






'''simple docstring'''







import argparse
import itertools
import operator
import sys
from collections import OrderedDict

from run_eval import datetime_now, run_generate

from utils import ROUGE_KEYS


# A table of supported tasks and the list of scores in the order of importance to be sorted by.
# To add a new task, simply list the score names that `run_eval.run_generate()` returns
_A      :     Optional[int]       	={
    "translation": ["bleu"],
    "summarization": ROUGE_KEYS,
}





def 					SCREAMING_SNAKE_CASE_			(UpperCamelCase ) ->			int:
							lowerCamelCase__   :      int			    =			search.split()
							lowerCamelCase__   :      int			    =			dict((g.split("""=""" ) for g in groups) )
							lowerCamelCase__   :      Optional[int]			    =			list(entries.keys() )
							lowerCamelCase__   :      Union[str, Any]			    =			[[f'''--{k} {v}''' for v in vs.split(""":""" )] for k, vs in entries.items()]
							lowerCamelCase__   :      Dict			    =			[list(UpperCAmelCase__ ) for x in itertools.product(*UpperCAmelCase__ )]
							return matrix, entry_names





def 					SCREAMING_SNAKE_CASE_			() ->			Any:
							lowerCamelCase__   :      Dict			    =			sys.argv[0]

							lowerCamelCase__   :      Optional[Any]			    =			argparse.ArgumentParser(
							    usage=(
							        """\n\nImportant: this script accepts all arguments `run_eval.py` accepts and then a few extra, therefore"""
							        """ refer to `run_eval.py -h` for the complete list."""
							    ) )
							parser.add_argument(
							    """--search"""							,     type=UpperCAmelCase__							,     required=UpperCAmelCase__							,     help="""param space to search, e.g. \"num_beams=5:10 length_penalty=0.8:1.0:1.2\""""							,     )
							parser.add_argument(
							    """--bs"""							,     type=UpperCAmelCase__							,     default=8							,     required=UpperCAmelCase__							,     help="""initial batch size (may get reduced if it\'s too big)""" )
							parser.add_argument("""--task"""							,     type=UpperCAmelCase__							,     help="""used for task_specific_params + metrics""" )
							parser.add_argument(
							    """--info"""							,     nargs="""?"""							,     type=UpperCAmelCase__							,     const=datetime_now()							,     help=(
							        """add custom notes to be printed before the results table. If no value is passed, the current datetime"""
							        """ string will be used."""
							    )							,     )
							lowerCamelCase__   :      List[Any]			    =			parser.parse_known_args()
							# we share some of the args
							args_main.extend(["""--task""", args.task] )
							lowerCamelCase__   :      Tuple			    =			[prog] + args_main

							# to support variations like translation_en_to_de"
							lowerCamelCase__   :      Optional[int]			    =			'translation' if 'translation' in args.task else 'summarization'

							lowerCamelCase__   :      Optional[int]			    =			parse_search_arg(args.search )
							lowerCamelCase__   :      str			    =			task_score_names[task]  # score cols first
							lowerCamelCase__   :      int			    =			{col: len(str(UpperCAmelCase__ ) ) for col in col_names}
							lowerCamelCase__   :      Optional[Any]			    =			[]
							for r in matrix:
														lowerCamelCase__   :      List[str]			    =			dict((x.replace("""--"""							,     """""" ).split() for x in r) )
														lowerCamelCase__   :      Union[str, Any]			    =			' '.join(UpperCAmelCase__ ).split()
														args_exp.extend(["""--bs""", str(args.bs )] )  # in case we need to reduce its size due to CUDA OOM
														lowerCamelCase__   :      Any			    =			args_normal + args_exp

														# XXX: need to trap CUDA OOM and lower args.bs if that happens and retry

														lowerCamelCase__   :      Any			    =			run_generate(verbose=UpperCAmelCase__ )
														# make sure scores are first in the table
														lowerCamelCase__   :      Tuple			    =			OrderedDict()
														for score in task_score_names[task]:
																					lowerCamelCase__   :      Dict			    =			scores[score]
														result.update(UpperCAmelCase__ )
														results.append(UpperCAmelCase__ )

														# find widest entries
														for k, v in result.items():
																					lowerCamelCase__   :      List[str]			    =			len(str(UpperCAmelCase__ ) )
																					if l > col_widths[k]:
																												lowerCamelCase__   :      Optional[Any]			    =			l

							lowerCamelCase__   :      Tuple			    =			sorted(UpperCAmelCase__							,     key=operator.itemgetter(*task_score_names[task] )							,     reverse=UpperCAmelCase__ )
							print(""" | """.join([f'''{col:{col_widths[col]}}''' for col in col_names] ) )
							print(""" | """.join([f'''{'-'*col_widths[col]}''' for col in col_names] ) )
							for row in results_sorted:
														print(""" | """.join([f'''{row[col]:{col_widths[col]}}''' for col in col_names] ) )

							lowerCamelCase__   :      Union[str, Any]			    =			results_sorted[0]
							for score in task_score_names[task]:
														del best[score]
							lowerCamelCase__   :      List[str]			    =			[f'''--{k} {v}''' for k, v in best.items()]
							lowerCamelCase__   :      List[Any]			    =			['--bs', str(args.bs )]
							if args.info:
														print(f'''\nInfo: {args.info}''' )
							print("""\nBest score args:""" )
							print(""" """.join(args_main + best_args + dyn_args ) )

							return results_sorted


if __name__ == "__main__":
			# Usage:
			# [normal-run_eval_search.py cmd plus] \
			# --search="num_beams=1:5:10 length_penalty=0.8:1:1.2 early_stopping=true:false"
			#
			# Example:
			# PYTHONPATH="src:examples/seq2seq" python examples/seq2seq/run_eval_search.py $MODEL_NAME \
			# $DATA_DIR/val.source $SAVE_DIR/test_translations.txt --reference_path $DATA_DIR/val.target \
			# --score_path $SAVE_DIR/test_bleu.json --bs $BS --task translation \
			# --search="num_beams=1:5:10 length_penalty=0.8:1:1.2 early_stopping=true:false"
			run_search()





"""simple docstring"""






import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property


class 	A_       (     unittest.TestCase   ):





  """simple docstring"""

  @cached_property
  def 							lowercase_     (						self						)				->					Optional[Any]:
     return BlenderbotTokenizer.from_pretrained('facebook/blenderbot-3B'						)
  @cached_property
  def 							lowercase_     (						self						)				->					Optional[int]:
     return BlenderbotTokenizerFast.from_pretrained('facebook/blenderbot-3B'						)
  def 							lowercase_     (						self						)				->					Union[str, Any]:
     a   :	List[Any]						=    self.tokenizer_ab
     a   :	int						=    ' I am a small frog.'
     a   :	Any						=    tok([src_text]  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase						)['input_ids']
     a   :	List[str]						=    tok.batch_decode(__UpperCAmelCase  ,					skip_special_tokens=__UpperCAmelCase  ,					clean_up_tokenization_spaces=__UpperCAmelCase						)[0]
     assert src_text == decoded
  def 							lowercase_     (						self						)				->					Optional[Any]:
     a   :	Optional[int]						=    self.rust_tokenizer_ab
     a   :	List[Any]						=    ' I am a small frog.'
     a   :	Union[str, Any]						=    tok([src_text]  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase						)['input_ids']
     a   :	Optional[Any]						=    tok.batch_decode(__UpperCAmelCase  ,					skip_special_tokens=__UpperCAmelCase  ,					clean_up_tokenization_spaces=__UpperCAmelCase						)[0]
     assert src_text == decoded
  def 							lowercase_     (						self						)				->					Tuple:
     assert self.tokenizer_ab.add_prefix_space
     assert self.tokenizer_ab([' Sam', 'Sam']						).input_ids == [[55_02, 2], [55_02, 2]]






  def 							lowercase_     (						self						)				->					Tuple:
     assert self.rust_tokenizer_ab.add_prefix_space
     assert self.rust_tokenizer_ab([' Sam', 'Sam']						).input_ids == [[55_02, 2], [55_02, 2]]





