

'''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 	lowerCAmelCase  (   A ):







       def       snake_case (				self      :			Dict   ):







            """simple docstring"""







            __lowercase      		=pa.array(TypedSequence([1, 2, 3]   )   )
            self.assertEqual(arr.type    ,   pa.intaa()   )







       def       snake_case (				self      :			Optional[int]   ):







            """simple docstring"""







            with self.assertRaises(__lowercase   ):
                 __lowercase      		=pa.array(TypedSequence([1, 2, 3]   )    ,   type=pa.intaa()   )







       def       snake_case (				self      :			str   ):







            """simple docstring"""







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







       def       snake_case (				self      :			str   ):







            """simple docstring"""







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







       def       snake_case (				self      :			Optional[int]   ):







            """simple docstring"""







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







       def       snake_case (				self      :			Optional[Any]   ):







            """simple docstring"""







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







       def       snake_case (				self      :			Tuple   ):







            """simple docstring"""







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







       def       snake_case (				self      :			Optional[Any]   ):







            """simple docstring"""







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







       def       snake_case (				self      :			Optional[Any]   ):







            """simple docstring"""







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







       def       snake_case (				self      :			List[Any]   ):







            """simple docstring"""







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







       def       snake_case (				self      :			Optional[int]   ):







            """simple docstring"""







            __lowercase      		=pa.array(TypedSequence(['foo', 'bar']    ,   try_type=ArrayaD((1, 3)    ,   'int64'   )   )   )
            self.assertEqual(arr.type    ,   pa.string()   )







       @require_pil
       def       snake_case (				self      :			Optional[Any]   ):







            """simple docstring"""







            import PIL.Image

            __lowercase      		=PIL.Image.fromarray(np.arange(10    ,   dtype=np.uinta   ).reshape(2    ,   5   )   )
            with patch(
                'datasets.arrow_writer.cast_to_python_objects'    ,   side_effect=__lowercase   ) as mock_cast_to_python_objects:
                 __lowercase      		=pa.array(TypedSequence([{'path': None, 'bytes': b'image_bytes'}, pil_image]    ,   type=Image()   )   )
                 __lowercase		,  __lowercase      		=mock_cast_to_python_objects.call_args_list[-1]
                 self.assertIn('optimize_list_casting'    ,   __lowercase   )
                 self.assertFalse(kwargs['optimize_list_casting']   )






def 					__UpperCamelCase				(						lowercase__    :	str,       lowercase__    :	int			):






     '''simple docstring'''





     __lowercase      		=pa.BufferReader(lowercase__			) if isinstance(lowercase__,       pa.Buffer			) else pa.memory_map(lowercase__			)
     __lowercase      		=pa.ipc.open_stream(lowercase__			)
     __lowercase      		=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 					__UpperCamelCase				(						lowercase__    :	Any,       lowercase__    :	int			):






     '''simple docstring'''





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

def 					__UpperCamelCase				(						):






     '''simple docstring'''





     __lowercase      		=pa.BufferOutputStream()
     __lowercase      		=Features({'labels': ClassLabel(names=['neg', 'pos']			)}			)
     with ArrowWriter(stream=lowercase__,       features=lowercase__			) as writer:
          writer.write({'labels': 0}			)
          writer.write({'labels': 1}			)
          __lowercase		,  __lowercase      		=writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     assert writer._schema == features.arrow_schema
     assert writer._schema.metadata == features.arrow_schema.metadata
     __lowercase      		=pa.BufferReader(output.getvalue()			)
     __lowercase      		=pa.ipc.open_stream(lowercase__			)
     __lowercase      		=f.read_all()
     __lowercase      		=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(lowercase__			)

@pytest.mark.parametrize('writer_batch_size',       [None, 1, 10]			)
def 					__UpperCamelCase				(						lowercase__    :	Tuple			):






     '''simple docstring'''





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

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






     '''simple docstring'''





     __lowercase      		=pa.BufferOutputStream()
     with ArrowWriter(
         stream=lowercase__,       writer_batch_size=lowercase__,       hash_salt='split_name',       check_duplicates=lowercase__,       ) as writer:
          with pytest.raises(lowercase__			):
               writer.write({'col_1': 'foo', 'col_2': 1},       key=10			)
               writer.write({'col_1': 'bar', 'col_2': 2},       key=10			)
               __lowercase		,  __lowercase      		=writer.finalize()

@pytest.mark.parametrize('writer_batch_size',       [None, 2, 10]			)
def 					__UpperCamelCase				(						lowercase__    :	int			):






     '''simple docstring'''





     __lowercase      		=pa.BufferOutputStream()
     with ArrowWriter(
         stream=lowercase__,       writer_batch_size=lowercase__,       hash_salt='split_name',       check_duplicates=lowercase__,       ) as writer:
          writer.write({'col_1': 'foo', 'col_2': 1},       key=1			)
          writer.write({'col_1': 'bar', 'col_2': 2},       key=2			)
          __lowercase		,  __lowercase      		=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 					__UpperCamelCase				(						lowercase__    :	Optional[Any],       lowercase__    :	Any			):






     '''simple docstring'''





     __lowercase      		=pa.BufferOutputStream()
     __lowercase      		=pa.schema(lowercase__			) if fields else None
     with ArrowWriter(stream=lowercase__,       schema=lowercase__,       writer_batch_size=lowercase__			) as writer:
          writer.write_batch({'col_1': ['foo', 'bar'], 'col_2': [1, 2]}			)
          writer.write_batch({'col_1': [], 'col_2': []}			)
          __lowercase		,  __lowercase      		=writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     if not fields:
          __lowercase      		={'col_1': pa.string(), 'col_2': pa.intaa()}
     assert writer._schema == pa.schema(lowercase__,       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 					__UpperCamelCase				(						lowercase__    :	str,       lowercase__    :	Union[str, Any]			):






     '''simple docstring'''





     __lowercase      		=pa.BufferOutputStream()
     __lowercase      		=pa.schema(lowercase__			) if fields else None
     with ArrowWriter(stream=lowercase__,       schema=lowercase__,       writer_batch_size=lowercase__			) as writer:
          writer.write_table(pa.Table.from_pydict({'col_1': ['foo', 'bar'], 'col_2': [1, 2]}			)			)
          __lowercase		,  __lowercase      		=writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     if not fields:
          __lowercase      		={'col_1': pa.string(), 'col_2': pa.intaa()}
     assert writer._schema == pa.schema(lowercase__,       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 					__UpperCamelCase				(						lowercase__    :	Any,       lowercase__    :	str			):






     '''simple docstring'''





     __lowercase      		=pa.BufferOutputStream()
     __lowercase      		=pa.schema(lowercase__			) if fields else None
     with ArrowWriter(stream=lowercase__,       schema=lowercase__,       writer_batch_size=lowercase__			) 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]}			)			)
          __lowercase		,  __lowercase      		=writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     if not fields:
          __lowercase      		={'col_1': pa.string(), 'col_2': pa.intaa()}
     assert writer._schema == pa.schema(lowercase__,       metadata=writer._schema.metadata			)
     _check_output(output.getvalue(),       expected_num_chunks=num_examples if writer_batch_size == 1 else 1			)

def 					__UpperCamelCase				(						):






     '''simple docstring'''





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

def 					__UpperCamelCase				(						lowercase__    :	int			):






     '''simple docstring'''





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

def 					__UpperCamelCase				(						lowercase__    :	Union[str, Any],       lowercase__    :	List[str]			):






     '''simple docstring'''





     if isinstance(lst[0],       lowercase__			):
          change_first_primitive_element_in_list(lst[0],       lowercase__			)
     else:
          __lowercase      		=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 					__UpperCamelCase				(						lowercase__    :	Any,       lowercase__    :	Optional[Any],       lowercase__    :	str			):






     '''simple docstring'''





     __lowercase      		=pa.array(TypedSequence(lowercase__,       optimized_int_type=lowercase__			)			)
     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 					__UpperCamelCase				(						lowercase__    :	Tuple,       lowercase__    :	Optional[Any],       lowercase__    :	Optional[Any]			):






     '''simple docstring'''





     __lowercase      		=pa.array(OptimizedTypedSequence(lowercase__,       col=lowercase__			)			)
     assert get_base_dtype(arr.type			) == expected_dtype

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

@pytest.mark.parametrize('raise_exception',       [False, True]			)
def 					__UpperCamelCase				(						lowercase__    :	Optional[Any],       lowercase__    :	List[str]			):






     '''simple docstring'''





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

def 					__UpperCamelCase				(						lowercase__    :	List[str]			):






     '''simple docstring'''





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

def 					__UpperCamelCase				(						):






     '''simple docstring'''





     __lowercase      		=pa.BufferOutputStream()
     with ParquetWriter(stream=lowercase__			) as writer:
          writer.write({'col_1': 'foo', 'col_2': 1}			)
          writer.write({'col_1': 'bar', 'col_2': 2}			)
          __lowercase		,  __lowercase      		=writer.finalize()
     assert num_examples == 2
     assert num_bytes > 0
     __lowercase      		=pa.BufferReader(output.getvalue()			)
     __lowercase      		=pq.read_table(lowercase__			)
     assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}

@require_pil
@pytest.mark.parametrize('embed_local_files',       [False, True]			)
def 					__UpperCamelCase				(						lowercase__    :	List[str],       lowercase__    :	Optional[Any]			):






     '''simple docstring'''





     import PIL.Image

     __lowercase      		=str(tmp_path / 'test_image_rgb.jpg'			)
     PIL.Image.fromarray(np.zeros((5, 5),       dtype=np.uinta			)			).save(lowercase__,       format='png'			)
     __lowercase      		=pa.BufferOutputStream()
     with ParquetWriter(
         stream=lowercase__,       features=Features({'image': Image()}			),       embed_local_files=lowercase__			) as writer:
          writer.write({'image': image_path}			)
          writer.finalize()
     __lowercase      		=pa.BufferReader(output.getvalue()			)
     __lowercase      		=pq.read_table(lowercase__			)
     __lowercase      		=pa_table.to_pydict()
     if embed_local_files:
          assert isinstance(out['image'][0]['path'],       lowercase__			)
          with open(lowercase__,       '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 					__UpperCamelCase				(						):






     '''simple docstring'''





     __lowercase      		=pa.schema([pa.field('col_1',       pa.string(),       nullable=lowercase__			)]			)
     __lowercase      		=pa.BufferOutputStream()
     with ArrowWriter(stream=lowercase__			) as writer:
          writer._build_writer(inferred_schema=lowercase__			)
          assert writer._schema == pa.schema([pa.field('col_1',       pa.string()			)]			)





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase					 =	{
    '''configuration_owlvit''': [
        '''OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''OwlViTConfig''',
        '''OwlViTOnnxConfig''',
        '''OwlViTTextConfig''',
        '''OwlViTVisionConfig''',
    ],
    '''processing_owlvit''': ['''OwlViTProcessor'''],
}


try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase					 =	['''OwlViTFeatureExtractor''']
       UpperCAmelCase					 =	['''OwlViTImageProcessor''']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase					 =	[
           '''OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''OwlViTModel''',
           '''OwlViTPreTrainedModel''',
           '''OwlViTTextModel''',
           '''OwlViTVisionModel''',
           '''OwlViTForObjectDetection''',
       ]

if TYPE_CHECKING:
       from .configuration_owlvit import (
           OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
           OwlViTConfig,
           OwlViTOnnxConfig,
           OwlViTTextConfig,
           OwlViTVisionConfig,
       )
       from .processing_owlvit import OwlViTProcessor

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_owlvit import OwlViTFeatureExtractor
              from .image_processing_owlvit import OwlViTImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_owlvit import (
                  OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  OwlViTForObjectDetection,
                  OwlViTModel,
                  OwlViTPreTrainedModel,
                  OwlViTTextModel,
                  OwlViTVisionModel,
              )

else:
       import sys

       UpperCAmelCase					 =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


