
"""simple docstring"""






import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List

import torch
from tqdm import tqdm

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, parse_numeric_n_bool_cl_kwargs, use_task_specific_params


__UpperCAmelCase 					=    getLogger(__name__)


__UpperCAmelCase 					=    'cuda' if torch.cuda.is_available() else 'cpu'






def 		_snake_case			(      lowercase__						:    List[str] ,	lowercase__						:    str ,	lowercase__						:    str ,	lowercase__						:    int = 8 ,	lowercase__						:    str = DEFAULT_DEVICE ,	lowercase__						:    Any=False ,	lowercase__						:    List[Any]="summarization" ,	lowercase__						:    Optional[int]=None ,	**lowercase__						:    str ,	)    ->							Dict:


			'''simple docstring'''





			lowerCAmelCase_       :str     	=    Path(lowercase__						).open("""w""" ,	encoding="""utf-8"""						)
			lowerCAmelCase_       :Optional[Any]     	=    str(lowercase__						)
			lowerCAmelCase_       :List[Any]     	=    AutoModelForSeqaSeqLM.from_pretrained(lowercase__						).to(lowercase__						)
			if fpaa:
						lowerCAmelCase_       :Optional[Any]     	=    model.half()

			lowerCAmelCase_       :int     	=    AutoTokenizer.from_pretrained(lowercase__						)
			logger.info(f"""Inferred tokenizer type: {tokenizer.__class__}"""						)  # if this is wrong, check config.model_type.

			lowerCAmelCase_       :Optional[int]     	=    time.time()
			# update config with task specific params
			use_task_specific_params(lowercase__ ,	lowercase__						)
			if prefix is None:
						lowerCAmelCase_       :Tuple     	=    prefix or getattr(model.config ,	"""prefix""" ,	""""""						) or """"""
			for examples_chunk in tqdm(list(chunks(lowercase__ ,	lowercase__						)						)						):
						lowerCAmelCase_       :List[Any]     	=    [prefix + text for text in examples_chunk]
						lowerCAmelCase_       :List[Any]     	=    tokenizer(lowercase__ ,	return_tensors="""pt""" ,	truncation=lowercase__ ,	padding="""longest"""						).to(lowercase__						)
						lowerCAmelCase_       :List[Any]     	=    model.generate(
						    input_ids=batch.input_ids ,	attention_mask=batch.attention_mask ,	**lowercase__ ,	)
						lowerCAmelCase_       :List[str]     	=    tokenizer.batch_decode(lowercase__ ,	skip_special_tokens=lowercase__ ,	clean_up_tokenization_spaces=lowercase__						)
						for hypothesis in dec:
									fout.write(hypothesis + """\n"""						)
									fout.flush()
			fout.close()
			lowerCAmelCase_       :Optional[Any]     	=    int(time.time() - start_time						)  # seconds
			lowerCAmelCase_       :Optional[int]     	=    len(lowercase__						)
			return {"n_obs": n_obs, "runtime": runtime, "seconds_per_sample": round(runtime / n_obs ,	4						)}






def 		_snake_case			(      )    ->							int:


			'''simple docstring'''





			return datetime.datetime.now().strftime("""%Y-%m-%d %H:%M:%S"""						)






def 		_snake_case			(      lowercase__						:    List[str]=True						)    ->							int:


			'''simple docstring'''





			lowerCAmelCase_       :int     	=    argparse.ArgumentParser()
			parser.add_argument("""model_name""" ,	type=lowercase__ ,	help="""like facebook/bart-large-cnn,t5-base, etc."""						)
			parser.add_argument("""input_path""" ,	type=lowercase__ ,	help="""like cnn_dm/test.source"""						)
			parser.add_argument("""save_path""" ,	type=lowercase__ ,	help="""where to save summaries"""						)
			parser.add_argument("""--reference_path""" ,	type=lowercase__ ,	required=lowercase__ ,	help="""like cnn_dm/test.target"""						)
			parser.add_argument("""--score_path""" ,	type=lowercase__ ,	required=lowercase__ ,	default="""metrics.json""" ,	help="""where to save metrics"""						)
			parser.add_argument("""--device""" ,	type=lowercase__ ,	required=lowercase__ ,	default=lowercase__ ,	help="""cuda, cuda:1, cpu etc."""						)
			parser.add_argument(
			    """--prefix""" ,	type=lowercase__ ,	required=lowercase__ ,	default=lowercase__ ,	help="""will be added to the begininng of src examples"""						)
			parser.add_argument("""--task""" ,	type=lowercase__ ,	default="""summarization""" ,	help="""used for task_specific_params + metrics"""						)
			parser.add_argument("""--bs""" ,	type=lowercase__ ,	default=8 ,	required=lowercase__ ,	help="""batch size"""						)
			parser.add_argument(
			    """--n_obs""" ,	type=lowercase__ ,	default=-1 ,	required=lowercase__ ,	help="""How many observations. Defaults to all."""						)
			parser.add_argument("""--fp16""" ,	action="""store_true"""						)
			parser.add_argument("""--dump-args""" ,	action="""store_true""" ,	help="""print the custom hparams with the results"""						)
			parser.add_argument(
			    """--info""" ,	nargs="""?""" ,	type=lowercase__ ,	const=datetime_now() ,	help=(
			        """use in conjunction w/ --dump-args to print with the results whatever other info you'd like, e.g."""
			        """ lang=en-ru. If no value is passed, the current datetime string will be used."""
			    ) ,	)
			# Unspecified args like --num_beams=2 --decoder_start_token_id=4 are passed to model.generate
			lowerCAmelCase_	,			lowerCAmelCase_       :int     	=    parser.parse_known_args()
			lowerCAmelCase_       :str     	=    parse_numeric_n_bool_cl_kwargs(lowercase__						)
			if parsed_args and verbose:
						print(f"""parsed the following generate kwargs: {parsed_args}"""						)
			with open(args.input_path						) as f:
						lowerCAmelCase_       :str     	=    [""" """ + x.rstrip() if """t5""" in args.model_name else x.rstrip() for x in f.readlines()]
			if args.n_obs > 0:
						lowerCAmelCase_       :Any     	=    examples[: args.n_obs]
			Path(args.save_path						).parent.mkdir(exist_ok=lowercase__						)
			if args.reference_path is None and Path(args.score_path						).exists():
						warnings.warn(f"""score_path {args.score_path} will be overwritten unless you type ctrl-c."""						)
			lowerCAmelCase_       :str     	=    generate_summaries_or_translations(
			    lowercase__ ,	args.save_path ,	args.model_name ,	batch_size=args.bs ,	device=args.device ,	fpaa=args.fpaa ,	task=args.task ,	prefix=args.prefix ,	**lowercase__ ,	)

			if args.reference_path is None:
						return {}

			# Compute scores
			lowerCAmelCase_       :Tuple     	=    calculate_bleu if """translation""" in args.task else calculate_rouge
			lowerCAmelCase_       :Any     	=    [x.rstrip() for x in open(args.save_path						).readlines()]
			lowerCAmelCase_       :Optional[int]     	=    [x.rstrip() for x in open(args.reference_path						).readlines()][: len(lowercase__						)]
			lowerCAmelCase_       :dict     	=    score_fn(lowercase__ ,	lowercase__						)
			scores.update(lowercase__						)

			if args.dump_args:
						scores.update(lowercase__						)
			if args.info:
						lowerCAmelCase_       :List[Any]     	=    args.info

			if verbose:
						print(lowercase__						)

			if args.score_path is not None:
						json.dump(lowercase__ ,	open(args.score_path ,	"""w"""						)						)

			return scores


if __name__ == "__main__":
				# Usage for MT:
				# python run_eval.py MODEL_NAME $DATA_DIR/test.source $save_dir/test_translations.txt --reference_path $DATA_DIR/test.target --score_path $save_dir/test_bleu.json  --task translation $@
				run_generate(verbose=True)








"""simple docstring"""






from __future__ import annotations

from typing import Generic, TypeVar

__UpperCAmelCase 					=    TypeVar('T')




class      _SCREAMING_SNAKE_CASE   (     A__				):
			pass




class      _SCREAMING_SNAKE_CASE   (     A__				):
			pass




class      _SCREAMING_SNAKE_CASE   (     Generic[T]				):






			def __init__(   self			,  __A = 10			)     ->	Optional[int]:
						lowerCAmelCase_       :list[T]     	=    []
						lowerCAmelCase_       :int     	=    limit






			def __bool__(   self			)     ->	bool:
						return bool(self.stack			)






			def __str__(   self			)     ->	str:
						return str(self.stack			)






			def 					__lowerCAmelCase					(   self			,  __A			)     ->	None:
						if len(self.stack			) >= self.limit:
									raise StackOverflowError
						self.stack.append(__A			)






			def 					__lowerCAmelCase					(   self			)     ->	T:
						if not self.stack:
									raise StackUnderflowError
						return self.stack.pop()






			def 					__lowerCAmelCase					(   self			)     ->	T:
						if not self.stack:
									raise StackUnderflowError
						return self.stack[-1]






			def 					__lowerCAmelCase					(   self			)     ->	bool:
						return not bool(self.stack			)






			def 					__lowerCAmelCase					(   self			)     ->	bool:
						return self.size() == self.limit






			def 					__lowerCAmelCase					(   self			)     ->	int:
						return len(self.stack			)






			def __contains__(   self			,  __A			)     ->	bool:
						return item in self.stack






def 		_snake_case			(      )    ->							None:


			'''simple docstring'''





			lowerCAmelCase_       :Stack[int]     	=    Stack(1_0						)
			assert bool(lowercase__						) is False
			assert stack.is_empty() is True
			assert stack.is_full() is False
			assert str(lowercase__						) == "[]"

			try:
						lowerCAmelCase_       :Optional[Any]     	=    stack.pop()
						raise AssertionError  # This should not happen
			except StackUnderflowError:
						assert True  # This should happen

			try:
						lowerCAmelCase_       :Optional[int]     	=    stack.peek()
						raise AssertionError  # This should not happen
			except StackUnderflowError:
						assert True  # This should happen

			for i in range(1_0						):
						assert stack.size() == i
						stack.push(lowercase__						)

			assert bool(lowercase__						)
			assert not stack.is_empty()
			assert stack.is_full()
			assert str(lowercase__						) == str(list(range(1_0						)						)						)
			assert stack.pop() == 9
			assert stack.peek() == 8

			stack.push(1_0_0						)
			assert str(lowercase__						) == str([0, 1, 2, 3, 4, 5, 6, 7, 8, 1_0_0]						)

			try:
						stack.push(2_0_0						)
						raise AssertionError  # This should not happen
			except StackOverflowError:
						assert True  # This should happen

			assert not stack.is_empty()
			assert stack.size() == 1_0

			assert 5 in stack
			assert 5_5 not in stack


if __name__ == "__main__":
				test_stack()






