


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[Any]          =				{
    'translation': ['bleu'],
    'summarization': ROUGE_KEYS,
}
def   snake_case_    (			__lowercase							):
   UpperCAmelCase_				:   Tuple							= search.split()
   UpperCAmelCase_				:   List[str]							= dict((g.split('''='''							) for g in groups)							)
   UpperCAmelCase_				:   Tuple							= list(entries.keys()							)
   UpperCAmelCase_				:   Any							= [[F'''--{k} {v}''' for v in vs.split(''':'''							)] for k, vs in entries.items()]
   UpperCAmelCase_				:   Tuple							= [list(__lowercase							) for x in itertools.product(*__lowercase							)]
   return matrix, entry_names
def   snake_case_    (			):
   UpperCAmelCase_				:   Optional[Any]							= sys.argv[0]

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

   # to support variations like translation_en_to_de"
   UpperCAmelCase_				:   List[Any]							= '''translation''' if '''translation''' in args.task else '''summarization'''

   UpperCAmelCase_		,   UpperCAmelCase_				:   int							= parse_search_arg(args.search							)
   UpperCAmelCase_				:   List[Any]							= task_score_names[task]  # score cols first
   UpperCAmelCase_				:   Optional[Any]							= {col: len(str(__lowercase							)							) for col in col_names}
   UpperCAmelCase_				:   int							= []
   for r in matrix:
      UpperCAmelCase_				:   Tuple							= dict((x.replace('''--'''      ,							''''''							).split() for x in r)							)
      UpperCAmelCase_				:   List[Any]							= ''' '''.join(__lowercase							).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_				:   Tuple							= run_generate(verbose=__lowercase							)
      # make sure scores are first in the table
      UpperCAmelCase_				:   Any							= OrderedDict()
      for score in task_score_names[task]:
         UpperCAmelCase_				:   Optional[Any]							= scores[score]
      result.update(__lowercase							)
      results.append(__lowercase							)

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

   UpperCAmelCase_				:   List[str]							= sorted(__lowercase      ,							key=operator.itemgetter(*task_score_names[task]							)      ,							reverse=__lowercase							)
   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_				:   Union[str, Any]							= results_sorted[0]
   for score in task_score_names[task]:
      del best[score]
   UpperCAmelCase_				:   Dict							= [F'''--{k} {v}''' for k, v in best.items()]
   UpperCAmelCase_				:   Optional[int]							= ['''--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 unittest

import numpy as np

from transformers import is_tf_available
from transformers.testing_utils import require_tf


if is_tf_available():
       import tensorflow as tf

       from transformers.activations_tf import get_tf_activation





@require_tf
class 			lowerCAmelCase__(     unittest.TestCase    ):






    '''simple docstring'''





    def        _lowerCamelCase			(						self					: Optional[int]						):





       '''simple docstring'''
       UpperCAmelCase_				:   str							= tf.constant([-100, -1.0, -0.1, 0, 0.1, 1.0, 100.0]						)
       UpperCAmelCase_				:   List[Any]							= get_tf_activation('''gelu'''						)
       UpperCAmelCase_				:   Any							= get_tf_activation('''gelu_10'''						)

       UpperCAmelCase_				:   int							= gelu(__snake_case						)
       UpperCAmelCase_				:   Union[str, Any]							= geluaa(__snake_case						)

       UpperCAmelCase_				:   Union[str, Any]							= tf.where(y_gelu_aa < 10.0							, 1.0							, 0.0						)

       self.assertEqual(tf.math.reduce_max(__snake_case						).numpy().item()							, 10.0						)
       self.assertTrue(np.allclose(y_gelu * clipped_mask							, y_gelu_aa * clipped_mask						)						)





    def        _lowerCamelCase			(						self					: Dict						):





       '''simple docstring'''
       get_tf_activation('''gelu'''						)
       get_tf_activation('''gelu_10'''						)
       get_tf_activation('''gelu_fast'''						)
       get_tf_activation('''gelu_new'''						)
       get_tf_activation('''glu'''						)
       get_tf_activation('''mish'''						)
       get_tf_activation('''quick_gelu'''						)
       get_tf_activation('''relu'''						)
       get_tf_activation('''sigmoid'''						)
       get_tf_activation('''silu'''						)
       get_tf_activation('''swish'''						)
       get_tf_activation('''tanh'''						)
       with self.assertRaises(__snake_case						):
          get_tf_activation('''bogus'''						)
       with self.assertRaises(__snake_case						):
          get_tf_activation(__snake_case						)