


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase__     							= {
    'configuration_camembert': ['CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CamembertConfig', 'CamembertOnnxConfig'],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__     							= ['CamembertTokenizer']

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__     							= ['CamembertTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__     							= [
			    'CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'CamembertForCausalLM',
			    'CamembertForMaskedLM',
			    'CamembertForMultipleChoice',
			    'CamembertForQuestionAnswering',
			    'CamembertForSequenceClassification',
			    'CamembertForTokenClassification',
			    'CamembertModel',
			    'CamembertPreTrainedModel',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__     							= [
			    'TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'TFCamembertForCausalLM',
			    'TFCamembertForMaskedLM',
			    'TFCamembertForMultipleChoice',
			    'TFCamembertForQuestionAnswering',
			    'TFCamembertForSequenceClassification',
			    'TFCamembertForTokenClassification',
			    'TFCamembertModel',
			    'TFCamembertPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_camembert import CamembertTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_camembert_fast import CamembertTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_camembert import (
						    CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CamembertForCausalLM,
						    CamembertForMaskedLM,
						    CamembertForMultipleChoice,
						    CamembertForQuestionAnswering,
						    CamembertForSequenceClassification,
						    CamembertForTokenClassification,
						    CamembertModel,
						    CamembertPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_camembert import (
						    TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFCamembertForCausalLM,
						    TFCamembertForMaskedLM,
						    TFCamembertForMultipleChoice,
						    TFCamembertForQuestionAnswering,
						    TFCamembertForSequenceClassification,
						    TFCamembertForTokenClassification,
						    TFCamembertModel,
						    TFCamembertPreTrainedModel,
						)

else:
			import sys

			lowercase__     							= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






import dataclasses
import enum
import functools
import math
import re

# The following script is adapted from the script of TaPas.
# Original: https://github.com/google-research/tapas/master/wikisql_utils.py
from typing import Any, List, Text


snake_case__     							= 'none'
snake_case__     							= 'none'
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :List[str]      ,						lowercase__  :Optional[Any]				)       ->  List[str]:
						__magic_name__				:							Dict				=      value.split(lowercase__				)
						return len(lowercase__				) > 1 and any((len(lowercase__				) == 3 for x in split)				)
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :List[Any]				)       ->  List[str]:
						if isinstance(lowercase__      ,						lowercase__				):
												return value
						if isinstance(lowercase__      ,						lowercase__				):
												return float(lowercase__				)
						if not isinstance(lowercase__      ,						lowercase__				):
												raise ValueError('Argument value is not a string. Can\'t parse it as float'				)
						__magic_name__				:							List[str]				=      value

						try:
												# Example: 1,000.7
												if "." in sanitized and "," in sanitized:
																		return float(sanitized.replace(','      ,						''				)				)
												# 1,000
												if "," in sanitized and _split_thousands(','      ,						lowercase__				):
																		return float(sanitized.replace(','      ,						''				)				)
												# 5,5556
												if "," in sanitized and sanitized.count(','				) == 1 and not _split_thousands(','      ,						lowercase__				):
																		return float(sanitized.replace(','      ,						'.'				)				)
												# 0.0.0.1
												if sanitized.count('.'				) > 1:
																		return float(sanitized.replace('.'      ,						''				)				)
												# 0,0,0,1
												if sanitized.count(','				) > 1:
																		return float(sanitized.replace(','      ,						''				)				)
												return float(lowercase__				)
						except ValueError:
												# Avoid adding the sanitized value in the error message.
												raise ValueError('Unable to convert value to float'				)
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :Tuple				)       ->  Tuple:
						if answer is None:
												return None
						try:
												__magic_name__				:							Any				=      convert_to_float(lowercase__				)
												if isinstance(lowercase__      ,						lowercase__				) and math.isnan(lowercase__				):
																		return None
												return value
						except ValueError:
												return answer.lower()


snake_case__     							= {
    'text': lambda x: x,
    'real': convert_to_float,
}



class     snake_case__  (      enum.Enum  ):
				__lowerCAmelCase		=      0
				__lowerCAmelCase		=      1
				__lowerCAmelCase		=      2
				__lowerCAmelCase		=      3
				__lowerCAmelCase		=      4
				__lowerCAmelCase		=      5






class     snake_case__  (      enum.Enum  ):
				__lowerCAmelCase		=      0
				__lowerCAmelCase		=      1
				__lowerCAmelCase		=      2






@dataclasses.dataclass
class     snake_case__  :
				__lowerCAmelCase		=      42
				__lowerCAmelCase		=      42
				__lowerCAmelCase		=      42






snake_case__     							= re.compile(R'\w+|[^\w\s]+', re.UNICODE | re.MULTILINE | re.DOTALL)
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :Any				)       ->  str:
						return list(_TOKENIZER.findall(x.lower()				)				)
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :str      ,						lowercase__  :str      ,						lowercase__  :Dict				)       ->  Dict:
						if operator == _Operator.EQUALS:
												return src == tgt
						elif operator == _Operator.GREATER:
												return src > tgt
						elif operator == _Operator.LESSER:
												return src < tgt
						raise ValueError(f"Unknown operator: {operator}"				)
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :List[Any]      ,						lowercase__  :Tuple      ,						lowercase__  :Union[str, Any]				)       ->  Optional[int]:
						__magic_name__				:							str				=      table['types']
						return _TYPE_CONVERTER[types[column]](lowercase__				)
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :Tuple				)       ->  Union[str, Any]:
						return isinstance(lowercase__      ,						lowercase__				)
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :List[Any]      ,						lowercase__  :List[str]      ,						lowercase__  :int				)       ->  str:
						for cond in conditions:
												__magic_name__				:							Optional[Any]				=      row[cond.column]

												__magic_name__				:							List[str]				=      _parse_value(lowercase__      ,						cond.column      ,						cond.cmp_value				)

												if _is_string(lowercase__				) and _is_string(lowercase__				):
																		__magic_name__				:							str				=      _normalize_for_match(lowercase__				)
																		__magic_name__				:							List[str]				=      _normalize_for_match(lowercase__				)

												if not isinstance(lowercase__      ,						type(lowercase__				)				):
																		raise ValueError('Type difference {} != {}'.format(type(lowercase__				)      ,						type(lowercase__				)				)				)

												if not _compare(cond.operator      ,						lowercase__      ,						lowercase__				):
																		return False
						return True
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :str      ,						lowercase__  :List[Any]      ,						lowercase__  :List[Any]				)       ->  int:
						if not answer_coordinates:
												if aggregation_op == _Aggregation.COUNT:
																		return 0.0
												else:
																		return EMPTY_ANSWER_AGG

    # Count can support non numeric answers.
						if aggregation_op == _Aggregation.COUNT:
												return float(len(lowercase__				)				)

						# If we have just one answer, if float returns it or try a conversion.
						__magic_name__				:							Any				=      [table['rows'][i][j] for (i, j) in answer_coordinates]
						if len(lowercase__				) == 1:
												try:
																		return convert_to_float(values[0]				)
												except ValueError as e:
																		if aggregation_op != _Aggregation.NONE:
																								raise e

						if aggregation_op == _Aggregation.NONE:
												return None

						# Other aggregation only support numeric values. Bail out if we have strings.
						if not all((isinstance(lowercase__      ,						(int, float)				) for v in values)				):
												return None

						if aggregation_op == _Aggregation.SUM:
												return float(sum(lowercase__				)				)
						elif aggregation_op == _Aggregation.AVERAGE:
												return sum(lowercase__				) / len(lowercase__				)
						else:
												raise ValueError(f"Unknown aggregation: {aggregation_op}"				)
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :Tuple      ,						lowercase__  :Any				)       ->  Optional[int]:
						__magic_name__				:							Optional[Any]				=      sql_query['agg']
						if aggregation_op_index >= 3:
												__magic_name__				:							Any				=      _Aggregation(lowercase__				)
						else:
												__magic_name__				:							int				=      _Aggregation.NONE

						__magic_name__				:							str				=      sql_query['sel']
						__magic_name__				:							Any				=      [
						    _Condition(lowercase__      ,						_Operator(lowercase__				)      ,						lowercase__				)
						    for column, operator, cmp_value in zip(
						        sql_query['conds']['column_index']      ,						sql_query['conds']['operator_index']      ,						sql_query['conds']['condition']				)
						]

						__magic_name__				:							Any				=      []
						for row in range(len(table['rows']				)				):
												if _respect_conditions(lowercase__      ,						table['rows'][row]      ,						lowercase__				):
																		indices.append((row, target_column)				)

						if not indices:
												return [], aggregation_op

						if len(lowercase__				) == 1:
												return indices, aggregation_op

						# Parsing of MIN/MAX.
						if aggregation_op_index in (1, 2):
												__magic_name__				:							str				=      {2: min, 1: max}
												__magic_name__				:							Optional[int]				=      [(table['rows'][i][j], index) for index, (i, j) in enumerate(lowercase__				)]
												__magic_name__				:							str				=      functools.reduce(operators[sql_query['agg']]      ,						lowercase__				)

												__magic_name__				:							List[Any]				=      [indices[reduced[1]]]
												return ret, _Aggregation.NONE

						return indices, aggregation_op
def  __SCREAMING_SNAKE_CASE       (				lowercase__  :Tuple      ,						lowercase__  :Any      ,						lowercase__  :Optional[int]				)       ->  List[Any]:
						if float_answer is not None:
												return [str(lowercase__				)]
						return [str(table['real_rows'][r][c]				) for r, c in answer_coordinates]

def  __SCREAMING_SNAKE_CASE       (				lowercase__  :Optional[Any]      ,						lowercase__  :Union[str, Any]				)       ->  List:
						__magic_name__		, __magic_name__				:							List[Any]				=      _get_answer_coordinates(lowercase__      ,						lowercase__				)
						__magic_name__				:							List[Any]				=      _get_float_answer(lowercase__      ,						lowercase__      ,						lowercase__				)
						__magic_name__				:							Any				=      _get_answer_text(lowercase__      ,						lowercase__      ,						lowercase__				)
						# keep the original data the same with TaPas
						if len(lowercase__				) == 0:
												__magic_name__				:							int				=      [EMPTY_ANSWER]
						return answer_text


