



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

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


__lowerCamelCase     :							Dict  							=				logging.getLogger(__name__)





class  __magic_name__   (							__snake_case						):






		def __init__(						self      :     Any				,		UpperCamelCase__      :     Optional[Any]=-1      )				->					List[Any]:
								'''simple docstring'''







								UpperCAmelCase         =     label_idx






		def SCREAMING_SNAKE_CASE_			(						self      :     List[str]				,		UpperCamelCase__      :     List[Any]				,		UpperCamelCase__      :     Union[str, Any]      )				->					Tuple:
								'''simple docstring'''







								if isinstance(A_				,		A_      ):
														UpperCAmelCase         =     mode.value
								UpperCAmelCase         =     os.path.join(A_				,		F'{mode}.txt'      )
								UpperCAmelCase         =     1
								UpperCAmelCase         =     []
								with open(A_				,		encoding="utf-8"      ) as f:
														UpperCAmelCase         =     []
														UpperCAmelCase         =     []
														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
																																UpperCAmelCase         =     []
																																UpperCAmelCase         =     []
																				else:
																										UpperCAmelCase         =     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 SCREAMING_SNAKE_CASE_			(						self      :     List[str]				,		UpperCamelCase__      :     List[Any]				,		UpperCamelCase__      :     Optional[Any]				,		UpperCamelCase__      :     str      )				->					Optional[int]:
								'''simple docstring'''







								UpperCAmelCase         =     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]:
																				UpperCAmelCase         =     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 SCREAMING_SNAKE_CASE_			(						self      :     str				,		UpperCamelCase__      :     List[Any]      )				->					Union[str, Any]:
								'''simple docstring'''







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





class  __magic_name__   (							__snake_case						):






		def __init__(						self      :     Optional[int]      )				->					List[Any]:
								'''simple docstring'''







								super().__init__(label_idx=-2      )







		def SCREAMING_SNAKE_CASE_			(						self      :     int				,		UpperCamelCase__      :     Dict      )				->					Union[str, Any]:
								'''simple docstring'''







								if path:
														with open(A_				,		"r"      ) as f:
																				UpperCAmelCase         =     f.read().splitlines()
														if "O" not in labels:
																				UpperCAmelCase         =     ["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  __magic_name__   (							__snake_case						):






		def SCREAMING_SNAKE_CASE_			(						self      :     Tuple				,		UpperCamelCase__      :     Optional[int]				,		UpperCamelCase__      :     List[str]      )				->					Any:
								'''simple docstring'''







								if isinstance(A_				,		A_      ):
														UpperCAmelCase         =     mode.value
								UpperCAmelCase         =     os.path.join(A_				,		F'{mode}.txt'      )
								UpperCAmelCase         =     1
								UpperCAmelCase         =     []

								with open(A_				,		encoding="utf-8"      ) as f:
														for sentence in parse_incr(A_      ):
																				UpperCAmelCase         =     []
																				UpperCAmelCase         =     []
																				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 SCREAMING_SNAKE_CASE_			(						self      :     Tuple				,		UpperCamelCase__      :     Any				,		UpperCamelCase__      :     List[Any]				,		UpperCamelCase__      :     List[str]      )				->					Union[str, Any]:
								'''simple docstring'''







								UpperCAmelCase         =     0
								for sentence in parse_incr(A_      ):
														UpperCAmelCase         =     preds_list[example_id]
														UpperCAmelCase         =     ""
														for token in sentence:
																				out += F'{token["form"]} ({token["upos"]}|{s_p.pop(0      )}) '
														out += "\n"
														writer.write(A_      )
														example_id += 1







		def SCREAMING_SNAKE_CASE_			(						self      :     int				,		UpperCamelCase__      :     Union[str, Any]      )				->					Union[str, Any]:
								'''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",
														]








import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
		import torch





@require_torch
@require_optimum
@slow
class  __magic_name__   (							unittest.TestCase						):






		def SCREAMING_SNAKE_CASE_			(						self      :     Tuple      )				->					Optional[int]:
								'''simple docstring'''







								UpperCAmelCase         =     "hf-internal-testing/tiny-random-t5"
								UpperCAmelCase         =     AutoTokenizer.from_pretrained(UpperCamelCase__      )
								UpperCAmelCase         =     AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__      )

								UpperCAmelCase         =     tokenizer("This is me"				,		return_tensors="pt"      )

								UpperCAmelCase         =     model.to_bettertransformer()

								self.assertTrue(any("BetterTransformer" in mod.__class__.__name__ for _, mod in model.named_modules()      )      )

								UpperCAmelCase         =     model.generate(**UpperCamelCase__      )

								UpperCAmelCase         =     model.reverse_bettertransformer()

								self.assertFalse(any("BetterTransformer" in mod.__class__.__name__ for _, mod in model.named_modules()      )      )

								with tempfile.TemporaryDirectory() as tmpdirname:
														model.save_pretrained(UpperCamelCase__      )

														UpperCAmelCase         =     AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__      )

														self.assertFalse(
														    any("BetterTransformer" in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()      )      )

														UpperCAmelCase         =     model_reloaded.generate(**UpperCamelCase__      )
														self.assertTrue(torch.allclose(UpperCamelCase__				,		UpperCamelCase__      )      )







		def SCREAMING_SNAKE_CASE_			(						self      :     List[str]      )				->					Optional[int]:
								'''simple docstring'''







								UpperCAmelCase         =     "hf-internal-testing/tiny-random-t5"
								UpperCAmelCase         =     AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__      )

								UpperCAmelCase         =     model.to_bettertransformer()

								with tempfile.TemporaryDirectory() as tmpdirname:
														with self.assertRaises(UpperCamelCase__      ):
																				model.save_pretrained(UpperCamelCase__      )

														UpperCAmelCase         =     model.reverse_bettertransformer()
														model.save_pretrained(UpperCamelCase__      )



