



'''simple docstring'''



# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch

from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool






class 					UpperCAmelCase__	(		UpperCamelCase__ ):
					a      :     List[Any]        =							"""facebook/bart-large-mnli"""
					a      :     str        =							(
					    """This is a tool that classifies an English text using provided labels. It takes two inputs: `text`, which """
					    """should be the text to classify, and `labels`, which should be the list of labels to use for classification. """
					    """It returns the most likely label in the list of provided `labels` for the input text."""
					)
					a      :     int        =							"""text_classifier"""
					a      :     int        =							AutoTokenizer
					a      :     Tuple        =							AutoModelForSequenceClassification

					a      :     str        =							["""text""", ["""text"""]]
					a      :     Union[str, Any]        =							["""text"""]



					def        UpperCAmelCase_ (    self     )     ->			str:
						super().setup()
						__lowerCAmelCase												=  self.model.config
						__lowerCAmelCase												=  -1
						for idx, label in config.idalabel.items():
							if label.lower().startswith("entail"     ):
								__lowerCAmelCase												=  int(UpperCamelCase     )
						if self.entailment_id == -1:
							raise ValueError("Could not determine the entailment ID from the model config, please pass it at init."     )



					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase     )     ->			Optional[Any]:
						__lowerCAmelCase												=  labels
						return self.pre_processor(
						    [text] * len(UpperCamelCase     )			,				[F'''This example is {label}''' for label in labels]			,				return_tensors="pt"			,				padding="max_length"			,				)



					def        UpperCAmelCase_ (    self			,				UpperCamelCase     )     ->			List[str]:
						__lowerCAmelCase												=  outputs.logits
						__lowerCAmelCase												=  torch.argmax(logits[:, 2]     ).item()
						return self._labels[label_id]




'''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   __lowerCAmelCase					(							lowerCamelCase   :						str				,		lowerCamelCase   :						Union[str, Any]					):






	'''simple docstring'''




	assert isinstance(lowerCamelCase				,		lowerCamelCase					)
	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   __lowerCAmelCase					(							lowerCamelCase   :						Tuple				,		lowerCamelCase   :						int				,		lowerCamelCase   :						Optional[int]					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		cache_dir=lowerCamelCase				,		keep_in_memory=lowerCamelCase					).read()
	_check_json_dataset(lowerCamelCase				,		lowerCamelCase					)



@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   __lowerCAmelCase					(							lowerCamelCase   :						List[Any]				,		lowerCamelCase   :						int				,		lowerCamelCase   :						Dict					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  features.copy() if features else default_expected_features
	__lowerCAmelCase												=  (
	    Features({feature: Value(lowerCamelCase					) for feature, dtype in features.items()}					) if features is not None else None
	)
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		features=lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	_check_json_dataset(lowerCamelCase				,		lowerCamelCase					)



@pytest.mark.parametrize(
    "features"				,		[
        None,
        {"col_3": "float64", "col_1": "string", "col_2": "int64"},
    ]				,		)
def   __lowerCAmelCase					(							lowerCamelCase   :						List[Any]				,		lowerCamelCase   :						Optional[int]				,		lowerCamelCase   :						Any					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_3": "float64", "col_1": "string", "col_2": "int64"}
	__lowerCAmelCase												=  features.copy() if features else default_expected_features
	__lowerCAmelCase												=  (
	    Features({feature: Value(lowerCamelCase					) for feature, dtype in features.items()}					) if features is not None else None
	)
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		features=lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	assert isinstance(lowerCamelCase				,		lowerCamelCase					)
	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   __lowerCAmelCase					(							lowerCamelCase   :						Any				,		lowerCamelCase   :						Optional[int]					):






	'''simple docstring'''




	__lowerCAmelCase												=  {"col_2": "int64", "col_3": "float64", "col_1": "string"}
	__lowerCAmelCase												=  features.copy()
	__lowerCAmelCase												=  (
	    Features({feature: Value(lowerCamelCase					) for feature, dtype in features.items()}					) if features is not None else None
	)
	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		features=lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	assert isinstance(lowerCamelCase				,		lowerCamelCase					)
	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   __lowerCAmelCase					(							lowerCamelCase   :						List[Any]				,		lowerCamelCase   :						Optional[Any]				,		lowerCamelCase   :						Union[str, Any]					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		cache_dir=lowerCamelCase				,		split=lowerCamelCase					).read()
	_check_json_dataset(lowerCamelCase				,		lowerCamelCase					)
	assert dataset.split == split if split else "train"



@pytest.mark.parametrize("path_type"				,		[str, list]					)
def   __lowerCAmelCase					(							lowerCamelCase   :						Any				,		lowerCamelCase   :						List[str]				,		lowerCamelCase   :						Optional[int]					):






	'''simple docstring'''




	if issubclass(lowerCamelCase				,		lowerCamelCase					):
		__lowerCAmelCase												=  jsonl_path
	elif issubclass(lowerCamelCase				,		lowerCamelCase					):
		__lowerCAmelCase												=  [jsonl_path]
	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	_check_json_dataset(lowerCamelCase				,		lowerCamelCase					)



def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[int]				,		lowerCamelCase   :						int				,		lowerCamelCase   :						str=("train",)					):






	'''simple docstring'''




	assert isinstance(lowerCamelCase				,		lowerCamelCase					)
	for split in splits:
		__lowerCAmelCase												=  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   __lowerCAmelCase					(							lowerCamelCase   :						Dict				,		lowerCamelCase   :						int				,		lowerCamelCase   :						List[str]					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		__lowerCAmelCase												=  JsonDatasetReader({"train": jsonl_path}				,		cache_dir=lowerCamelCase				,		keep_in_memory=lowerCamelCase					).read()
	_check_json_datasetdict(lowerCamelCase				,		lowerCamelCase					)



@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   __lowerCAmelCase					(							lowerCamelCase   :						int				,		lowerCamelCase   :						Any				,		lowerCamelCase   :						Dict					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  features.copy() if features else default_expected_features
	__lowerCAmelCase												=  (
	    Features({feature: Value(lowerCamelCase					) for feature, dtype in features.items()}					) if features is not None else None
	)
	__lowerCAmelCase												=  JsonDatasetReader({"train": jsonl_path}				,		features=lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	_check_json_datasetdict(lowerCamelCase				,		lowerCamelCase					)



@pytest.mark.parametrize("split"				,		[None, NamedSplit("train"					), "train", "test"]					)
def   __lowerCAmelCase					(							lowerCamelCase   :						int				,		lowerCamelCase   :						Optional[int]				,		lowerCamelCase   :						int					):






	'''simple docstring'''




	if split:
		__lowerCAmelCase												=  {split: jsonl_path}
	else:
		__lowerCAmelCase												=  "train"
		__lowerCAmelCase												=  {"train": jsonl_path, "test": jsonl_path}
	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	_check_json_datasetdict(lowerCamelCase				,		lowerCamelCase				,		splits=list(path.keys()					)					)
	assert all(dataset[split].split == split for split in path.keys()					)



def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[Any]					):






	'''simple docstring'''




	return json.load(lowerCamelCase					)



def   __lowerCAmelCase					(							lowerCamelCase   :						Tuple					):






	'''simple docstring'''




	return [json.loads(lowerCamelCase					) for line in buffer]






class 					UpperCAmelCase__	:



					@pytest.mark.parametrize("lines, load_json_function"			,				[(True, load_json_lines), (False, load_json)]     )
					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			int:
						with io.BytesIO() as buffer:
							JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				lines=UpperCamelCase     ).write()
							buffer.seek(0     )
							__lowerCAmelCase												=  load_json_function(UpperCamelCase     )
						assert isinstance(UpperCamelCase			,				UpperCamelCase     )
						assert isinstance(exported_content[0]			,				UpperCamelCase     )
						assert len(UpperCamelCase     ) == 10



					@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        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			int:
						with io.BytesIO() as buffer:
							JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				lines=UpperCamelCase			,				orient=UpperCamelCase     ).write()
							buffer.seek(0     )
							__lowerCAmelCase												=  load_json(UpperCamelCase     )
						assert isinstance(UpperCamelCase			,				UpperCamelCase     )
						if keys:
							if container is dict:
								assert exported_content.keys() == keys
							else:
								assert exported_content[0].keys() == keys
						else:
							assert not hasattr(UpperCamelCase			,				"keys"     ) and not hasattr(exported_content[0]			,				"keys"     )
						if len_at:
							assert len(exported_content[len_at]     ) == 10
						else:
							assert len(UpperCamelCase     ) == 10



					@pytest.mark.parametrize("lines, load_json_function"			,				[(True, load_json_lines), (False, load_json)]     )
					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			str:
						with io.BytesIO() as buffer:
							JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				lines=UpperCamelCase			,				num_proc=2     ).write()
							buffer.seek(0     )
							__lowerCAmelCase												=  load_json_function(UpperCamelCase     )
						assert isinstance(UpperCamelCase			,				UpperCamelCase     )
						assert isinstance(exported_content[0]			,				UpperCamelCase     )
						assert len(UpperCamelCase     ) == 10



					@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        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			Union[str, Any]:
						with io.BytesIO() as buffer:
							JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				lines=UpperCamelCase			,				orient=UpperCamelCase			,				num_proc=2     ).write()
							buffer.seek(0     )
							__lowerCAmelCase												=  load_json(UpperCamelCase     )
						assert isinstance(UpperCamelCase			,				UpperCamelCase     )
						if keys:
							if container is dict:
								assert exported_content.keys() == keys
							else:
								assert exported_content[0].keys() == keys
						else:
							assert not hasattr(UpperCamelCase			,				"keys"     ) and not hasattr(exported_content[0]			,				"keys"     )
						if len_at:
							assert len(exported_content[len_at]     ) == 10
						else:
							assert len(UpperCamelCase     ) == 10



					def        UpperCAmelCase_ (    self			,				UpperCamelCase     )     ->			Any:
						with pytest.raises(UpperCamelCase     ):
							with io.BytesIO() as buffer:
								JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				num_proc=0     )



					@pytest.mark.parametrize("compression, extension"			,				[("gzip", "gz"), ("bz2", "bz2"), ("xz", "xz")]     )
					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			Tuple:
						__lowerCAmelCase												=  tmp_path_factory.mktemp("data"     ) / F'''test.json.{extension}'''
						__lowerCAmelCase												=  str(shared_datadir / F'''test_file.json.{extension}'''     )
						JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				compression=UpperCamelCase     ).write()

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