
import functools
import operator

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


_A	  =					logging.get_logger(__name__)

_A	  =					{
    '''facebook/hubert-base-ls960''': '''https://huggingface.co/facebook/hubert-base-ls960/resolve/main/config.json''',
    # See all Hubert models at https://huggingface.co/models?filter=hubert
}

class 		lowercase_       (       __SCREAMING_SNAKE_CASE				):
 A__						:				List[Any]         =    """hubert"""

 def __init__(      self     ,	__UpperCamelCase=3_2     ,	__UpperCamelCase=7_6_8     ,	__UpperCamelCase=1_2     ,	__UpperCamelCase=1_2     ,	__UpperCamelCase=3_0_7_2     ,	__UpperCamelCase="gelu"     ,	__UpperCamelCase=0.1     ,	__UpperCamelCase=0.1     ,	__UpperCamelCase=0.1     ,	__UpperCamelCase=True     ,	__UpperCamelCase=0.0     ,	__UpperCamelCase=0.1     ,	__UpperCamelCase=0.1     ,	__UpperCamelCase=0.02     ,	__UpperCamelCase=1e-5     ,	__UpperCamelCase="group"     ,	__UpperCamelCase="gelu"     ,	__UpperCamelCase=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2)     ,	__UpperCamelCase=(5, 2, 2, 2, 2, 2, 2)     ,	__UpperCamelCase=(1_0, 3, 3, 3, 3, 2, 2)     ,	__UpperCamelCase=False     ,	__UpperCamelCase=1_2_8     ,	__UpperCamelCase=1_6     ,	__UpperCamelCase=False     ,	__UpperCamelCase=True     ,	__UpperCamelCase=0.05     ,	__UpperCamelCase=1_0     ,	__UpperCamelCase=2     ,	__UpperCamelCase=0.0     ,	__UpperCamelCase=1_0     ,	__UpperCamelCase=0     ,	__UpperCamelCase="sum"     ,	__UpperCamelCase=False     ,	__UpperCamelCase=False     ,	__UpperCamelCase=2_5_6     ,	__UpperCamelCase=0     ,	__UpperCamelCase=1     ,	__UpperCamelCase=2     ,	**__UpperCamelCase     ,	):




        """simple docstring"""


        super().__init__(**__UpperCamelCase     ,	pad_token_id=__UpperCamelCase     ,	bos_token_id=__UpperCamelCase     ,	eos_token_id=__UpperCamelCase     )
        UpperCamelCase_							       =       hidden_size
        UpperCamelCase_							       =       feat_extract_norm
        UpperCamelCase_							       =       feat_extract_activation
        UpperCamelCase_							       =       list(__UpperCamelCase     )
        UpperCamelCase_							       =       list(__UpperCamelCase     )
        UpperCamelCase_							       =       list(__UpperCamelCase     )
        UpperCamelCase_							       =       conv_bias
        UpperCamelCase_							       =       num_conv_pos_embeddings
        UpperCamelCase_							       =       num_conv_pos_embedding_groups
        UpperCamelCase_							       =       len(self.conv_dim     )
        UpperCamelCase_							       =       num_hidden_layers
        UpperCamelCase_							       =       intermediate_size
        UpperCamelCase_							       =       hidden_act
        UpperCamelCase_							       =       num_attention_heads
        UpperCamelCase_							       =       hidden_dropout
        UpperCamelCase_							       =       attention_dropout
        UpperCamelCase_							       =       activation_dropout
        UpperCamelCase_							       =       feat_proj_layer_norm
        UpperCamelCase_							       =       feat_proj_dropout
        UpperCamelCase_							       =       final_dropout
        UpperCamelCase_							       =       layerdrop
        UpperCamelCase_							       =       layer_norm_eps
        UpperCamelCase_							       =       initializer_range
        UpperCamelCase_							       =       vocab_size
        UpperCamelCase_							       =       do_stable_layer_norm
        UpperCamelCase_							       =       use_weighted_layer_sum
        UpperCamelCase_							       =       classifier_proj_size

        if (
            (len(self.conv_stride     ) != self.num_feat_extract_layers)
            or (len(self.conv_kernel     ) != self.num_feat_extract_layers)
            or (len(self.conv_dim     ) != self.num_feat_extract_layers)
        ):
               raise ValueError(
                   """Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =="""
                   """ `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ="""
                   f''' {len(self.conv_dim     )}`, `len(config.conv_stride) = {len(self.conv_stride     )}`,'''
                   f''' `len(config.conv_kernel) = {len(self.conv_kernel     )}`.'''     )

        # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
        UpperCamelCase_							       =       apply_spec_augment
        UpperCamelCase_							       =       mask_time_prob
        UpperCamelCase_							       =       mask_time_length
        UpperCamelCase_							       =       mask_time_min_masks
        UpperCamelCase_							       =       mask_feature_prob
        UpperCamelCase_							       =       mask_feature_length
        UpperCamelCase_							       =       mask_feature_min_masks

        # ctc loss
        UpperCamelCase_							       =       ctc_loss_reduction
        UpperCamelCase_							       =       ctc_zero_infinity

 @property
 def lowerCamelCase_				(      self     ):




        """simple docstring"""


        return functools.reduce(operator.mul     ,	self.conv_stride     ,	1     )





import hashlib
import importlib.util
import json
import os
import pathlib
from types import ModuleType

import pytest
import requests

_A	  =					pathlib.Path.cwd().joinpath('''project_euler''')
_A	  =					pathlib.Path.cwd().joinpath(
    '''scripts''', '''project_euler_answers.json'''
)

with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
      _A	  =					json.load(file_handle)




def 				lowerCamelCase__				(						a__  :  pathlib.Path     )		->	ModuleType:
       UpperCamelCase_							       =       importlib.util.spec_from_file_location(file_path.name	,      str(a__     )     )
       UpperCamelCase_							       =       importlib.util.module_from_spec(a__     )  # type: ignore
       spec.loader.exec_module(a__     )  # type: ignore
       return module




def 				lowerCamelCase__				(						)		->	list[pathlib.Path]:
       UpperCamelCase_							       =       []
       for problem_dir_path in PROJECT_EULER_DIR_PATH.iterdir():
              if problem_dir_path.is_file() or problem_dir_path.name.startswith("""_"""     ):
                     continue
              for file_path in problem_dir_path.iterdir():
                     if file_path.suffix != ".py" or file_path.name.startswith(("""_""", """test""")     ):
                            continue
                     solution_file_paths.append(a__     )
       return solution_file_paths




def 				lowerCamelCase__				(						)		->	str:
       with open(os.environ["""GITHUB_EVENT_PATH"""]     ) as file:
              UpperCamelCase_							       =       json.load(a__     )
       return event["pull_request"]["url"] + "/files"




def 				lowerCamelCase__				(						)		->	list[pathlib.Path]:
       UpperCamelCase_							       =       []
       UpperCamelCase_							       =       {
           """Accept""": """application/vnd.github.v3+json""",
           """Authorization""": """token """ + os.environ["""GITHUB_TOKEN"""],
       }
       UpperCamelCase_							       =       requests.get(get_files_url()	,      headers=a__     ).json()
       for file in files:
              UpperCamelCase_							       =       pathlib.Path.cwd().joinpath(file["""filename"""]     )
              if (
                  filepath.suffix != ".py"
                  or filepath.name.startswith(("""_""", """test""")     )
                  or not filepath.name.startswith("""sol"""     )
              ):
                     continue
              solution_file_paths.append(a__     )
       return solution_file_paths




def 				lowerCamelCase__				(						)		->	list[pathlib.Path]:
       if os.environ.get("""CI"""     ) and os.environ.get("""GITHUB_EVENT_NAME"""     ) == "pull_request":
              # Return only if there are any, otherwise default to all solutions
              if filepaths := added_solution_file_path():
                     return filepaths
       return all_solution_file_paths()







@pytest.mark.parametrize(
    """solution_path"""	,      collect_solution_file_paths()	,      ids=lambda a__     : f'''{path.parent.name}/{path.name}'''	,      )
def 				lowerCamelCase__				(						a__  :  pathlib.Path     )		->	None:
       UpperCamelCase_							       =       solution_path.parent.name[8:].zfill(3     )
       UpperCamelCase_							       =       PROBLEM_ANSWERS[problem_number]
       UpperCamelCase_							       =       convert_path_to_module(a__     )
       UpperCamelCase_							       =       str(solution_module.solution()     )  # type: ignore
       UpperCamelCase_							       =       hashlib.shaaaa(answer.encode()     ).hexdigest()
       assert (
           answer == expected
       ), f'''Expected solution to {problem_number} to have hash {expected}, got {answer}'''



