
'''simple docstring'''

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


snake_case									=    logging.get_logger(__name__)

# TODO: upload to AWS
snake_case									=    {
    """yjernite/retribert-base-uncased""": (
        """https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"""
    ),
}




class    lowerCAmelCase       (     UpperCamelCase_  ):
 A_				:				Dict	=			"""retribert"""


 def __init__(    self  : int			,							a__  : Any=3_0522			,							a__  : Optional[int]=768			,							a__  : Tuple=8			,							a__  : Tuple=12			,							a__  : List[Any]=3072			,							a__  : Any="gelu"			,							a__  : Dict=0.1			,							a__  : Union[str, Any]=0.1			,							a__  : List[Any]=512			,							a__  : Optional[int]=2			,							a__  : Optional[Any]=0.02			,							a__  : List[Any]=1e-12			,							a__  : int=True			,							a__  : int=128			,							a__  : str=0			,							**a__  : List[Any]			,							):
  '''simple docstring'''

  super().__init__(pad_token_id=_lowercase			,							**_lowercase    )

  lowerCAmelCase__     :   Tuple     		=	vocab_size
  lowerCAmelCase__     :   int     		=	hidden_size
  lowerCAmelCase__     :   Dict     		=	num_hidden_layers
  lowerCAmelCase__     :   Tuple     		=	num_attention_heads
  lowerCAmelCase__     :   List[Any]     		=	hidden_act
  lowerCAmelCase__     :   Dict     		=	intermediate_size
  lowerCAmelCase__     :   Any     		=	hidden_dropout_prob
  lowerCAmelCase__     :   Union[str, Any]     		=	attention_probs_dropout_prob
  lowerCAmelCase__     :   Union[str, Any]     		=	max_position_embeddings
  lowerCAmelCase__     :   int     		=	type_vocab_size
  lowerCAmelCase__     :   Any     		=	initializer_range
  lowerCAmelCase__     :   Union[str, Any]     		=	layer_norm_eps
  lowerCAmelCase__     :   str     		=	share_encoders
  lowerCAmelCase__     :   Tuple     		=	projection_dim











'''simple docstring'''
import re
import time
from typing import Optional

import IPython.display as disp

from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		str:
			A_									= int(SCREAMING_SNAKE_CASE_     )
			A_		, A_		, A_									= t // 3600, (t // 60) % 60, t % 60
			return F'{h}:{m:02d}:{s:02d}' if h != 0 else F'{m:02d}:{s:02d}'





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_=300     )		->		Dict:
			# docstyle-ignore
			return F'\n    <div>\n      {prefix}\n      <progress value=\'{value}\' max=\'{total}\' style=\'width:{width}px; height:20px; vertical-align: middle;\'></progress>\n      {label}\n    </div>\n    '





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		List[str]:
			A_									= '<table border="1" class="dataframe">\n'
			html_code += """  <thead>\n <tr style="text-align: left;">\n"""
			for i in items[0]:
						html_code += F'      <th>{i}</th>\n'
			html_code += "    </tr>\n  </thead>\n  <tbody>\n"
			for line in items[1:]:
						html_code += "    <tr>\n"
						for elt in line:
									A_									= F'{elt:.6f}' if isinstance(SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_     ) else str(SCREAMING_SNAKE_CASE_     )
									html_code += F'      <td>{elt}</td>\n'
						html_code += "    </tr>\n"
			html_code += "  </tbody>\n</table><p>"
			return html_code
class   __UpperCAmelCase				:



					'''simple docstring'''





					_UpperCamelCase							=		5
					_UpperCamelCase							=		0.2



					def __init__(	self     :						Tuple      ,       _lowercase     :						int      ,       _lowercase     :						Optional[str] = None      ,       _lowercase     :						bool = True      ,       _lowercase     :						Optional["NotebookTrainingTracker"] = None      ,       _lowercase     :						int = 300      ,       )    ->							Dict:
								A_									= total
								A_									= '' if prefix is None else prefix
								A_									= leave
								A_									= parent
								A_									= width
								A_									= None
								A_									= None
								A_									= None



					def     __snake_case						(	self     :						Optional[int]      ,       _lowercase     :						int      ,       _lowercase     :						bool = False      ,       _lowercase     :						str = None)    ->							Dict:
								A_									= value
								if comment is not None:
											A_									= comment
								if self.last_value is None:
											A_									= A_									= time.time()
											A_									= A_									= value
											A_									= A_									= None
											A_									= self.warmup
											A_									= 1
											self.update_bar(_lowercase)
								elif value <= self.last_value and not force_update:
											return
								elif force_update or self.first_calls > 0 or value >= min(self.last_value + self.wait_for      ,       self.total):
											if self.first_calls > 0:
														self.first_calls -= 1
											A_									= time.time()
											A_									= current_time - self.start_time
											# We could have value = self.start_value if the update is called twixe with the same start value.
											if value > self.start_value:
														A_									= self.elapsed_time / (value - self.start_value)
											else:
														A_									= None
											if value >= self.total:
														A_									= self.total
														A_									= None
														if not self.leave:
																	self.close()
											elif self.average_time_per_item is not None:
														A_									= self.average_time_per_item * (self.total - value)
											self.update_bar(_lowercase)
											A_									= value
											A_									= current_time
											if self.average_time_per_item is None:
														A_									= 1
											else:
														A_									= max(int(self.update_every / self.average_time_per_item)      ,       1)



					def     __snake_case						(	self     :						str      ,       _lowercase     :						List[Any]      ,       _lowercase     :						Optional[int]=None)    ->							str:
								A_									= ' ' * (len(str(self.total)) - len(str(_lowercase))) + str(_lowercase)
								if self.elapsed_time is None:
											A_									= F'[{spaced_value}/{self.total} : < :'
								elif self.predicted_remaining is None:
											A_									= F'[{spaced_value}/{self.total} {format_time(self.elapsed_time)}'
								else:
											A_									= (
											    F'[{spaced_value}/{self.total} {format_time(self.elapsed_time)} <'
											    F' {format_time(self.predicted_remaining)}'
											)
											self.label += F', {1/self.average_time_per_item:.2f} it/s'
								self.label += "]" if self.comment is None or len(self.comment) == 0 else F', {self.comment}]'
								self.display()



					def     __snake_case						(	self     :						Optional[int])    ->							Dict:
								A_									= html_progress_bar(self.value      ,       self.total      ,       self.prefix      ,       self.label      ,       self.width)
								if self.parent is not None:
											# If this is a child bar, the parent will take care of the display.
											self.parent.display()
											return
								if self.output is None:
											A_									= disp.display(disp.HTML(self.html_code)      ,       display_id=_lowercase)
								else:
											self.output.update(disp.HTML(self.html_code))



					def     __snake_case						(	self     :						List[Any])    ->							Optional[Any]:
								if self.parent is None and self.output is not None:
											self.output.update(disp.HTML(''))





class   __UpperCAmelCase				(     lowerCAmelCase				):



					'''simple docstring'''





					def __init__(	self     :						int      ,       _lowercase     :						Union[str, Any]      ,       _lowercase     :						str=None)    ->							str:
								super().__init__(_lowercase)
								A_									= None if column_names is None else [column_names]
								A_									= None



					def     __snake_case						(	self     :						Dict)    ->							List[Any]:
								A_									= html_progress_bar(self.value      ,       self.total      ,       self.prefix      ,       self.label      ,       self.width)
								if self.inner_table is not None:
											self.html_code += text_to_html_table(self.inner_table)
								if self.child_bar is not None:
											self.html_code += self.child_bar.html_code
								if self.output is None:
											A_									= disp.display(disp.HTML(self.html_code)      ,       display_id=_lowercase)
								else:
											self.output.update(disp.HTML(self.html_code))



					def     __snake_case						(	self     :						str      ,       _lowercase     :						int)    ->							Optional[int]:
								if self.inner_table is None:
											A_									= [list(values.keys()), list(values.values())]
								else:
											A_									= self.inner_table[0]
											if len(self.inner_table) == 1:
														# We give a chance to update the column names at the first iteration
														for key in values.keys():
																	if key not in columns:
																				columns.append(_lowercase)
														A_									= columns
											self.inner_table.append([values[c] for c in columns])



					def     __snake_case						(	self     :						List[Any]      ,       _lowercase     :						Union[str, Any]      ,       _lowercase     :						str=None      ,       _lowercase     :						Optional[int]=300)    ->							Dict:
								A_									= NotebookProgressBar(_lowercase      ,       prefix=_lowercase      ,       parent=self      ,       width=_lowercase)
								return self.child_bar



					def     __snake_case						(	self     :						Any)    ->							int:
								A_									= None
								self.display()





class   __UpperCAmelCase				(     lowerCAmelCase				):



					'''simple docstring'''





					def __init__(	self     :						Dict)    ->							Tuple:
								A_									= None
								A_									= None
								A_									= False



					def     __snake_case						(	self     :						int      ,       _lowercase     :						str      ,       _lowercase     :						str      ,       _lowercase     :						str      ,       **_lowercase     :						List[Any])    ->							List[Any]:
								A_									= 'Epoch' if args.evaluation_strategy == IntervalStrategy.EPOCH else 'Step'
								A_									= 0
								A_									= 0
								A_									= [self.first_column] + ['Training Loss']
								if args.evaluation_strategy != IntervalStrategy.NO:
											column_names.append('Validation Loss')
								A_									= NotebookTrainingTracker(state.max_steps      ,       _lowercase)



					def     __snake_case						(	self     :						Tuple      ,       _lowercase     :						Union[str, Any]      ,       _lowercase     :						List[Any]      ,       _lowercase     :						List[str]      ,       **_lowercase     :						Union[str, Any])    ->							str:
								A_									= int(state.epoch) if int(state.epoch) == state.epoch else F'{state.epoch:.2f}'
								self.training_tracker.update(
								    state.global_step + 1      ,       comment=F'Epoch {epoch}/{state.num_train_epochs}'      ,       force_update=self._force_next_update      ,       )
								A_									= False



					def     __snake_case						(	self     :						Union[str, Any]      ,       _lowercase     :						Any      ,       _lowercase     :						int      ,       _lowercase     :						Optional[int]      ,       _lowercase     :						List[Any]=None      ,       **_lowercase     :						Any)    ->							Union[str, Any]:
								if not has_length(_lowercase):
											return
								if self.prediction_bar is None:
											if self.training_tracker is not None:
														A_									= self.training_tracker.add_child(len(_lowercase))
											else:
														A_									= NotebookProgressBar(len(_lowercase))
											self.prediction_bar.update(1)
								else:
											self.prediction_bar.update(self.prediction_bar.value + 1)



					def     __snake_case						(	self     :						List[Any]      ,       _lowercase     :						List[str]      ,       _lowercase     :						Any      ,       _lowercase     :						Union[str, Any]      ,       **_lowercase     :						Optional[int])    ->							Optional[Any]:
								if self.prediction_bar is not None:
											self.prediction_bar.close()
								A_									= None



					def     __snake_case						(	self     :						Dict      ,       _lowercase     :						Dict      ,       _lowercase     :						str      ,       _lowercase     :						str      ,       _lowercase     :						Optional[Any]=None      ,       **_lowercase     :						Dict)    ->							Optional[int]:
								# Only for when there is no evaluation
								if args.evaluation_strategy == IntervalStrategy.NO and "loss" in logs:
											A_									= {'Training Loss': logs['loss']}
											# First column is necessarily Step sine we're not in epoch eval strategy
											A_									= state.global_step
											self.training_tracker.write_line(_lowercase)



					def     __snake_case						(	self     :						List[Any]      ,       _lowercase     :						Any      ,       _lowercase     :						Optional[int]      ,       _lowercase     :						str      ,       _lowercase     :						Optional[Any]=None      ,       **_lowercase     :						Union[str, Any])    ->							Union[str, Any]:
								if self.training_tracker is not None:
											A_									= {'Training Loss': 'No log', 'Validation Loss': 'No log'}
											for log in reversed(state.log_history):
														if "loss" in log:
																	A_									= log['loss']
																	break

											if self.first_column == "Epoch":
														A_									= int(state.epoch)
											else:
														A_									= state.global_step
											A_									= 'eval'
											for k in metrics:
														if k.endswith('_loss'):
																	A_									= re.sub(r'\_loss$'      ,       ''      ,       _lowercase)
											A_									= metrics.pop('total_flos'      ,       _lowercase)
											A_									= metrics.pop('epoch'      ,       _lowercase)
											A_									= metrics.pop(F'{metric_key_prefix}_runtime'      ,       _lowercase)
											A_									= metrics.pop(F'{metric_key_prefix}_samples_per_second'      ,       _lowercase)
											A_									= metrics.pop(F'{metric_key_prefix}_steps_per_second'      ,       _lowercase)
											A_									= metrics.pop(F'{metric_key_prefix}_jit_compilation_time'      ,       _lowercase)
											for k, v in metrics.items():
														if k == F'{metric_key_prefix}_loss':
																	A_									= v
														else:
																	A_									= k.split('_')
																	A_									= ' '.join([part.capitalize() for part in splits[1:]])
																	A_									= v
											self.training_tracker.write_line(_lowercase)
											self.training_tracker.remove_child()
											A_									= None
											# Evaluation takes a long time so we should force the next update.
											A_									= True



					def     __snake_case						(	self     :						Tuple      ,       _lowercase     :						Dict      ,       _lowercase     :						str      ,       _lowercase     :						List[str]      ,       **_lowercase     :						str)    ->							Optional[int]:
								self.training_tracker.update(
								    state.global_step      ,       comment=F'Epoch {int(state.epoch)}/{state.num_train_epochs}'      ,       force_update=_lowercase)
								A_									= None




