'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


snake_case__					:      Dict				      =  {
    '''configuration_swiftformer''': [
        '''SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SwiftFormerConfig''',
        '''SwiftFormerOnnxConfig''',
    ]
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__					:      str				      =  [
     '''SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''SwiftFormerForImageClassification''',
     '''SwiftFormerModel''',
     '''SwiftFormerPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_swiftformer import (
     SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
     SwiftFormerConfig,
     SwiftFormerOnnxConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_swiftformer import (
      SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      SwiftFormerForImageClassification,
      SwiftFormerModel,
      SwiftFormerPreTrainedModel,
  )

else:
 import sys

 snake_case__					:      Optional[Any]				      =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







'''simple docstring'''


import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil






class 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_	):







  '''simple docstring'''






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[Any]       =				pa.array(TypedSequence([1, 2, 3]						)						)
       self.assertEqual(arr.type				,		pa.intaa()						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       with self.assertRaises(snake_case_						):
            UpperCAmelCase_							:       Optional[int]       =				pa.array(TypedSequence([1, 2, 3]						)				,		type=pa.intaa()						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       with self.assertRaises(snake_case_						):
            UpperCAmelCase_							:       List[Any]       =				pa.array(TypedSequence([1, 2, 3]				,		try_type=Value('bool'						)				,		type=Value('int64'						)						)						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Any       =				pa.array(TypedSequence([1, 2, 3]				,		type=Value('int32'						)						)						)
       self.assertEqual(arr.type				,		pa.intaa()						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       with self.assertRaises((TypeError, pa.lib.ArrowInvalid)						):
            UpperCAmelCase_							:       List[str]       =				pa.array(TypedSequence(['foo', 'bar']				,		type=Value('int64'						)						)						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       str       =				pa.array(TypedSequence([1, 2, 3]				,		try_type=Value('int32'						)						)						)
       self.assertEqual(arr.type				,		pa.intaa()						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[str]       =				pa.array(TypedSequence(['foo', 'bar']				,		try_type=Value('int64'						)						)						)
       self.assertEqual(arr.type				,		pa.string()						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Tuple       =				pa.array(TypedSequence([[[1, 2, 3]]]				,		type=ArrayaD((1, 3)				,		'int64'						)						)						)
       self.assertEqual(arr.type				,		ArrayaDExtensionType((1, 3)				,		'int64'						)						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       with self.assertRaises((TypeError, pa.lib.ArrowInvalid)						):
            UpperCAmelCase_							:       Any       =				pa.array(TypedSequence(['foo', 'bar']				,		type=ArrayaD((1, 3)				,		'int64'						)						)						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       int       =				pa.array(TypedSequence([[[1, 2, 3]]]				,		try_type=ArrayaD((1, 3)				,		'int64'						)						)						)
       self.assertEqual(arr.type				,		ArrayaDExtensionType((1, 3)				,		'int64'						)						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Union[str, Any]       =				pa.array(TypedSequence(['foo', 'bar']				,		try_type=ArrayaD((1, 3)				,		'int64'						)						)						)
       self.assertEqual(arr.type				,		pa.string()						)






  @require_pil
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       import PIL.Image

       UpperCAmelCase_							:       Any       =				PIL.Image.fromarray(np.arange(1_0				,		dtype=np.uinta						).reshape(2				,		5						)						)
       with patch(
           'datasets.arrow_writer.cast_to_python_objects'				,		side_effect=snake_case_						) as mock_cast_to_python_objects:
            UpperCAmelCase_							:       int       =				pa.array(TypedSequence([{'path': None, 'bytes': b'image_bytes'}, pil_image]				,		type=Image()						)						)
            UpperCAmelCase_       ,      UpperCAmelCase_							:       Any       =				mock_cast_to_python_objects.call_args_list[-1]
            self.assertIn('optimize_list_casting'				,		snake_case_						)
            self.assertFalse(kwargs['optimize_list_casting']						)







def  _lowerCamelCase   (				lowerCamelCase_ :							Any     ,					lowerCamelCase_ :							int       ):



     """simple docstring"""





     UpperCAmelCase_							:       str       =				pa.BufferReader(lowerCamelCase_       ) if isinstance(lowerCamelCase_     ,					pa.Buffer       ) else pa.memory_map(lowerCamelCase_       )
     UpperCAmelCase_							:       Union[str, Any]       =				pa.ipc.open_stream(lowerCamelCase_       )
     UpperCAmelCase_							:       pa.Table       =				f.read_all()
     assert len(pa_table.to_batches()       ) == expected_num_chunks
     assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
     del pa_table


@pytest.mark.parametrize('writer_batch_size'     ,					[None, 1, 10]       )
@pytest.mark.parametrize(
    'fields'     ,					[None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							Optional[Any]     ,					lowerCamelCase_ :							int       ):



     """simple docstring"""





     UpperCAmelCase_							:       List[str]       =				pa.BufferOutputStream()
     UpperCAmelCase_							:       Dict       =				pa.schema(lowerCamelCase_       ) if fields else None
     with ArrowWriter(stream=lowerCamelCase_     ,					schema=lowerCamelCase_     ,					writer_batch_size=lowerCamelCase_       ) as writer:
          writer.write({'col_1': 'foo', 'col_2': 1}       )
          writer.write({'col_1': 'bar', 'col_2': 2}       )
          UpperCAmelCase_       ,      UpperCAmelCase_							:       Dict       =				writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     if not fields:
          UpperCAmelCase_							:       Optional[int]       =				{'col_1': pa.string(), 'col_2': pa.intaa()}
     assert writer._schema == pa.schema(lowerCamelCase_     ,					metadata=writer._schema.metadata       )
     _check_output(output.getvalue()     ,					expected_num_chunks=num_examples if writer_batch_size == 1 else 1       )


def  _lowerCamelCase   (				):



     """simple docstring"""





     UpperCAmelCase_							:       Tuple       =				pa.BufferOutputStream()
     UpperCAmelCase_							:       Optional[int]       =				Features({'labels': ClassLabel(names=['neg', 'pos']       )}       )
     with ArrowWriter(stream=lowerCamelCase_     ,					features=lowerCamelCase_       ) as writer:
          writer.write({'labels': 0}       )
          writer.write({'labels': 1}       )
          UpperCAmelCase_       ,      UpperCAmelCase_							:       List[Any]       =				writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     assert writer._schema == features.arrow_schema
     assert writer._schema.metadata == features.arrow_schema.metadata
     UpperCAmelCase_							:       Any       =				pa.BufferReader(output.getvalue()       )
     UpperCAmelCase_							:       List[str]       =				pa.ipc.open_stream(lowerCamelCase_       )
     UpperCAmelCase_							:       pa.Table       =				f.read_all()
     UpperCAmelCase_							:       Optional[Any]       =				pa_table.schema
     assert pa_table.num_rows == 2
     assert schema == features.arrow_schema
     assert schema.metadata == features.arrow_schema.metadata
     assert features == Features.from_arrow_schema(lowerCamelCase_       )


@pytest.mark.parametrize('writer_batch_size'     ,					[None, 1, 10]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							List[Any]       ):



     """simple docstring"""





     UpperCAmelCase_							:       Union[str, Any]       =				pa.BufferOutputStream()
     with ArrowWriter(
         stream=lowerCamelCase_     ,					writer_batch_size=lowerCamelCase_     ,					hash_salt='split_name'     ,					check_duplicates=lowerCamelCase_     ,					) as writer:
          with pytest.raises(lowerCamelCase_       ):
               writer.write({'col_1': 'foo', 'col_2': 1}     ,					key=[1, 2]       )
               UpperCAmelCase_       ,      UpperCAmelCase_							:       Any       =				writer.finalize()


@pytest.mark.parametrize('writer_batch_size'     ,					[None, 2, 10]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							Union[str, Any]       ):



     """simple docstring"""





     UpperCAmelCase_							:       int       =				pa.BufferOutputStream()
     with ArrowWriter(
         stream=lowerCamelCase_     ,					writer_batch_size=lowerCamelCase_     ,					hash_salt='split_name'     ,					check_duplicates=lowerCamelCase_     ,					) as writer:
          with pytest.raises(lowerCamelCase_       ):
               writer.write({'col_1': 'foo', 'col_2': 1}     ,					key=10       )
               writer.write({'col_1': 'bar', 'col_2': 2}     ,					key=10       )
               UpperCAmelCase_       ,      UpperCAmelCase_							:       Optional[Any]       =				writer.finalize()


@pytest.mark.parametrize('writer_batch_size'     ,					[None, 2, 10]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							Optional[int]       ):



     """simple docstring"""





     UpperCAmelCase_							:       str       =				pa.BufferOutputStream()
     with ArrowWriter(
         stream=lowerCamelCase_     ,					writer_batch_size=lowerCamelCase_     ,					hash_salt='split_name'     ,					check_duplicates=lowerCamelCase_     ,					) as writer:
          writer.write({'col_1': 'foo', 'col_2': 1}     ,					key=1       )
          writer.write({'col_1': 'bar', 'col_2': 2}     ,					key=2       )
          UpperCAmelCase_       ,      UpperCAmelCase_							:       Dict       =				writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     _check_output(output.getvalue()     ,					expected_num_chunks=num_examples if writer_batch_size == 1 else 1       )


@pytest.mark.parametrize('writer_batch_size'     ,					[None, 1, 10]       )
@pytest.mark.parametrize(
    'fields'     ,					[None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							Dict     ,					lowerCamelCase_ :							str       ):



     """simple docstring"""





     UpperCAmelCase_							:       List[Any]       =				pa.BufferOutputStream()
     UpperCAmelCase_							:       Optional[Any]       =				pa.schema(lowerCamelCase_       ) if fields else None
     with ArrowWriter(stream=lowerCamelCase_     ,					schema=lowerCamelCase_     ,					writer_batch_size=lowerCamelCase_       ) as writer:
          writer.write_batch({'col_1': ['foo', 'bar'], 'col_2': [1, 2]}       )
          writer.write_batch({'col_1': [], 'col_2': []}       )
          UpperCAmelCase_       ,      UpperCAmelCase_							:       str       =				writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     if not fields:
          UpperCAmelCase_							:       int       =				{'col_1': pa.string(), 'col_2': pa.intaa()}
     assert writer._schema == pa.schema(lowerCamelCase_     ,					metadata=writer._schema.metadata       )
     _check_output(output.getvalue()     ,					expected_num_chunks=num_examples if writer_batch_size == 1 else 1       )


@pytest.mark.parametrize('writer_batch_size'     ,					[None, 1, 10]       )
@pytest.mark.parametrize(
    'fields'     ,					[None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							int     ,					lowerCamelCase_ :							Union[str, Any]       ):



     """simple docstring"""





     UpperCAmelCase_							:       List[str]       =				pa.BufferOutputStream()
     UpperCAmelCase_							:       Optional[int]       =				pa.schema(lowerCamelCase_       ) if fields else None
     with ArrowWriter(stream=lowerCamelCase_     ,					schema=lowerCamelCase_     ,					writer_batch_size=lowerCamelCase_       ) as writer:
          writer.write_table(pa.Table.from_pydict({'col_1': ['foo', 'bar'], 'col_2': [1, 2]}       )       )
          UpperCAmelCase_       ,      UpperCAmelCase_							:       Union[str, Any]       =				writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     if not fields:
          UpperCAmelCase_							:       Any       =				{'col_1': pa.string(), 'col_2': pa.intaa()}
     assert writer._schema == pa.schema(lowerCamelCase_     ,					metadata=writer._schema.metadata       )
     _check_output(output.getvalue()     ,					expected_num_chunks=num_examples if writer_batch_size == 1 else 1       )


@pytest.mark.parametrize('writer_batch_size'     ,					[None, 1, 10]       )
@pytest.mark.parametrize(
    'fields'     ,					[None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							Dict     ,					lowerCamelCase_ :							List[str]       ):



     """simple docstring"""





     UpperCAmelCase_							:       Tuple       =				pa.BufferOutputStream()
     UpperCAmelCase_							:       Tuple       =				pa.schema(lowerCamelCase_       ) if fields else None
     with ArrowWriter(stream=lowerCamelCase_     ,					schema=lowerCamelCase_     ,					writer_batch_size=lowerCamelCase_       ) as writer:
          writer.write_row(pa.Table.from_pydict({'col_1': ['foo'], 'col_2': [1]}       )       )
          writer.write_row(pa.Table.from_pydict({'col_1': ['bar'], 'col_2': [2]}       )       )
          UpperCAmelCase_       ,      UpperCAmelCase_							:       Optional[int]       =				writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     if not fields:
          UpperCAmelCase_							:       Union[str, Any]       =				{'col_1': pa.string(), 'col_2': pa.intaa()}
     assert writer._schema == pa.schema(lowerCamelCase_     ,					metadata=writer._schema.metadata       )
     _check_output(output.getvalue()     ,					expected_num_chunks=num_examples if writer_batch_size == 1 else 1       )


def  _lowerCamelCase   (				):



     """simple docstring"""





     with tempfile.TemporaryDirectory() as tmp_dir:
          UpperCAmelCase_							:       Union[str, Any]       =				{'col_1': pa.string(), 'col_2': pa.intaa()}
          UpperCAmelCase_							:       Tuple       =				os.path.join(lowerCamelCase_     ,					'test.arrow'       )
          with ArrowWriter(path=lowerCamelCase_     ,					schema=pa.schema(lowerCamelCase_       )       ) as writer:
               writer.write_batch({'col_1': ['foo', 'bar'], 'col_2': [1, 2]}       )
               UpperCAmelCase_       ,      UpperCAmelCase_							:       Union[str, Any]       =				writer.finalize()
          assert num_examples == 2
          assert num_bytes > 0
          assert writer._schema == pa.schema(lowerCamelCase_     ,					metadata=writer._schema.metadata       )
          _check_output(lowerCamelCase_     ,					1       )


def  _lowerCamelCase   (				lowerCamelCase_ :							Optional[Any]       ):



     """simple docstring"""





     if pa.types.is_list(lowerCamelCase_       ):
          return get_base_dtype(arr_type.value_type       )
     else:
          return arr_type


def  _lowerCamelCase   (				lowerCamelCase_ :							Optional[int]     ,					lowerCamelCase_ :							Optional[Any]       ):



     """simple docstring"""





     if isinstance(lst[0]     ,					lowerCamelCase_       ):
          change_first_primitive_element_in_list(lst[0]     ,					lowerCamelCase_       )
     else:
          UpperCAmelCase_							:       str       =				value


@pytest.mark.parametrize('optimized_int_type, expected_dtype'     ,					[(None, pa.intaa()), (Value('int32'       ), pa.intaa())]       )
@pytest.mark.parametrize('sequence'     ,					[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							int     ,					lowerCamelCase_ :							Dict     ,					lowerCamelCase_ :							int       ):



     """simple docstring"""





     UpperCAmelCase_							:       List[Any]       =				pa.array(TypedSequence(lowerCamelCase_     ,					optimized_int_type=lowerCamelCase_       )       )
     assert get_base_dtype(arr.type       ) == expected_dtype


@pytest.mark.parametrize(
    'col, expected_dtype'     ,					[
        ('attention_mask', pa.inta()),
        ('special_tokens_mask', pa.inta()),
        ('token_type_ids', pa.inta()),
        ('input_ids', pa.intaa()),
        ('other', pa.intaa()),
    ]     ,					)
@pytest.mark.parametrize('sequence'     ,					[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							Optional[Any]     ,					lowerCamelCase_ :							Tuple     ,					lowerCamelCase_ :							List[Any]       ):



     """simple docstring"""





     UpperCAmelCase_							:       Tuple       =				pa.array(OptimizedTypedSequence(lowerCamelCase_     ,					col=lowerCamelCase_       )       )
     assert get_base_dtype(arr.type       ) == expected_dtype

     # not in range
     if col != "other":
          # avoids errors due to in-place modifications
          UpperCAmelCase_							:       int       =				copy.deepcopy(lowerCamelCase_       )
          UpperCAmelCase_							:       str       =				np.iinfo(expected_dtype.to_pandas_dtype()       ).max + 1
          change_first_primitive_element_in_list(lowerCamelCase_     ,					lowerCamelCase_       )
          UpperCAmelCase_							:       Dict       =				pa.array(OptimizedTypedSequence(lowerCamelCase_     ,					col=lowerCamelCase_       )       )
          assert get_base_dtype(arr.type       ) == pa.intaa()


@pytest.mark.parametrize('raise_exception'     ,					[False, True]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							List[str]     ,					lowerCamelCase_ :							List[Any]       ):



     """simple docstring"""





     UpperCAmelCase_							:       int       =				str(tmp_path / 'dataset-train.arrow'       )
     try:
          with ArrowWriter(path=lowerCamelCase_       ) as writer:
               if raise_exception:
                    raise pa.lib.ArrowInvalid()
               else:
                    writer.stream.close()
     except pa.lib.ArrowInvalid:
          pass
     finally:
          assert writer.stream.closed


def  _lowerCamelCase   (				lowerCamelCase_ :							Dict       ):



     """simple docstring"""





     UpperCAmelCase_							:       Dict       =				'mock://dataset-train.arrow'
     with ArrowWriter(path=lowerCamelCase_     ,					storage_options=mockfs.storage_options       ) as writer:
          assert isinstance(writer._fs     ,					type(lowerCamelCase_       )       )
          assert writer._fs.storage_options == mockfs.storage_options
          writer.write({'col_1': 'foo', 'col_2': 1}       )
          writer.write({'col_1': 'bar', 'col_2': 2}       )
          UpperCAmelCase_       ,      UpperCAmelCase_							:       Tuple       =				writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     assert mockfs.exists(lowerCamelCase_       )


def  _lowerCamelCase   (				):



     """simple docstring"""





     UpperCAmelCase_							:       Optional[Any]       =				pa.BufferOutputStream()
     with ParquetWriter(stream=lowerCamelCase_       ) as writer:
          writer.write({'col_1': 'foo', 'col_2': 1}       )
          writer.write({'col_1': 'bar', 'col_2': 2}       )
          UpperCAmelCase_       ,      UpperCAmelCase_							:       Optional[int]       =				writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     UpperCAmelCase_							:       List[str]       =				pa.BufferReader(output.getvalue()       )
     UpperCAmelCase_							:       pa.Table       =				pq.read_table(lowerCamelCase_       )
     assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}


@require_pil
@pytest.mark.parametrize('embed_local_files'     ,					[False, True]       )
def  _lowerCamelCase   (				lowerCamelCase_ :							List[Any]     ,					lowerCamelCase_ :							Union[str, Any]       ):



     """simple docstring"""





     import PIL.Image

     UpperCAmelCase_							:       str       =				str(tmp_path / 'test_image_rgb.jpg'       )
     PIL.Image.fromarray(np.zeros((5, 5)     ,					dtype=np.uinta       )       ).save(lowerCamelCase_     ,					format='png'       )
     UpperCAmelCase_							:       int       =				pa.BufferOutputStream()
     with ParquetWriter(
         stream=lowerCamelCase_     ,					features=Features({'image': Image()}       )     ,					embed_local_files=lowerCamelCase_       ) as writer:
          writer.write({'image': image_path}       )
          writer.finalize()
     UpperCAmelCase_							:       Optional[int]       =				pa.BufferReader(output.getvalue()       )
     UpperCAmelCase_							:       pa.Table       =				pq.read_table(lowerCamelCase_       )
     UpperCAmelCase_							:       List[str]       =				pa_table.to_pydict()
     if embed_local_files:
          assert isinstance(out['image'][0]['path']     ,					lowerCamelCase_       )
          with open(lowerCamelCase_     ,					'rb'       ) as f:
               assert out["image"][0]["bytes"] == f.read()
     else:
          assert out["image"][0]["path"] == image_path
          assert out["image"][0]["bytes"] is None





def  _lowerCamelCase   (				):



     """simple docstring"""





     UpperCAmelCase_							:       List[str]       =				pa.schema([pa.field('col_1'     ,					pa.string()     ,					nullable=lowerCamelCase_       )]       )
     UpperCAmelCase_							:       Dict       =				pa.BufferOutputStream()
     with ArrowWriter(stream=lowerCamelCase_       ) as writer:
          writer._build_writer(inferred_schema=lowerCamelCase_       )
          assert writer._schema == pa.schema([pa.field('col_1'     ,					pa.string()       )]       )






