


from ...configuration_utils import PretrainedConfig
from ...utils import logging


_A							     =       logging.get_logger(__name__)

_A							     =       {
    'tau/splinter-base': 'https://huggingface.co/tau/splinter-base/resolve/main/config.json',
    'tau/splinter-base-qass': 'https://huggingface.co/tau/splinter-base-qass/resolve/main/config.json',
    'tau/splinter-large': 'https://huggingface.co/tau/splinter-large/resolve/main/config.json',
    'tau/splinter-large-qass': 'https://huggingface.co/tau/splinter-large-qass/resolve/main/config.json',
    # See all Splinter models at https://huggingface.co/models?filter=splinter
}

class 			lowerCamelCase_					(    _lowercase    ):
							_lowerCamelCase				: List[Any]       =					"""splinter"""





							def __init__(							self			,       _SCREAMING_SNAKE_CASE=3_0522			,       _SCREAMING_SNAKE_CASE=768			,       _SCREAMING_SNAKE_CASE=12			,       _SCREAMING_SNAKE_CASE=12			,       _SCREAMING_SNAKE_CASE=3072			,       _SCREAMING_SNAKE_CASE="gelu"			,       _SCREAMING_SNAKE_CASE=0.1			,       _SCREAMING_SNAKE_CASE=0.1			,       _SCREAMING_SNAKE_CASE=512			,       _SCREAMING_SNAKE_CASE=2			,       _SCREAMING_SNAKE_CASE=0.0_2			,       _SCREAMING_SNAKE_CASE=1E-12			,       _SCREAMING_SNAKE_CASE=True			,       _SCREAMING_SNAKE_CASE=0			,       _SCREAMING_SNAKE_CASE=104			,       **_SCREAMING_SNAKE_CASE			,       ):
								super().__init__(pad_token_id=__snake_case			,       **__snake_case    )

								a_     			=   vocab_size
								a_     			=   max_position_embeddings
								a_     			=   hidden_size
								a_     			=   num_hidden_layers
								a_     			=   num_attention_heads
								a_     			=   intermediate_size
								a_     			=   hidden_act
								a_     			=   hidden_dropout_prob
								a_     			=   attention_probs_dropout_prob
								a_     			=   initializer_range
								a_     			=   type_vocab_size
								a_     			=   layer_norm_eps
								a_     			=   use_cache
								a_     			=   question_token_id


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
lowerCAmelCase__             =		{
    """translation""": ["""bleu"""],
    """summarization""": ROUGE_KEYS,
}






def        lowerCamelCase_  (				UpperCAmelCase_				:  Optional[int]						)    ->					Any:




	'''simple docstring'''




	_UpperCamelCase :		str								=    search.split()
	_UpperCamelCase :		str								=    dict((g.split('='						) for g in groups)						)
	_UpperCamelCase :		List[Any]								=    list(entries.keys()						)
	_UpperCamelCase :		Dict								=    [[F'''--{k} {v}''' for v in vs.split(':'						)] for k, vs in entries.items()]
	_UpperCamelCase :		Dict								=    [list(UpperCAmelCase_						) for x in itertools.product(*UpperCAmelCase_						)]
	return matrix, entry_names






def        lowerCamelCase_  (				)    ->					int:




	'''simple docstring'''




	_UpperCamelCase :		Optional[Any]								=    sys.argv[0]

	_UpperCamelCase :		Tuple								=    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.'
	    )				,							)
	_UpperCamelCase						,		_UpperCamelCase :		str								=    parser.parse_known_args()
	# we share some of the args
	args_main.extend(['--task', args.task]						)
	_UpperCamelCase :		str								=    [prog] + args_main

	# to support variations like translation_en_to_de"
	_UpperCamelCase :		Tuple								=    'translation' if 'translation' in args.task else 'summarization'

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

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

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

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

	_UpperCamelCase :		Optional[int]								=    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]						)						)

	_UpperCamelCase :		Optional[int]								=    results_sorted[0]
	for score in task_score_names[task]:
		del best[score]
	_UpperCamelCase :		str								=    [F'''--{k} {v}''' for k, v in best.items()]
	_UpperCamelCase :		Optional[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()




