




import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases

class 		lowercase_       (	lowerCAmelCase__				):




					def     _lowercase						(   self:		Any,     _lowercase:		int,     _lowercase:		Optional[int]=False):


									'''simple docstring'''


									__lowerCAmelCase	,				__lowerCAmelCase	,				__lowerCAmelCase					=  (
									    filename_skip_take["""filename"""],
									    filename_skip_take["""skip"""] if """skip""" in filename_skip_take else None,
									    filename_skip_take["""take"""] if """take""" in filename_skip_take else None,
									)
									open(os.path.join(_lowercase),     """wb""").close()
									__lowerCAmelCase					=  pa.Table.from_pydict({"""filename""": [Path(_lowercase).name] * 100})
									if take == -1:
													__lowerCAmelCase					=  len(_lowercase) - skip
									if skip is not None and take is not None:
													__lowerCAmelCase					=  pa_table.slice(_lowercase,     _lowercase)
									return pa_table





class 		lowercase_       (	lowerCAmelCase__				):




					def     _lowercase						(   self:		List[Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  """my_name"""
									__lowerCAmelCase					=  SplitInfo(name="""train""",     num_examples=100)
									__lowerCAmelCase					=  SplitInfo(name="""test""",     num_examples=100)
									__lowerCAmelCase					=  [train_info, test_info]
									__lowerCAmelCase					=  SplitDict()
									split_dict.add(_lowercase)
									split_dict.add(_lowercase)
									__lowerCAmelCase					=  DatasetInfo(splits=_lowercase)

									with tempfile.TemporaryDirectory() as tmp_dir:
													__lowerCAmelCase					=  ReaderTest(_lowercase,     _lowercase)

													__lowerCAmelCase					=  """test[:33%]"""
													__lowerCAmelCase					=  Dataset(**reader.read(_lowercase,     _lowercase,     _lowercase))
													self.assertEqual(dset["""filename"""][0],     f'''{name}-test''')
													self.assertEqual(dset.num_rows,     33)
													self.assertEqual(dset.num_columns,     1)

													__lowerCAmelCase					=  ["""train""", """test[:33%]"""]
													__lowerCAmelCase					=  [Split.TRAIN, ReadInstruction.from_spec("""test[:33%]""")]
													for instructions in [instructionsa, instructionsa]:
																	__lowerCAmelCase					=  [reader.read(_lowercase,     _lowercase,     _lowercase) for instr in instructions]
																	__lowerCAmelCase	,				__lowerCAmelCase					=  (Dataset(**_lowercase) for dataset_kwargs in datasets_kwargs)
																	self.assertEqual(train_dset["""filename"""][0],     f'''{name}-train''')
																	self.assertEqual(train_dset.num_rows,     100)
																	self.assertEqual(train_dset.num_columns,     1)
																	self.assertIsInstance(train_dset.split,     _lowercase)
																	self.assertEqual(str(train_dset.split),     """train""")
																	self.assertEqual(test_dset["""filename"""][0],     f'''{name}-test''')
																	self.assertEqual(test_dset.num_rows,     33)
																	self.assertEqual(test_dset.num_columns,     1)
																	self.assertIsInstance(test_dset.split,     _lowercase)
																	self.assertEqual(str(test_dset.split),     """test[:33%]""")
																	del train_dset, test_dset




					def     _lowercase						(   self:		Any):


									'''simple docstring'''


									__lowerCAmelCase					=  """my_name"""
									__lowerCAmelCase					=  SplitInfo(name="""train""",     num_examples=1000,     shard_lengths=[100] * 10)
									__lowerCAmelCase					=  [train_info]
									__lowerCAmelCase					=  SplitDict()
									split_dict.add(_lowercase)
									__lowerCAmelCase					=  DatasetInfo(splits=_lowercase)

									with tempfile.TemporaryDirectory() as tmp_dir:
													__lowerCAmelCase					=  ReaderTest(_lowercase,     _lowercase)

													__lowerCAmelCase					=  """train[:33%]"""
													__lowerCAmelCase					=  Dataset(**reader.read(_lowercase,     _lowercase,     _lowercase))
													self.assertEqual(dset["""filename"""][0],     f'''{name}-train-00000-of-00010''')
													self.assertEqual(dset["""filename"""][-1],     f'''{name}-train-00003-of-00010''')
													self.assertEqual(dset.num_rows,     330)
													self.assertEqual(dset.num_columns,     1)







					def     _lowercase						(   self:		Union[str, Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  SplitInfo(name="""train""",     num_examples=100)
									__lowerCAmelCase					=  SplitInfo(name="""test""",     num_examples=100)
									__lowerCAmelCase					=  SplitDict()
									split_dict.add(_lowercase)
									split_dict.add(_lowercase)
									__lowerCAmelCase					=  DatasetInfo(splits=_lowercase)

									with tempfile.TemporaryDirectory() as tmp_dir:
													__lowerCAmelCase					=  ReaderTest(_lowercase,     _lowercase)

													__lowerCAmelCase					=  [
													    {"""filename""": os.path.join(_lowercase,     """train""")},
													    {"""filename""": os.path.join(_lowercase,     """test"""), """skip""": 10, """take""": 10},
													]
													__lowerCAmelCase					=  Dataset(**reader.read_files(_lowercase,     original_instructions="""train+test[10:20]"""))
													self.assertEqual(dset.num_rows,     110)
													self.assertEqual(dset.num_columns,     1)
													del dset





@pytest.mark.parametrize("""in_memory"""						,			[False, True]   )
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				__lowerCAmelCase					=  arrow_file
				with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
								__lowerCAmelCase					=  ArrowReader.read_table(UpperCamelCase__						,			in_memory=UpperCamelCase__   )
				assert table.shape == dataset.data.shape
				assert set(table.column_names   ) == set(dataset.data.column_names   )
				assert dict(table.to_pydict()   ) == dict(dataset.data.to_pydict()   )  # to_pydict returns OrderedDict





@pytest.mark.parametrize("""in_memory"""						,			[False, True]   )
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				__lowerCAmelCase					=  arrow_file
				__lowerCAmelCase					=  ArrowReader(""""""						,			UpperCamelCase__   )
				with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
								__lowerCAmelCase					=  reader.read_files([{"""filename""": filename}]						,			in_memory=UpperCamelCase__   )
				assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
				__lowerCAmelCase					=  dataset_kwargs["""arrow_table"""]
				assert table.shape == dataset.data.shape
				assert set(table.column_names   ) == set(dataset.data.column_names   )
				assert dict(table.to_pydict()   ) == dict(dataset.data.to_pydict()   )  # to_pydict returns OrderedDict





def      UpperCAmelCase  (						)     ->     List[Any]:







				'''simple docstring'''


				assert ReadInstruction("""train"""						,			to=10						,			unit="""abs"""   ).to_spec() == "train[:10]"
				assert ReadInstruction("""train"""						,			from_=-80						,			to=10						,			unit="""%"""   ).to_spec() == "train[-80%:10%]"

				__lowerCAmelCase					=  """train+test"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_test

				__lowerCAmelCase					=  """train[2:10]"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_abs

				__lowerCAmelCase					=  """train[15%:-20%]"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_pct

				__lowerCAmelCase					=  """train[:10%](closest)"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == "train[:10%]"

				__lowerCAmelCase					=  """train[:10%](pct1_dropremainder)"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_pct_rounding

				__lowerCAmelCase					=  """train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_test_pct_rounding





def      UpperCAmelCase  (						)     ->     List[str]:







				'''simple docstring'''


				__lowerCAmelCase					=  """dummy"""
				__lowerCAmelCase					=  [SplitInfo(name="""train"""						,			num_examples=1_00   )]
				__lowerCAmelCase					=  """train[:33%]"""
				__lowerCAmelCase					=  """arrow"""
				__lowerCAmelCase					=  """prefix"""

				__lowerCAmelCase					=  make_file_instructions(UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )
				assert isinstance(UpperCamelCase__						,			UpperCamelCase__   )
				assert file_instructions.num_examples == 33
				assert file_instructions.file_instructions == [
				    {"filename": os.path.join(UpperCamelCase__						,			F'''{name}-train.arrow'''   ), "skip": 0, "take": 33}
				]

				__lowerCAmelCase					=  [SplitInfo(name="""train"""						,			num_examples=1_00						,			shard_lengths=[10] * 10   )]
				__lowerCAmelCase					=  make_file_instructions(UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )
				assert isinstance(UpperCamelCase__						,			UpperCamelCase__   )
				assert file_instructions.num_examples == 33
				assert file_instructions.file_instructions == [
				    {"filename": os.path.join(UpperCamelCase__						,			F'''{name}-train-00000-of-00010.arrow'''   ), "skip": 0, "take": -1},
				    {"filename": os.path.join(UpperCamelCase__						,			F'''{name}-train-00001-of-00010.arrow'''   ), "skip": 0, "take": -1},
				    {"filename": os.path.join(UpperCamelCase__						,			F'''{name}-train-00002-of-00010.arrow'''   ), "skip": 0, "take": -1},
				    {"filename": os.path.join(UpperCamelCase__						,			F'''{name}-train-00003-of-00010.arrow'''   ), "skip": 0, "take": 3},
				]





@pytest.mark.parametrize("""name, expected_exception"""						,			[(None, TypeError), ("""""", ValueError)]   )
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				__lowerCAmelCase					=  [SplitInfo(name="""train"""						,			num_examples=1_00   )]
				__lowerCAmelCase					=  """train"""
				__lowerCAmelCase					=  """arrow"""
				__lowerCAmelCase					=  """prefix_path"""
				with pytest.raises(UpperCamelCase__   ):
								__lowerCAmelCase					=  make_file_instructions(UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )









import numpy as np  # noqa: E402

from ...configuration_utils import ConfigMixin, register_to_config
from ...schedulers.scheduling_utils import SchedulerMixin


try:
  import librosa  # noqa: E402

  __UpperCAmelCase			:			Union[str, Any]			      =					True
  __UpperCAmelCase			:			Optional[int]			      =					""
except Exception as e:
  __UpperCAmelCase			:			Union[str, Any]			      =					False
  __UpperCAmelCase			:			Tuple			      =					(
      f'''Cannot import librosa because {e}. Make sure to correctly install librosa to be able to install it.'''
  )


from PIL import Image  # noqa: E402



class  UpperCAmelCase_						(				_a,  _a):
       '''simple docstring'''
       __UpperCamelCase   :  Tuple				=       "mel_config.json"






       @register_to_config
       def __init__(  self			,       __SCREAMING_SNAKE_CASE = 256			,       __SCREAMING_SNAKE_CASE = 256			,       __SCREAMING_SNAKE_CASE = 22_050			,       __SCREAMING_SNAKE_CASE = 2_048			,       __SCREAMING_SNAKE_CASE = 512			,       __SCREAMING_SNAKE_CASE = 80			,       __SCREAMING_SNAKE_CASE = 32			,       ):




              """simple docstring"""




              UpperCamelCase     :						Union[str, Any] 						=		hop_length
              UpperCamelCase     :						List[str] 						=		sample_rate
              UpperCamelCase     :						List[Any] 						=		n_fft
              UpperCamelCase     :						List[str] 						=		top_db
              UpperCamelCase     :						Tuple 						=		n_iter
              self.set_resolution(__SCREAMING_SNAKE_CASE			,       __SCREAMING_SNAKE_CASE    )
              UpperCamelCase     :						Any 						=		None

              if not _librosa_can_be_imported:
                     raise ValueError(_import_error    )






       def 			_lowercase (  self			,       __SCREAMING_SNAKE_CASE			,       __SCREAMING_SNAKE_CASE    ):




              """simple docstring"""




              UpperCamelCase     :						Any 						=		x_res
              UpperCamelCase     :						Union[str, Any] 						=		y_res
              UpperCamelCase     :						Any 						=		self.y_res
              UpperCamelCase     :						Union[str, Any] 						=		self.x_res * self.hop_length - 1






       def 			_lowercase (  self			,       __SCREAMING_SNAKE_CASE = None			,       __SCREAMING_SNAKE_CASE = None    ):




              """simple docstring"""




              if audio_file is not None:
                     UpperCamelCase						,			UpperCamelCase     :						Tuple 						=		librosa.load(__SCREAMING_SNAKE_CASE			,       mono=__SCREAMING_SNAKE_CASE			,       sr=self.sr    )
              else:
                     UpperCamelCase     :						Tuple 						=		raw_audio

              # Pad with silence if necessary.
              if len(self.audio    ) < self.x_res * self.hop_length:
                     UpperCamelCase     :						List[str] 						=		np.concatenate([self.audio, np.zeros((self.x_res * self.hop_length - len(self.audio    ),)    )]    )






       def 			_lowercase (  self    ):




              """simple docstring"""




              return len(self.audio    ) // self.slice_size






       def 			_lowercase (  self			,       __SCREAMING_SNAKE_CASE = 0    ):




              """simple docstring"""




              return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]






       def 			_lowercase (  self    ):




              """simple docstring"""




              return self.sr






       def 			_lowercase (  self			,       __SCREAMING_SNAKE_CASE    ):




              """simple docstring"""




              UpperCamelCase     :						List[str] 						=		librosa.feature.melspectrogram(
                  y=self.get_audio_slice(__SCREAMING_SNAKE_CASE    )			,       sr=self.sr			,       n_fft=self.n_fft			,       hop_length=self.hop_length			,       n_mels=self.n_mels    )
              UpperCamelCase     :						Optional[int] 						=		librosa.power_to_db(__SCREAMING_SNAKE_CASE			,       ref=np.max			,       top_db=self.top_db    )
              UpperCamelCase     :						Optional[int] 						=		(((log_S + self.top_db) * 255 / self.top_db).clip(0			,       255    ) + 0.5).astype(np.uinta    )
              UpperCamelCase     :						List[Any] 						=		Image.fromarray(__SCREAMING_SNAKE_CASE    )
              return image






       def 			_lowercase (  self			,       __SCREAMING_SNAKE_CASE    ):




              """simple docstring"""




              UpperCamelCase     :						int 						=		np.frombuffer(image.tobytes()			,       dtype='''uint8'''    ).reshape((image.height, image.width)    )
              UpperCamelCase     :						Tuple 						=		bytedata.astype('''float'''    ) * self.top_db / 255 - self.top_db
              UpperCamelCase     :						List[Any] 						=		librosa.db_to_power(__SCREAMING_SNAKE_CASE    )
              UpperCamelCase     :						Optional[int] 						=		librosa.feature.inverse.mel_to_audio(
                  __SCREAMING_SNAKE_CASE			,       sr=self.sr			,       n_fft=self.n_fft			,       hop_length=self.hop_length			,       n_iter=self.n_iter    )
              return audio

