





"""simple docstring"""


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

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


__magic_name__       :					Dict						=			logging.getLogger(__name__)






class 							lowercase__			(   __SCREAMING_SNAKE_CASE	):

			"""simple docstring"""







			def __init__(      self						,   _A=-1    ):






									'''simple docstring'''







									UpperCamelCase				:		List[str]				   =			label_idx







			def   _a      (      self						,   _A						,   _A    ):






									'''simple docstring'''







									if isinstance(_A						,   _A    ):
															UpperCamelCase				:		Tuple				   =			mode.value
									UpperCamelCase				:		int				   =			os.path.join(_A						,   f"""{mode}.txt"""    )
									UpperCamelCase				:		List[Any]				   =			1
									UpperCamelCase				:		str				   =			[]
									with open(_A						,   encoding="""utf-8"""    ) as f:
															UpperCamelCase				:		Any				   =			[]
															UpperCamelCase				:		Dict				   =			[]
															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				:		int				   =			[]
																																	UpperCamelCase				:		Union[str, Any]				   =			[]
																					else:
																											UpperCamelCase				:		Any				   =			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   _a      (      self						,   _A						,   _A						,   _A    ):






									'''simple docstring'''







									UpperCamelCase				:		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]:
																					UpperCamelCase				:		str				   =			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   _a      (      self						,   _A    ):






									'''simple docstring'''







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






class 							lowercase__			(   __SCREAMING_SNAKE_CASE	):

			"""simple docstring"""







			def __init__(      self    ):






									'''simple docstring'''







									super().__init__(label_idx=-2    )







			def   _a      (      self						,   _A    ):






									'''simple docstring'''







									if path:
															with open(_A						,   """r"""    ) as f:
																					UpperCamelCase				:		str				   =			f.read().splitlines()
															if "O" not in labels:
																					UpperCamelCase				:		List[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 							lowercase__			(   __SCREAMING_SNAKE_CASE	):

			"""simple docstring"""







			def   _a      (      self						,   _A						,   _A    ):






									'''simple docstring'''







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

									with open(_A						,   encoding="""utf-8"""    ) as f:
															for sentence in parse_incr(_A    ):
																					UpperCamelCase				:		List[Any]				   =			[]
																					UpperCamelCase				:		Union[str, Any]				   =			[]
																					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   _a      (      self						,   _A						,   _A						,   _A    ):






									'''simple docstring'''







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







			def   _a      (      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",
															]










"""simple docstring"""


import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						assert isinstance(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						assert dataset.num_rows == 4
						assert dataset.num_columns == 3
						assert dataset.column_names == ["col_1", "col_2", "col_3"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize("""keep_in_memory"""							,     [False, True]     )
def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		Tuple				   =			tmp_path / """cache"""
						UpperCamelCase				:		Optional[int]				   =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												UpperCamelCase				:		Tuple				   =			JsonDatasetReader(SCREAMING_SNAKE_CASE							,     cache_dir=SCREAMING_SNAKE_CASE							,     keep_in_memory=SCREAMING_SNAKE_CASE     ).read()
						_check_json_dataset(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

@pytest.mark.parametrize(
    """features"""							,     [
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]							,     )
def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		Optional[Any]				   =			tmp_path / """cache"""
						UpperCamelCase				:		int				   =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						UpperCamelCase				:		Union[str, Any]				   =			features.copy() if features else default_expected_features
						UpperCamelCase				:		str				   =			(
						    Features({feature: Value(SCREAMING_SNAKE_CASE     ) for feature, dtype in features.items()}     ) if features is not None else None
						)
						UpperCamelCase				:		Optional[int]				   =			JsonDatasetReader(SCREAMING_SNAKE_CASE							,     features=SCREAMING_SNAKE_CASE							,     cache_dir=SCREAMING_SNAKE_CASE     ).read()
						_check_json_dataset(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

@pytest.mark.parametrize(
    """features"""							,     [
        None,
        {"""col_3""": """float64""", """col_1""": """string""", """col_2""": """int64"""},
    ]							,     )
def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		int				   =			tmp_path / """cache"""
						UpperCamelCase				:		Optional[int]				   =			{"""col_3""": """float64""", """col_1""": """string""", """col_2""": """int64"""}
						UpperCamelCase				:		Optional[Any]				   =			features.copy() if features else default_expected_features
						UpperCamelCase				:		Tuple				   =			(
						    Features({feature: Value(SCREAMING_SNAKE_CASE     ) for feature, dtype in features.items()}     ) if features is not None else None
						)
						UpperCamelCase				:		int				   =			JsonDatasetReader(SCREAMING_SNAKE_CASE							,     features=SCREAMING_SNAKE_CASE							,     cache_dir=SCREAMING_SNAKE_CASE     ).read()
						assert isinstance(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						assert dataset.num_rows == 2
						assert dataset.num_columns == 3
						assert dataset.column_names == ["col_3", "col_1", "col_2"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						# jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
						UpperCamelCase				:		str				   =			{"""col_2""": """int64""", """col_3""": """float64""", """col_1""": """string"""}
						UpperCamelCase				:		Tuple				   =			features.copy()
						UpperCamelCase				:		Tuple				   =			(
						    Features({feature: Value(SCREAMING_SNAKE_CASE     ) for feature, dtype in features.items()}     ) if features is not None else None
						)
						UpperCamelCase				:		Optional[int]				   =			tmp_path / """cache"""
						UpperCamelCase				:		List[Any]				   =			JsonDatasetReader(SCREAMING_SNAKE_CASE							,     features=SCREAMING_SNAKE_CASE							,     cache_dir=SCREAMING_SNAKE_CASE     ).read()
						assert isinstance(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						assert dataset.num_rows == 2
						assert dataset.num_columns == 3
						assert dataset.column_names == ["col_2", "col_3", "col_1"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize("""split"""							,     [None, NamedSplit("""train"""     ), """train""", """test"""]     )
def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		Optional[int]				   =			tmp_path / """cache"""
						UpperCamelCase				:		Any				   =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						UpperCamelCase				:		Dict				   =			JsonDatasetReader(SCREAMING_SNAKE_CASE							,     cache_dir=SCREAMING_SNAKE_CASE							,     split=SCREAMING_SNAKE_CASE     ).read()
						_check_json_dataset(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						assert dataset.split == split if split else "train"

@pytest.mark.parametrize("""path_type"""							,     [str, list]     )
def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						if issubclass(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
												UpperCamelCase				:		List[str]				   =			jsonl_path
						elif issubclass(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
												UpperCamelCase				:		List[str]				   =			[jsonl_path]
						UpperCamelCase				:		List[Any]				   =			tmp_path / """cache"""
						UpperCamelCase				:		List[Any]				   =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						UpperCamelCase				:		Optional[int]				   =			JsonDatasetReader(SCREAMING_SNAKE_CASE							,     cache_dir=SCREAMING_SNAKE_CASE     ).read()
						_check_json_dataset(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE=("train",)     ):
						assert isinstance(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						for split in splits:
												UpperCamelCase				:		Optional[Any]				   =			dataset_dict[split]
												assert dataset.num_rows == 4
												assert dataset.num_columns == 3
												assert dataset.column_names == ["col_1", "col_2", "col_3"]
												for feature, expected_dtype in expected_features.items():
																		assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize("""keep_in_memory"""							,     [False, True]     )
def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		int				   =			tmp_path / """cache"""
						UpperCamelCase				:		int				   =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												UpperCamelCase				:		Any				   =			JsonDatasetReader({"""train""": jsonl_path}							,     cache_dir=SCREAMING_SNAKE_CASE							,     keep_in_memory=SCREAMING_SNAKE_CASE     ).read()
						_check_json_datasetdict(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

@pytest.mark.parametrize(
    """features"""							,     [
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]							,     )
def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		List[str]				   =			tmp_path / """cache"""
						UpperCamelCase				:		Optional[Any]				   =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						UpperCamelCase				:		Optional[Any]				   =			features.copy() if features else default_expected_features
						UpperCamelCase				:		Optional[Any]				   =			(
						    Features({feature: Value(SCREAMING_SNAKE_CASE     ) for feature, dtype in features.items()}     ) if features is not None else None
						)
						UpperCamelCase				:		Optional[Any]				   =			JsonDatasetReader({"""train""": jsonl_path}							,     features=SCREAMING_SNAKE_CASE							,     cache_dir=SCREAMING_SNAKE_CASE     ).read()
						_check_json_datasetdict(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

@pytest.mark.parametrize("""split"""							,     [None, NamedSplit("""train"""     ), """train""", """test"""]     )
def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						if split:
												UpperCamelCase				:		List[Any]				   =			{split: jsonl_path}
						else:
												UpperCamelCase				:		Tuple				   =			"""train"""
												UpperCamelCase				:		Union[str, Any]				   =			{"""train""": jsonl_path, """test""": jsonl_path}
						UpperCamelCase				:		Optional[Any]				   =			tmp_path / """cache"""
						UpperCamelCase				:		Optional[int]				   =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						UpperCamelCase				:		Union[str, Any]				   =			JsonDatasetReader(SCREAMING_SNAKE_CASE							,     cache_dir=SCREAMING_SNAKE_CASE     ).read()
						_check_json_datasetdict(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     splits=list(path.keys()     )     )
						assert all(dataset[split].split == split for split in path.keys()     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						return json.load(SCREAMING_SNAKE_CASE     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						return [json.loads(SCREAMING_SNAKE_CASE     ) for line in buffer]






class 							lowercase__			:

			"""simple docstring"""







			@pytest.mark.parametrize("""lines, load_json_function"""						,   [(True, load_json_lines), (False, load_json)]    )
			def   _a      (      self						,   _A						,   _A						,   _A    ):






									'''simple docstring'''







									with io.BytesIO() as buffer:
															JsonDatasetWriter(_A						,   _A						,   lines=_A    ).write()
															buffer.seek(0    )
															UpperCamelCase				:		Optional[Any]				   =			load_json_function(_A    )
									assert isinstance(_A						,   _A    )
									assert isinstance(exported_content[0]						,   _A    )
									assert len(_A    ) == 1_0







			@pytest.mark.parametrize(
			    """orient, container, keys, len_at"""						,   [
			        ("""records""", list, {"""tokens""", """labels""", """answers""", """id"""}, None),
			        ("""split""", dict, {"""columns""", """data"""}, """data"""),
			        ("""index""", dict, set("""0123456789"""    ), None),
			        ("""columns""", dict, {"""tokens""", """labels""", """answers""", """id"""}, """tokens"""),
			        ("""values""", list, None, None),
			        ("""table""", dict, {"""schema""", """data"""}, """data"""),
			    ]						,   )
			def   _a      (      self						,   _A						,   _A						,   _A						,   _A						,   _A    ):






									'''simple docstring'''







									with io.BytesIO() as buffer:
															JsonDatasetWriter(_A						,   _A						,   lines=_A						,   orient=_A    ).write()
															buffer.seek(0    )
															UpperCamelCase				:		str				   =			load_json(_A    )
									assert isinstance(_A						,   _A    )
									if keys:
															if container is dict:
																					assert exported_content.keys() == keys
															else:
																					assert exported_content[0].keys() == keys
									else:
															assert not hasattr(_A						,   """keys"""    ) and not hasattr(exported_content[0]						,   """keys"""    )
									if len_at:
															assert len(exported_content[len_at]    ) == 1_0
									else:
															assert len(_A    ) == 1_0







			@pytest.mark.parametrize("""lines, load_json_function"""						,   [(True, load_json_lines), (False, load_json)]    )
			def   _a      (      self						,   _A						,   _A						,   _A    ):






									'''simple docstring'''







									with io.BytesIO() as buffer:
															JsonDatasetWriter(_A						,   _A						,   lines=_A						,   num_proc=2    ).write()
															buffer.seek(0    )
															UpperCamelCase				:		List[Any]				   =			load_json_function(_A    )
									assert isinstance(_A						,   _A    )
									assert isinstance(exported_content[0]						,   _A    )
									assert len(_A    ) == 1_0







			@pytest.mark.parametrize(
			    """orient, container, keys, len_at"""						,   [
			        ("""records""", list, {"""tokens""", """labels""", """answers""", """id"""}, None),
			        ("""split""", dict, {"""columns""", """data"""}, """data"""),
			        ("""index""", dict, set("""0123456789"""    ), None),
			        ("""columns""", dict, {"""tokens""", """labels""", """answers""", """id"""}, """tokens"""),
			        ("""values""", list, None, None),
			        ("""table""", dict, {"""schema""", """data"""}, """data"""),
			    ]						,   )
			def   _a      (      self						,   _A						,   _A						,   _A						,   _A						,   _A    ):






									'''simple docstring'''







									with io.BytesIO() as buffer:
															JsonDatasetWriter(_A						,   _A						,   lines=_A						,   orient=_A						,   num_proc=2    ).write()
															buffer.seek(0    )
															UpperCamelCase				:		Dict				   =			load_json(_A    )
									assert isinstance(_A						,   _A    )
									if keys:
															if container is dict:
																					assert exported_content.keys() == keys
															else:
																					assert exported_content[0].keys() == keys
									else:
															assert not hasattr(_A						,   """keys"""    ) and not hasattr(exported_content[0]						,   """keys"""    )
									if len_at:
															assert len(exported_content[len_at]    ) == 1_0
									else:
															assert len(_A    ) == 1_0







			def   _a      (      self						,   _A    ):






									'''simple docstring'''







									with pytest.raises(_A    ):
															with io.BytesIO() as buffer:
																					JsonDatasetWriter(_A						,   _A						,   num_proc=0    )







			@pytest.mark.parametrize("""compression, extension"""						,   [("""gzip""", """gz"""), ("""bz2""", """bz2"""), ("""xz""", """xz""")]    )
			def   _a      (      self						,   _A						,   _A						,   _A						,   _A						,   _A    ):






									'''simple docstring'''







									UpperCamelCase				:		List[str]				   =			tmp_path_factory.mktemp("""data"""    ) / f"""test.json.{extension}"""
									UpperCamelCase				:		Tuple				   =			str(shared_datadir / f"""test_file.json.{extension}"""    )
									JsonDatasetWriter(_A						,   _A						,   compression=_A    ).write()

									with fsspec.open(_A						,   """rb"""						,   compression="""infer"""    ) as f:
															UpperCamelCase				:		Dict				   =			f.read()
									with fsspec.open(_A						,   """rb"""						,   compression="""infer"""    ) as f:
															UpperCamelCase				:		Tuple				   =			f.read()
									assert exported_content == original_content



