




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

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


_lowerCamelCase   :	List[Any]       =    logging.getLogger(__name__)
class 							__snake_case	(lowercase_		):



				def __init__(   self   :		Dict		,						_UpperCAmelCase   :		List[Any]=-1   )	->     Tuple:





								'''simple docstring'''




								_lowerCAmelCase     :     Dict              =   label_idx



				def    SCREAMING_SNAKE_CASE							(   self   :		Union[str, Any]		,						_UpperCAmelCase   :		List[Any]		,						_UpperCAmelCase   :		Optional[Any]   )	->     int:





								'''simple docstring'''




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



				def    SCREAMING_SNAKE_CASE							(   self   :		Optional[int]		,						_UpperCAmelCase   :		Optional[int]		,						_UpperCAmelCase   :		int		,						_UpperCAmelCase   :		Union[str, Any]   )	->     Optional[int]:





								'''simple docstring'''




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



				def    SCREAMING_SNAKE_CASE							(   self   :		Optional[Any]		,						_UpperCAmelCase   :		Optional[Any]   )	->     List[Any]:





								'''simple docstring'''




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






class 							__snake_case	(lowercase_		):



				def __init__(   self   :		Optional[Any]   )	->     Optional[Any]:





								'''simple docstring'''




								super().__init__(label_idx=-2   )



				def    SCREAMING_SNAKE_CASE							(   self   :		List[Any]		,						_UpperCAmelCase   :		Dict   )	->     List[Any]:





								'''simple docstring'''




								if path:
												with open(_UpperCAmelCase		,						"""r"""   ) as f:
																_lowerCAmelCase     :     str              =   f.read().splitlines()
												if "O" not in labels:
																_lowerCAmelCase     :     Optional[int]              =   ["""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 							__snake_case	(lowercase_		):



				def    SCREAMING_SNAKE_CASE							(   self   :		Tuple		,						_UpperCAmelCase   :		Optional[int]		,						_UpperCAmelCase   :		Union[str, Any]   )	->     Any:





								'''simple docstring'''




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

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



				def    SCREAMING_SNAKE_CASE							(   self   :		Dict		,						_UpperCAmelCase   :		Union[str, Any]		,						_UpperCAmelCase   :		Tuple		,						_UpperCAmelCase   :		int   )	->     Tuple:





								'''simple docstring'''




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



				def    SCREAMING_SNAKE_CASE							(   self   :		Dict		,						_UpperCAmelCase   :		Optional[Any]   )	->     Optional[Any]:





								'''simple docstring'''




								if path:
												with open(_UpperCAmelCase		,						"""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 make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


_UpperCAmelCase						:  Dict									=			"""sshleifer/bart-tiny-random"""
_UpperCAmelCase						:  Optional[Any]									=			"""patrickvonplaten/t5-tiny-random"""







@require_torch
class 					lowercase							(			unittest.TestCase     ):




				@cached_property
				def        a				(   self			):
											return AutoConfig.from_pretrained(snake_case			)




				def        a				(   self			):
											snake_case_							,       *snake_case_     							=       create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=1 ,  d=1			)
											self.assertEqual(student.config.num_hidden_layers ,  1			)




				def        a				(   self			):
											snake_case_							,       *snake_case_     							=       create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=1 ,  d=snake_case			)




				def        a				(   self			):
											snake_case_							,       *snake_case_     							=       create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=1 ,  d=snake_case			)
											self.assertEqual(student.config.encoder_layers ,  1			)
											self.assertEqual(student.config.decoder_layers ,  self.teacher_config.encoder_layers			)




				def        a				(   self			):
											snake_case_							,       *snake_case_     							=       create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=1 ,  d=1			)
											self.assertEqual(student.config.encoder_layers ,  1			)
											self.assertEqual(student.config.decoder_layers ,  1			)




				def        a				(   self			):
											with self.assertRaises(snake_case			):
																		create_student_by_copying_alternating_layers(snake_case ,  tempfile.mkdtemp() ,  e=snake_case ,  d=snake_case			)




