



import logging
import os
from typing import List, TextIO, Union

from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask


_snake_case	=						logging.getLogger(__name__)



class 						UpperCAmelCase_					( _lowerCamelCase):







							def __init__(     self,    __a=-1):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[int]				     =					label_idx







							def      snake_case__   (     self,    __a,    __a):

														'''simple docstring'''

														if isinstance(A__,    A__):
																					_lowerCAmelCase  :							Optional[Any]				     =					mode.value
														_lowerCAmelCase  :							List[Any]				     =					os.path.join(A__,    f"{mode}.txt")
														_lowerCAmelCase  :							Optional[Any]				     =					1
														_lowerCAmelCase  :							Optional[Any]				     =					[]
														with open(A__,    encoding="utf-8") as f:
																					_lowerCAmelCase  :							str				     =					[]
																					_lowerCAmelCase  :							Optional[int]				     =					[]
																					for line in f:
																												if line.startswith("-DOCSTART-") or line == "" or line == "\n":
																																			if words:
																																										examples.append(InputExample(guid=f"{mode}-{guid_index}",    words=A__,    labels=A__))
																																										guid_index += 1
																																										_lowerCAmelCase  :							List[Any]				     =					[]
																																										_lowerCAmelCase  :							Optional[int]				     =					[]
																												else:
																																			_lowerCAmelCase  :							List[str]				     =					line.split(" ")
																																			words.append(splits[0])
																																			if len(A__) > 1:
																																										labels.append(splits[self.label_idx].replace("\n",    ""))
																																			else:
																																										# Examples could have no label for mode = "test"
																																										labels.append("O")
																					if words:
																												examples.append(InputExample(guid=f"{mode}-{guid_index}",    words=A__,    labels=A__))
														return examples







							def      snake_case__   (     self,    __a,    __a,    __a):

														'''simple docstring'''

														_lowerCAmelCase  :							List[Any]				     =					0
														for line in test_input_reader:
																					if line.startswith("-DOCSTART-") or line == "" or line == "\n":
																												writer.write(A__)
																												if not preds_list[example_id]:
																																			example_id += 1
																					elif preds_list[example_id]:
																												_lowerCAmelCase  :							Tuple				     =					line.split()[0] + " " + preds_list[example_id].pop(0) + "\n"
																												writer.write(A__)
																					else:
																												logger.warning("Maximum sequence length exceeded: No prediction for '%s'.",    line.split()[0])







							def      snake_case__   (     self,    __a):

														'''simple docstring'''

														if path:
																					with open(A__,    "r") as f:
																												_lowerCAmelCase  :							Any				     =					f.read().splitlines()
																					if "O" not in labels:
																												_lowerCAmelCase  :							Any				     =					["O"] + labels
																					return labels
														else:
																					return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]



class 						UpperCAmelCase_					( _lowerCamelCase):







							def __init__(     self):

														'''simple docstring'''

														super().__init__(label_idx=-2)







							def      snake_case__   (     self,    __a):

														'''simple docstring'''

														if path:
																					with open(A__,    "r") as f:
																												_lowerCAmelCase  :							str				     =					f.read().splitlines()
																					if "O" not in labels:
																												_lowerCAmelCase  :							Union[str, Any]				     =					["O"] + labels
																					return labels
														else:
																					return [
																					    "O",
																					    "B-ADVP",
																					    "B-INTJ",
																					    "B-LST",
																					    "B-PRT",
																					    "B-NP",
																					    "B-SBAR",
																					    "B-VP",
																					    "B-ADJP",
																					    "B-CONJP",
																					    "B-PP",
																					    "I-ADVP",
																					    "I-INTJ",
																					    "I-LST",
																					    "I-PRT",
																					    "I-NP",
																					    "I-SBAR",
																					    "I-VP",
																					    "I-ADJP",
																					    "I-CONJP",
																					    "I-PP",
																					]



class 						UpperCAmelCase_					( _lowerCamelCase):







							def      snake_case__   (     self,    __a,    __a):

														'''simple docstring'''

														if isinstance(A__,    A__):
																					_lowerCAmelCase  :							Optional[int]				     =					mode.value
														_lowerCAmelCase  :							List[str]				     =					os.path.join(A__,    f"{mode}.txt")
														_lowerCAmelCase  :							List[Any]				     =					1
														_lowerCAmelCase  :							Optional[int]				     =					[]

														with open(A__,    encoding="utf-8") as f:
																					for sentence in parse_incr(A__):
																												_lowerCAmelCase  :							Tuple				     =					[]
																												_lowerCAmelCase  :							Dict				     =					[]
																												for token in sentence:
																																			words.append(token["form"])
																																			labels.append(token["upos"])
																												assert len(A__) == len(A__)
																												if words:
																																			examples.append(InputExample(guid=f"{mode}-{guid_index}",    words=A__,    labels=A__))
																																			guid_index += 1
														return examples







							def      snake_case__   (     self,    __a,    __a,    __a):

														'''simple docstring'''

														_lowerCAmelCase  :							Tuple				     =					0
														for sentence in parse_incr(A__):
																					_lowerCAmelCase  :							str				     =					preds_list[example_id]
																					_lowerCAmelCase  :							Union[str, Any]				     =					""
																					for token in sentence:
																												out += f"{token['form']} ({token['upos']}|{s_p.pop(0)}) "
																					out += "\n"
																					writer.write(A__)
																					example_id += 1







							def      snake_case__   (     self,    __a):

														'''simple docstring'''

														if path:
																					with open(A__,    "r") as f:
																												return f.read().splitlines()
														else:
																					return [
																					    "ADJ",
																					    "ADP",
																					    "ADV",
																					    "AUX",
																					    "CCONJ",
																					    "DET",
																					    "INTJ",
																					    "NOUN",
																					    "NUM",
																					    "PART",
																					    "PRON",
																					    "PROPN",
																					    "PUNCT",
																					    "SCONJ",
																					    "SYM",
																					    "VERB",
																					    "X",
																					]





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


_snake_case	=						logging.get_logger(__name__)

_snake_case	=						{
    "weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}



class 						UpperCAmelCase_					( a):
							lowerCamelCase__         =	'roc_bert'







							def __init__(     self,    __a=3_0522,    __a=768,    __a=12,    __a=12,    __a=3072,    __a="gelu",    __a=0.1,    __a=0.1,    __a=512,    __a=2,    __a=0.02,    __a=1E-12,    __a=True,    __a=0,    __a="absolute",    __a=None,    __a=True,    __a=True,    __a=768,    __a=910,    __a=512,    __a=2_4858,    __a=True,    **__a,    ):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[Any]				     =					vocab_size
														_lowerCAmelCase  :							Optional[Any]				     =					max_position_embeddings
														_lowerCAmelCase  :							Union[str, Any]				     =					hidden_size
														_lowerCAmelCase  :							str				     =					num_hidden_layers
														_lowerCAmelCase  :							List[Any]				     =					num_attention_heads
														_lowerCAmelCase  :							int				     =					intermediate_size
														_lowerCAmelCase  :							Optional[int]				     =					hidden_act
														_lowerCAmelCase  :							Optional[Any]				     =					hidden_dropout_prob
														_lowerCAmelCase  :							Optional[Any]				     =					attention_probs_dropout_prob
														_lowerCAmelCase  :							Union[str, Any]				     =					initializer_range
														_lowerCAmelCase  :							Optional[Any]				     =					type_vocab_size
														_lowerCAmelCase  :							int				     =					layer_norm_eps
														_lowerCAmelCase  :							Union[str, Any]				     =					use_cache
														_lowerCAmelCase  :							Optional[int]				     =					enable_pronunciation
														_lowerCAmelCase  :							Dict				     =					enable_shape
														_lowerCAmelCase  :							Optional[Any]				     =					pronunciation_embed_dim
														_lowerCAmelCase  :							Any				     =					pronunciation_vocab_size
														_lowerCAmelCase  :							List[str]				     =					shape_embed_dim
														_lowerCAmelCase  :							int				     =					shape_vocab_size
														_lowerCAmelCase  :							Optional[int]				     =					concat_input
														_lowerCAmelCase  :							Dict				     =					position_embedding_type
														_lowerCAmelCase  :							Tuple				     =					classifier_dropout
														super().__init__(pad_token_id=__a,    **__a)
