



"""simple docstring"""







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

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


lowerCAmelCase_   						=   logging.getLogger(__name__)
class        __A       (	A_    ):







		'''simple docstring'''





		def __init__(	self						:  Optional[int]			,_snake_case						:  Tuple=-1						)					->		int:






				"""simple docstring"""



				lowercase__   :    Union[str, Any]				=			label_idx







		def 					UpperCAmelCase    (	self						:  Any			,_snake_case						:  int			,_snake_case						:  Union[Split, str]						)					->		List[InputExample]:






				"""simple docstring"""



				if isinstance(_snake_case			,_snake_case						):
						lowercase__   :    Optional[int]				=			mode.value
				lowercase__   :    Optional[Any]				=			os.path.join(_snake_case			,f"""{mode}.txt"""						)
				lowercase__   :    Union[str, Any]				=			1
				lowercase__   :    Tuple				=			[]
				with open(_snake_case			,encoding='''utf-8'''						) as f:
						lowercase__   :    Union[str, Any]				=			[]
						lowercase__   :    Tuple				=			[]
						for line in f:
								if line.startswith('''-DOCSTART-'''						) or line == "" or line == "\n":
										if words:
												examples.append(InputExample(guid=f"""{mode}-{guid_index}"""			,words=_snake_case			,labels=_snake_case						)						)
												guid_index += 1
												lowercase__   :    List[str]				=			[]
												lowercase__   :    List[Any]				=			[]
								else:
										lowercase__   :    Dict				=			line.split(''' '''						)
										words.append(splits[0]						)
										if len(_snake_case						) > 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=_snake_case			,labels=_snake_case						)						)
				return examples







		def 					UpperCAmelCase    (	self						:  str			,_snake_case						:  TextIO			,_snake_case						:  TextIO			,_snake_case						:  List						)					->		List[Any]:






				"""simple docstring"""



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







		def 					UpperCAmelCase    (	self						:  Tuple			,_snake_case						:  str						)					->		List[str]:






				"""simple docstring"""



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





class        __A       (	A_    ):







		'''simple docstring'''





		def __init__(	self						:  str						)					->		Any:






				"""simple docstring"""



				super().__init__(label_idx=-2						)







		def 					UpperCAmelCase    (	self						:  str			,_snake_case						:  str						)					->		List[str]:






				"""simple docstring"""



				if path:
						with open(_snake_case			,'''r'''						) as f:
								lowercase__   :    int				=			f.read().splitlines()
						if "O" not in labels:
								lowercase__   :    List[str]				=			['''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        __A       (	A_    ):







		'''simple docstring'''





		def 					UpperCAmelCase    (	self						:  int			,_snake_case						:  Optional[int]			,_snake_case						:  Union[Split, str]						)					->		List[InputExample]:






				"""simple docstring"""



				if isinstance(_snake_case			,_snake_case						):
						lowercase__   :    List[str]				=			mode.value
				lowercase__   :    str				=			os.path.join(_snake_case			,f"""{mode}.txt"""						)
				lowercase__   :    Union[str, Any]				=			1
				lowercase__   :    Tuple				=			[]

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







		def 					UpperCAmelCase    (	self						:  List[Any]			,_snake_case						:  TextIO			,_snake_case						:  TextIO			,_snake_case						:  List						)					->		str:






				"""simple docstring"""



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







		def 					UpperCAmelCase    (	self						:  List[str]			,_snake_case						:  str						)					->		List[str]:






				"""simple docstring"""



				if path:
						with open(_snake_case			,'''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",
						]





"""simple docstring"""







from collections import UserDict
from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    is_torch_available,
    is_vision_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
							from PIL import Image

							from ..image_utils import load_image

if is_torch_available():
							from ..models.auto.modeling_auto import MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING

if is_tf_available():
							from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING
							from ..tf_utils import stable_softmax

lowerCAmelCase_   						=   logging.get_logger(__name__)
@add_end_docstrings(A_    )
class        __A       (	A_    ):







		'''simple docstring'''





		def __init__(	self						:  List[str]			,**_snake_case						:  Dict						)					->		List[Any]:






				"""simple docstring"""



				super().__init__(**_snake_case						)

				requires_backends(self			,'''vision'''						)
				self.check_model_type(
				    TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING
				    if self.framework == '''tf'''
				    else MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING						)







		def __call__(	self						:  Optional[int]			,_snake_case						:  Union[str, List[str], "Image", List["Image"]]			,**_snake_case						:  int						)					->		Optional[Any]:






				"""simple docstring"""



				return super().__call__(_snake_case			,**_snake_case						)







		def 					UpperCAmelCase    (	self						:  Dict			,**_snake_case						:  Optional[int]						)					->		List[Any]:






				"""simple docstring"""



				lowercase__   :    List[str]				=			{}
				if "candidate_labels" in kwargs:
						lowercase__   :    Any				=			kwargs['''candidate_labels''']
				if "hypothesis_template" in kwargs:
						lowercase__   :    Optional[Any]				=			kwargs['''hypothesis_template''']

				return preprocess_params, {}, {}







		def 					UpperCAmelCase    (	self						:  Optional[Any]			,_snake_case						:  Optional[int]			,_snake_case						:  Dict=None			,_snake_case						:  Union[str, Any]="This is a photo of {}."						)					->		List[str]:






				"""simple docstring"""



				lowercase__   :    List[Any]				=			load_image(_snake_case						)
				lowercase__   :    int				=			self.image_processor(images=[image]			,return_tensors=self.framework						)
				lowercase__   :    str				=			candidate_labels
				lowercase__   :    Dict				=			[hypothesis_template.format(_snake_case						) for x in candidate_labels]
				lowercase__   :    Any				=			self.tokenizer(_snake_case			,return_tensors=self.framework			,padding=_snake_case						)
				lowercase__   :    Optional[int]				=			[text_inputs]
				return inputs







		def 					UpperCAmelCase    (	self						:  Optional[Any]			,_snake_case						:  Optional[int]						)					->		List[Any]:






				"""simple docstring"""



				lowercase__   :    Optional[int]				=			model_inputs.pop('''candidate_labels'''						)
				lowercase__   :    Union[str, Any]				=			model_inputs.pop('''text_inputs'''						)
				if isinstance(text_inputs[0]			,_snake_case						):
						lowercase__   :    List[str]				=			text_inputs[0]
				else:
						# Batching case.
						lowercase__   :    int				=			text_inputs[0][0]

				lowercase__   :    Tuple				=			self.model(**_snake_case			,**_snake_case						)

				lowercase__   :    Union[str, Any]				=			{
				    '''candidate_labels''': candidate_labels,
				    '''logits''': outputs.logits_per_image,
				}
				return model_outputs







		def 					UpperCAmelCase    (	self						:  Any			,_snake_case						:  Tuple						)					->		Any:






				"""simple docstring"""



				lowercase__   :    Dict				=			model_outputs.pop('''candidate_labels'''						)
				lowercase__   :    Optional[Any]				=			model_outputs['''logits'''][0]
				if self.framework == "pt":
						lowercase__   :    Optional[int]				=			logits.softmax(dim=-1						).squeeze(-1						)
						lowercase__   :    Tuple				=			probs.tolist()
						if not isinstance(_snake_case			,_snake_case						):
								lowercase__   :    Any				=			[scores]
				elif self.framework == "tf":
						lowercase__   :    List[str]				=			stable_softmax(_snake_case			,axis=-1						)
						lowercase__   :    Optional[Any]				=			probs.numpy().tolist()
				else:
						raise ValueError(f"""Unsupported framework: {self.framework}"""						)

				lowercase__   :    Union[str, Any]				=			[
				    {'''score''': score, '''label''': candidate_label}
				    for score, candidate_label in sorted(zip(_snake_case			,_snake_case						)			,key=lambda _snake_case						: -x[0]						)
				]
				return result
