max_lens.append(max(__snake_case,     __snake_case	)	)
															else:
																				max_lens.extend(__snake_case	)
										return max_lens

					_UpperCamelCase							 =  get_lens(__snake_case	)
					_UpperCamelCase							 =  SeqaSeqDataset(__snake_case,     __snake_case,     __snake_case,     __snake_case,     type_path='''val''',     **__snake_case	)
					_UpperCamelCase							 =  get_lens(__snake_case	)
					pickle_save(__snake_case,     train_ds.len_file	)
					pickle_save(__snake_case,     val_ds.len_file	)


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








"""simple docstring"""





from collections import defaultdict






class     _UpperCAmelCase:



		def __init__(					self				,		__a				,		__a)       ->       Union[str, Any]:






							'''simple docstring'''
							_UpperCamelCase							 =  total  # total no of tasks (N)

							# DP table will have a dimension of (2^M)*N
							# initially all values are set to -1
							_UpperCamelCase							 =  [
							    [-1 for i in range(total + 1)] for j in range(2 ** len(__a))
							]

							_UpperCamelCase							 =  defaultdict(__a)  # stores the list of persons for each task

							# final_mask is used to check if all persons are included by setting all bits
							# to 1
							_UpperCamelCase							 =  (1 << len(__a)) - 1



		def 						UpperCAmelCase							(					self				,		__a				,		__a)       ->       Dict:






							'''simple docstring'''
							# if mask == self.finalmask all persons are distributed tasks, return 1
							if mask == self.final_mask:
												return 1

							# if not everyone gets the task and no more tasks are available, return 0
							if task_no > self.total_tasks:
												return 0

							# if case already considered
							if self.dp[mask][task_no] != -1:
												return self.dp[mask][task_no]

							# Number of ways when we don't this task in the arrangement
							_UpperCamelCase							 =  self.count_ways_until(__a				,		task_no + 1)

							# now assign the tasks one by one to all possible persons and recursively
							# assign for the remaining tasks.
							if task_no in self.task:
												for p in self.task[task_no]:
																	# if p is already given a task
																	if mask & (1 << p):
																						continue

																	# assign this task to p and change the mask value. And recursively
																	# assign tasks with the new mask value.
																	total_ways_util += self.count_ways_until(mask | (1 << p)				,		task_no + 1)

        # save the value.
							_UpperCamelCase							 =  total_ways_util

							return self.dp[mask][task_no]




		def 						UpperCAmelCase							(					self				,		__a)       ->       int:






							'''simple docstring'''
							# Store the list of persons for each task
							for i in range(len(__a)):
												for j in task_performed[i]:
																	self.task[j].append(__a)

        # call the function to fill the DP table, final answer is stored in dp[0][1]
							return self.count_ways_until(0				,		1)


if __name__ == "__main__":
				_a														=		5  # total no of tasks (the value of N)

				# the list of tasks that can be done by M persons.
				_a														=		[[1, 3, 4], [1, 2, 5], [3, 4]]
				print(
				    AssignmentUsingBitmask(task_performed, total_tasks).count_no_of_ways(
				        task_performed
				    )
				)






