



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
UpperCAmelCase :				Optional[int]							={
    """translation""": ["""bleu"""],
    """summarization""": ROUGE_KEYS,
}



def  _lowerCAmelCase     (_lowerCAmelCase):
					UpperCamelCase_			= search.split()
					UpperCamelCase_			= dict((g.split("=") for g in groups))
					UpperCamelCase_			= list(entries.keys())
					UpperCamelCase_			= [[f"""--{k} {v}""" for v in vs.split(":")] for k, vs in entries.items()]
					UpperCamelCase_			= [list(_lowerCAmelCase) for x in itertools.product(*_lowerCAmelCase)]
					return matrix, entry_names



def  _lowerCAmelCase     ():
					UpperCamelCase_			= sys.argv[0]

					UpperCamelCase_			= 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=_lowerCAmelCase ,						required=_lowerCAmelCase ,						help="param space to search, e.g. \"num_beams=5:10 length_penalty=0.8:1.0:1.2\"" ,						)
					parser.add_argument(
					    "--bs" ,						type=_lowerCAmelCase ,						default=8 ,						required=_lowerCAmelCase ,						help="initial batch size (may get reduced if it's too big)")
					parser.add_argument("--task" ,						type=_lowerCAmelCase ,						help="used for task_specific_params + metrics")
					parser.add_argument(
					    "--info" ,						nargs="?" ,						type=_lowerCAmelCase ,						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."
					    ) ,						)
					UpperCamelCase_	,     UpperCamelCase_			= parser.parse_known_args()
					# we share some of the args
					args_main.extend(["--task", args.task])
					UpperCamelCase_			= [prog] + args_main

					# to support variations like translation_en_to_de"
					UpperCamelCase_			= "translation" if "translation" in args.task else "summarization"

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

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

										UpperCamelCase_			= run_generate(verbose=_lowerCAmelCase)
										# make sure scores are first in the table
										UpperCamelCase_			= OrderedDict()
										for score in task_score_names[task]:
															UpperCamelCase_			= scores[score]
										result.update(_lowerCAmelCase)
										results.append(_lowerCAmelCase)

										# find widest entries
										for k, v in result.items():
															UpperCamelCase_			= len(str(_lowerCAmelCase))
															if l > col_widths[k]:
																				UpperCamelCase_			= l

					UpperCamelCase_			= sorted(_lowerCAmelCase ,						key=operator.itemgetter(*task_score_names[task]) ,						reverse=_lowerCAmelCase)
					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]))

					UpperCamelCase_			= results_sorted[0]
					for score in task_score_names[task]:
										del best[score]
					UpperCamelCase_			= [f"""--{k} {v}""" for k, v in best.items()]
					UpperCamelCase_			= ["--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()





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


UpperCAmelCase :				Union[str, Any]							=logging.get_logger(__name__)


class    _lowercase (a_   ):
				'''simple docstring'''







				lowercase__     =    """speech-encoder-decoder"""
				lowercase__     =    True

				def __init__(			self  ,			**snake_case__     ):

									'''simple docstring'''


									super().__init__(**snake_case__     )
									if "encoder" not in kwargs or "decoder" not in kwargs:
														raise ValueError(
														    F"""A configuraton of type {self.model_type} cannot be instantiated because not both `encoder` and"""
														    F""" `decoder` sub-configurations are passed, but only {kwargs}"""     )

									UpperCamelCase_			= kwargs.pop("encoder"     )
									UpperCamelCase_			= encoder_config.pop("model_type"     )
									UpperCamelCase_			= kwargs.pop("decoder"     )
									UpperCamelCase_			= decoder_config.pop("model_type"     )

									UpperCamelCase_			= AutoConfig.for_model(snake_case__  ,			**snake_case__     )
									UpperCamelCase_			= AutoConfig.for_model(snake_case__  ,			**snake_case__     )
									UpperCamelCase_			= True

				@classmethod
				def    _lowerCamelCase       (			cls  ,			snake_case__  ,			snake_case__  ,			**snake_case__     ):

									'''simple docstring'''


									logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"     )
									UpperCamelCase_			= True
									UpperCamelCase_			= True

									return cls(encoder=encoder_config.to_dict()  ,			decoder=decoder_config.to_dict()  ,			**snake_case__     )

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= copy.deepcopy(self.__dict__     )
									UpperCamelCase_			= self.encoder.to_dict()
									UpperCamelCase_			= self.decoder.to_dict()
									UpperCamelCase_			= self.__class__.model_type
									return output
