



'''simple docstring'''



from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


try:
	if not (is_transformers_available() and is_torch_available()):
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
	from .notes_encoder import SpectrogramNotesEncoder
	from .continous_encoder import SpectrogramContEncoder
	from .pipeline_spectrogram_diffusion import (
	    SpectrogramContEncoder,
	    SpectrogramDiffusionPipeline,
	    TaFilmDecoder,
	)

try:
	if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
	from .midi_utils import MidiProcessor




'''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