





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase			:			Optional[Any]	  = {
    """configuration_musicgen""": [
        """MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MusicgenConfig""",
        """MusicgenDecoderConfig""",
    ],
    """processing_musicgen""": ["""MusicgenProcessor"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase			:			Optional[Any]	  = [
         """MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """MusicgenForConditionalGeneration""",
         """MusicgenForCausalLM""",
         """MusicgenModel""",
         """MusicgenPreTrainedModel""",
     ]

if TYPE_CHECKING:
     from .configuration_musicgen import (
         MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP,
         MusicgenConfig,
         MusicgenDecoderConfig,
     )
     from .processing_musicgen import MusicgenProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_musicgen import (
              MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
              MusicgenForCausalLM,
              MusicgenForConditionalGeneration,
              MusicgenModel,
              MusicgenPreTrainedModel,
          )

else:
     import sys

     UpperCAmelCase			:			Optional[int]	  = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)













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        __lowerCAmelCase (					UpperCamelCase__):







      def      _lowercase						(					self	,   lowerCAmelCase__	,   lowerCAmelCase__=False							)     ->		List[Any]:



        '''simple docstring'''




        a__      ,							a__      ,							a__			:      Optional[int]            =(
            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(lowerCAmelCase__							)	,   "wb"							).close()
        a__			:      Optional[int]            =pa.Table.from_pydict({"filename": [Path(lowerCAmelCase__							).name] * 1_0_0}							)
        if take == -1:
          a__			:      int            =len(lowerCAmelCase__							) - skip
        if skip is not None and take is not None:
          a__			:      Optional[Any]            =pa_table.slice(lowerCAmelCase__	,   lowerCAmelCase__							)
        return pa_table







class        __lowerCAmelCase (					UpperCamelCase__):







      def      _lowercase						(					self							)     ->		str:



        '''simple docstring'''




        a__			:      List[str]            ="my_name"
        a__			:      List[Any]            =SplitInfo(name="train"	,   num_examples=1_0_0							)
        a__			:      List[str]            =SplitInfo(name="test"	,   num_examples=1_0_0							)
        a__			:      List[Any]            =[train_info, test_info]
        a__			:      Union[str, Any]            =SplitDict()
        split_dict.add(lowerCAmelCase__							)
        split_dict.add(lowerCAmelCase__							)
        a__			:      Dict            =DatasetInfo(splits=lowerCAmelCase__							)

        with tempfile.TemporaryDirectory() as tmp_dir:
          a__			:      Optional[Any]            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)

          a__			:      Any            ="test[:33%]"
          a__			:      int            =Dataset(**reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							)							)
          self.assertEqual(dset["filename"][0]	,   F'''{name}-test'''							)
          self.assertEqual(dset.num_rows	,   3_3							)
          self.assertEqual(dset.num_columns	,   1							)

          a__			:      Tuple            =["train", "test[:33%]"]
          a__			:      str            =[Split.TRAIN, ReadInstruction.from_spec("test[:33%]"							)]
          for instructions in [instructionsa, instructionsa]:
            a__			:      Optional[int]            =[reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							) for instr in instructions]
            a__      ,							a__			:      Optional[int]            =(Dataset(**lowerCAmelCase__							) for dataset_kwargs in datasets_kwargs)
            self.assertEqual(train_dset["filename"][0]	,   F'''{name}-train'''							)
            self.assertEqual(train_dset.num_rows	,   1_0_0							)
            self.assertEqual(train_dset.num_columns	,   1							)
            self.assertIsInstance(train_dset.split	,   lowerCAmelCase__							)
            self.assertEqual(str(train_dset.split							)	,   "train"							)
            self.assertEqual(test_dset["filename"][0]	,   F'''{name}-test'''							)
            self.assertEqual(test_dset.num_rows	,   3_3							)
            self.assertEqual(test_dset.num_columns	,   1							)
            self.assertIsInstance(test_dset.split	,   lowerCAmelCase__							)
            self.assertEqual(str(test_dset.split							)	,   "test[:33%]"							)
            del train_dset, test_dset







      def      _lowercase						(					self							)     ->		Optional[Any]:



        '''simple docstring'''




        a__			:      Any            ="my_name"
        a__			:      List[Any]            =SplitInfo(name="train"	,   num_examples=1_0_0_0	,   shard_lengths=[1_0_0] * 1_0							)
        a__			:      Optional[Any]            =[train_info]
        a__			:      Any            =SplitDict()
        split_dict.add(lowerCAmelCase__							)
        a__			:      Any            =DatasetInfo(splits=lowerCAmelCase__							)

        with tempfile.TemporaryDirectory() as tmp_dir:
          a__			:      Optional[int]            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)

          a__			:      Union[str, Any]            ="train[:33%]"
          a__			:      Union[str, Any]            =Dataset(**reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							)							)
          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	,   3_3_0							)
          self.assertEqual(dset.num_columns	,   1							)







      def      _lowercase						(					self							)     ->		List[str]:



        '''simple docstring'''




        a__			:      Dict            =SplitInfo(name="train"	,   num_examples=1_0_0							)
        a__			:      str            =SplitInfo(name="test"	,   num_examples=1_0_0							)
        a__			:      int            =SplitDict()
        split_dict.add(lowerCAmelCase__							)
        split_dict.add(lowerCAmelCase__							)
        a__			:      int            =DatasetInfo(splits=lowerCAmelCase__							)

        with tempfile.TemporaryDirectory() as tmp_dir:
          a__			:      Tuple            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)

          a__			:      Tuple            =[
              {"filename": os.path.join(lowerCAmelCase__	,   "train"							)},
              {"filename": os.path.join(lowerCAmelCase__	,   "test"							), "skip": 1_0, "take": 1_0},
          ]
          a__			:      Optional[Any]            =Dataset(**reader.read_files(lowerCAmelCase__	,   original_instructions="train+test[10:20]"							)							)
          self.assertEqual(dset.num_rows	,   1_1_0							)
          self.assertEqual(dset.num_columns	,   1							)
          del dset
@pytest.mark.parametrize("in_memory" , [False, True]		)
def   _A (	SCREAMING_SNAKE_CASE  :     Optional[Any] , SCREAMING_SNAKE_CASE  :     Optional[Any] , SCREAMING_SNAKE_CASE  :     Optional[Any]		):





  """simple docstring"""



  a__			:      int            =arrow_file
  with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
    a__			:      str            =ArrowReader.read_table(SCREAMING_SNAKE_CASE , in_memory=SCREAMING_SNAKE_CASE		)
  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   _A (	SCREAMING_SNAKE_CASE  :     Tuple , SCREAMING_SNAKE_CASE  :     List[Any] , SCREAMING_SNAKE_CASE  :     str		):





  """simple docstring"""



  a__			:      Optional[int]            =arrow_file
  a__			:      Tuple            =ArrowReader("" , SCREAMING_SNAKE_CASE		)
  with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
    a__			:      Union[str, Any]            =reader.read_files([{"filename": filename}] , in_memory=SCREAMING_SNAKE_CASE		)
  assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
  a__			:      Dict            =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   _A (	):





  """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%]"

  a__			:      List[Any]            ="train+test"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_test

  a__			:      Union[str, Any]            ="train[2:10]"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_abs

  a__			:      List[Any]            ="train[15%:-20%]"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_pct

  a__			:      Dict            ="train[:10%](closest)"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == "train[:10%]"

  a__			:      Tuple            ="train[:10%](pct1_dropremainder)"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_pct_rounding

  a__			:      List[Any]            ="train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"
  assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_test_pct_rounding
def   _A (	):





  """simple docstring"""



  a__			:      Optional[Any]            ="dummy"
  a__			:      Dict            =[SplitInfo(name="train" , num_examples=100		)]
  a__			:      Optional[Any]            ="train[:33%]"
  a__			:      int            ="arrow"
  a__			:      Any            ="prefix"

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

  a__			:      List[str]            =[SplitInfo(name="train" , num_examples=100 , shard_lengths=[10] * 10		)]
  a__			:      Union[str, Any]            =make_file_instructions(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  assert file_instructions.num_examples == 33
  assert file_instructions.file_instructions == [
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00000-of-00010.arrow'''		), "skip": 0, "take": -1},
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00001-of-00010.arrow'''		), "skip": 0, "take": -1},
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00002-of-00010.arrow'''		), "skip": 0, "take": -1},
      {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00003-of-00010.arrow'''		), "skip": 0, "take": 3},
  ]





@pytest.mark.parametrize("name, expected_exception" , [(None, TypeError), ("", ValueError)]		)
def   _A (	SCREAMING_SNAKE_CASE  :     Tuple , SCREAMING_SNAKE_CASE  :     Tuple		):





  """simple docstring"""



  a__			:      Dict            =[SplitInfo(name="train" , num_examples=100		)]
  a__			:      Any            ="train"
  a__			:      Optional[Any]            ="arrow"
  a__			:      List[Any]            ="prefix_path"
  with pytest.raises(SCREAMING_SNAKE_CASE		):
    a__			:      Optional[Any]            =make_file_instructions(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)






