
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   (							lowerCAmelCase__			,      lowerCAmelCase__		):
					'''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 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										lowercase						     =						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 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					lowercase						     =						features.copy() if features else default_expected_features
					lowercase						     =						(
					    Features({feature: Value(lowerCAmelCase__		) for feature, dtype in features.items()}		) if features is not None else None
					)
					lowercase						     =						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 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						{'''col_3''': '''float64''', '''col_1''': '''string''', '''col_2''': '''int64'''}
					lowercase						     =						features.copy() if features else default_expected_features
					lowercase						     =						(
					    Features({feature: Value(lowerCAmelCase__		) for feature, dtype in features.items()}		) if features is not None else None
					)
					lowercase						     =						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 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					# jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
					lowercase						     =						{'''col_2''': '''int64''', '''col_3''': '''float64''', '''col_1''': '''string'''}
					lowercase						     =						features.copy()
					lowercase						     =						(
					    Features({feature: Value(lowerCAmelCase__		) for feature, dtype in features.items()}		) if features is not None else None
					)
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						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 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					lowercase						     =						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 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					if issubclass(lowerCAmelCase__			,      lowerCAmelCase__		):
										lowercase						     =						jsonl_path
					elif issubclass(lowerCAmelCase__			,      lowerCAmelCase__		):
										lowercase						     =						[jsonl_path]
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					lowercase						     =						JsonDatasetReader(lowerCAmelCase__			,      cache_dir=lowerCAmelCase__		).read()
					_check_json_dataset(lowerCAmelCase__			,      lowerCAmelCase__		)



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__=("train",)		):
					'''simple docstring'''
					assert isinstance(lowerCAmelCase__			,      lowerCAmelCase__		)
					for split in splits:
										lowercase						     =						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   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										lowercase						     =						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 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					lowercase						     =						features.copy() if features else default_expected_features
					lowercase						     =						(
					    Features({feature: Value(lowerCAmelCase__		) for feature, dtype in features.items()}		) if features is not None else None
					)
					lowercase						     =						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 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					if split:
										lowercase						     =						{split: jsonl_path}
					else:
										lowercase						     =						'''train'''
										lowercase						     =						{'''train''': jsonl_path, '''test''': jsonl_path}
					lowercase						     =						tmp_path / '''cache'''
					lowercase						     =						{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					lowercase						     =						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 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					return json.load(lowerCAmelCase__		)



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					return [json.loads(lowerCAmelCase__		) for line in buffer]







class     lowercase		:




							@pytest.mark.parametrize('''lines, load_json_function'''       ,[(True, load_json_lines), (False, load_json)])
							def 			A__				(    self       ,A__       ,A__       ,A__):
												with io.BytesIO() as buffer:
																	JsonDatasetWriter(A__       ,A__       ,lines=A__).write()
																	buffer.seek(0)
																	lowercase						     =						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__):
												with io.BytesIO() as buffer:
																	JsonDatasetWriter(A__       ,A__       ,lines=A__       ,orient=A__).write()
																	buffer.seek(0)
																	lowercase						     =						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__):
												with io.BytesIO() as buffer:
																	JsonDatasetWriter(A__       ,A__       ,lines=A__       ,num_proc=2).write()
																	buffer.seek(0)
																	lowercase						     =						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__):
												with io.BytesIO() as buffer:
																	JsonDatasetWriter(A__       ,A__       ,lines=A__       ,orient=A__       ,num_proc=2).write()
																	buffer.seek(0)
																	lowercase						     =						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__):
												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__):
												lowercase						     =						tmp_path_factory.mktemp('''data''') / f'test.json.{extension}'
												lowercase						     =						str(shared_datadir / f'test_file.json.{extension}')
												JsonDatasetWriter(A__       ,A__       ,compression=A__).write()

												with fsspec.open(A__       ,'''rb'''       ,compression='''infer''') as f:
																	lowercase						     =						f.read()
												with fsspec.open(A__       ,'''rb'''       ,compression='''infer''') as f:
																	lowercase						     =						f.read()
												assert exported_content == original_content






from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


lowercase__		:Union[str, Any]			  =   {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"]}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:List[Any]			  =   ["DPTFeatureExtractor"]
							lowercase__		:List[Any]			  =   ["DPTImageProcessor"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Optional[int]			  =   [
							    "DPT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "DPTForDepthEstimation",
							    "DPTForSemanticSegmentation",
							    "DPTModel",
							    "DPTPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_dpt import DPTFeatureExtractor
														from .image_processing_dpt import DPTImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_dpt import (
														    DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DPTForDepthEstimation,
														    DPTForSemanticSegmentation,
														    DPTModel,
														    DPTPreTrainedModel,
														)


else:
							import sys

							lowercase__		:List[Any]			  =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




