



"""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        _UpperCAmelCase       (			lowerCAmelCase__):

 def 						_snake_case					(     self		:       str				):
     snake_case_ :     List[str]				=	pa.array(TypedSequence([1, 2, 3]				)				)
     self.assertEqual(arr.type  ,     pa.intaa()				)

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

 def 						_snake_case					(     self		:       Union[str, Any]				):
     with self.assertRaises(lowercase_				):
         snake_case_ :     Optional[Any]				=	pa.array(TypedSequence([1, 2, 3]  ,     try_type=Value('''bool'''				)  ,     type=Value('''int64'''				)				)				)

 def 						_snake_case					(     self		:       Dict				):
     snake_case_ :     Optional[Any]				=	pa.array(TypedSequence([1, 2, 3]  ,     type=Value('''int32'''				)				)				)
     self.assertEqual(arr.type  ,     pa.intaa()				)

 def 						_snake_case					(     self		:       Dict				):
     with self.assertRaises((TypeError, pa.lib.ArrowInvalid)				):
         snake_case_ :     Union[str, Any]				=	pa.array(TypedSequence(['''foo''', '''bar''']  ,     type=Value('''int64'''				)				)				)

 def 						_snake_case					(     self		:       int				):
     snake_case_ :     Any				=	pa.array(TypedSequence([1, 2, 3]  ,     try_type=Value('''int32'''				)				)				)
     self.assertEqual(arr.type  ,     pa.intaa()				)

 def 						_snake_case					(     self		:       Dict				):
     snake_case_ :     Tuple				=	pa.array(TypedSequence(['''foo''', '''bar''']  ,     try_type=Value('''int64'''				)				)				)
     self.assertEqual(arr.type  ,     pa.string()				)

 def 						_snake_case					(     self		:       Dict				):
     snake_case_ :     Union[str, Any]				=	pa.array(TypedSequence([[[1, 2, 3]]]  ,     type=ArrayaD((1, 3)  ,     '''int64'''				)				)				)
     self.assertEqual(arr.type  ,     ArrayaDExtensionType((1, 3)  ,     '''int64'''				)				)

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

 def 						_snake_case					(     self		:       Dict				):
     snake_case_ :     Dict				=	pa.array(TypedSequence([[[1, 2, 3]]]  ,     try_type=ArrayaD((1, 3)  ,     '''int64'''				)				)				)
     self.assertEqual(arr.type  ,     ArrayaDExtensionType((1, 3)  ,     '''int64'''				)				)

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






 @require_pil
 def 						_snake_case					(     self		:       str				):
     import PIL.Image

     snake_case_ :     List[str]				=	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:
         snake_case_ :     Union[str, Any]				=	pa.array(TypedSequence([{'''path''': None, '''bytes''': B'''image_bytes'''}, pil_image]  ,     type=Image()				)				)
         snake_case_,	snake_case_ :     Tuple				=	mock_cast_to_python_objects.call_args_list[-1]
         self.assertIn('''optimize_list_casting'''  ,     lowercase_				)
         self.assertFalse(kwargs['''optimize_list_casting''']				)





def __lowercase			(							_a		,			_a    ):
    snake_case_ :     List[Any]				=	pa.BufferReader(_a    ) if isinstance(_a		,			pa.Buffer    ) else pa.memory_map(_a    )
    snake_case_ :     int				=	pa.ipc.open_stream(_a    )
    snake_case_ :     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 __lowercase			(							_a		,			_a    ):
    snake_case_ :     Optional[Any]				=	pa.BufferOutputStream()
    snake_case_ :     Optional[Any]				=	pa.schema(_a    ) if fields else None
    with ArrowWriter(stream=_a		,			schema=_a		,			writer_batch_size=_a    ) as writer:
        writer.write({'''col_1''': '''foo''', '''col_2''': 1}    )
        writer.write({'''col_1''': '''bar''', '''col_2''': 2}    )
        snake_case_,	snake_case_ :     Optional[Any]				=	writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        snake_case_ :     Dict				=	{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
    assert writer._schema == pa.schema(_a		,			metadata=writer._schema.metadata    )
    _check_output(output.getvalue()		,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1    )




def __lowercase			(							):
    snake_case_ :     Tuple				=	pa.BufferOutputStream()
    snake_case_ :     Optional[Any]				=	Features({'''labels''': ClassLabel(names=['''neg''', '''pos''']    )}    )
    with ArrowWriter(stream=_a		,			features=_a    ) as writer:
        writer.write({'''labels''': 0}    )
        writer.write({'''labels''': 1}    )
        snake_case_,	snake_case_ :     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
    snake_case_ :     str				=	pa.BufferReader(output.getvalue()    )
    snake_case_ :     str				=	pa.ipc.open_stream(_a    )
    snake_case_ :     pa.Table				=	f.read_all()
    snake_case_ :     Dict				=	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(_a    )




@pytest.mark.parametrize('''writer_batch_size'''		,			[None, 1, 10]    )
def __lowercase			(							_a    ):
    snake_case_ :     Any				=	pa.BufferOutputStream()
    with ArrowWriter(
        stream=_a		,			writer_batch_size=_a		,			hash_salt='''split_name'''		,			check_duplicates=_a		,			) as writer:
        with pytest.raises(_a    ):
            writer.write({'''col_1''': '''foo''', '''col_2''': 1}		,			key=[1, 2]    )
            snake_case_,	snake_case_ :     List[str]				=	writer.finalize()




@pytest.mark.parametrize('''writer_batch_size'''		,			[None, 2, 10]    )
def __lowercase			(							_a    ):
    snake_case_ :     List[Any]				=	pa.BufferOutputStream()
    with ArrowWriter(
        stream=_a		,			writer_batch_size=_a		,			hash_salt='''split_name'''		,			check_duplicates=_a		,			) as writer:
        with pytest.raises(_a    ):
            writer.write({'''col_1''': '''foo''', '''col_2''': 1}		,			key=10    )
            writer.write({'''col_1''': '''bar''', '''col_2''': 2}		,			key=10    )
            snake_case_,	snake_case_ :     Dict				=	writer.finalize()




@pytest.mark.parametrize('''writer_batch_size'''		,			[None, 2, 10]    )
def __lowercase			(							_a    ):
    snake_case_ :     List[str]				=	pa.BufferOutputStream()
    with ArrowWriter(
        stream=_a		,			writer_batch_size=_a		,			hash_salt='''split_name'''		,			check_duplicates=_a		,			) as writer:
        writer.write({'''col_1''': '''foo''', '''col_2''': 1}		,			key=1    )
        writer.write({'''col_1''': '''bar''', '''col_2''': 2}		,			key=2    )
        snake_case_,	snake_case_ :     Union[str, Any]				=	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 __lowercase			(							_a		,			_a    ):
    snake_case_ :     List[Any]				=	pa.BufferOutputStream()
    snake_case_ :     str				=	pa.schema(_a    ) if fields else None
    with ArrowWriter(stream=_a		,			schema=_a		,			writer_batch_size=_a    ) as writer:
        writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}    )
        writer.write_batch({'''col_1''': [], '''col_2''': []}    )
        snake_case_,	snake_case_ :     str				=	writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        snake_case_ :     Optional[int]				=	{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
    assert writer._schema == pa.schema(_a		,			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 __lowercase			(							_a		,			_a    ):
    snake_case_ :     Any				=	pa.BufferOutputStream()
    snake_case_ :     List[str]				=	pa.schema(_a    ) if fields else None
    with ArrowWriter(stream=_a		,			schema=_a		,			writer_batch_size=_a    ) as writer:
        writer.write_table(pa.Table.from_pydict({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}    )    )
        snake_case_,	snake_case_ :     int				=	writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        snake_case_ :     Dict				=	{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
    assert writer._schema == pa.schema(_a		,			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 __lowercase			(							_a		,			_a    ):
    snake_case_ :     Optional[int]				=	pa.BufferOutputStream()
    snake_case_ :     Dict				=	pa.schema(_a    ) if fields else None
    with ArrowWriter(stream=_a		,			schema=_a		,			writer_batch_size=_a    ) 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]}    )    )
        snake_case_,	snake_case_ :     List[Any]				=	writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        snake_case_ :     Optional[int]				=	{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
    assert writer._schema == pa.schema(_a		,			metadata=writer._schema.metadata    )
    _check_output(output.getvalue()		,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1    )




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




def __lowercase			(							_a    ):
    if pa.types.is_list(_a    ):
        return get_base_dtype(arr_type.value_type    )
    else:
        return arr_type




def __lowercase			(							_a		,			_a    ):
    if isinstance(lst[0]		,			_a    ):
        change_first_primitive_element_in_list(lst[0]		,			_a    )
    else:
        snake_case_ :     Any				=	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 __lowercase			(							_a		,			_a		,			_a    ):
    snake_case_ :     List[Any]				=	pa.array(TypedSequence(_a		,			optimized_int_type=_a    )    )
    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 __lowercase			(							_a		,			_a		,			_a    ):
    # in range
    snake_case_ :     int				=	pa.array(OptimizedTypedSequence(_a		,			col=_a    )    )
    assert get_base_dtype(arr.type    ) == expected_dtype

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




@pytest.mark.parametrize('''raise_exception'''		,			[False, True]    )
def __lowercase			(							_a		,			_a    ):
    snake_case_ :     Tuple				=	str(tmp_path / '''dataset-train.arrow'''    )
    try:
        with ArrowWriter(path=_a    ) as writer:
            if raise_exception:
                raise pa.lib.ArrowInvalid()
            else:
                writer.stream.close()
    except pa.lib.ArrowInvalid:
        pass
    finally:
        assert writer.stream.closed




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




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




@require_pil
@pytest.mark.parametrize('''embed_local_files'''		,			[False, True]    )
def __lowercase			(							_a		,			_a    ):
    import PIL.Image

    snake_case_ :     Optional[Any]				=	str(tmp_path / '''test_image_rgb.jpg'''    )
    PIL.Image.fromarray(np.zeros((5, 5)		,			dtype=np.uinta    )    ).save(_a		,			format='''png'''    )
    snake_case_ :     Tuple				=	pa.BufferOutputStream()
    with ParquetWriter(
        stream=_a		,			features=Features({'''image''': Image()}    )		,			embed_local_files=_a    ) as writer:
        writer.write({'''image''': image_path}    )
        writer.finalize()
    snake_case_ :     Any				=	pa.BufferReader(output.getvalue()    )
    snake_case_ :     pa.Table				=	pq.read_table(_a    )
    snake_case_ :     Union[str, Any]				=	pa_table.to_pydict()
    if embed_local_files:
        assert isinstance(out['''image'''][0]['''path''']		,			_a    )
        with open(_a		,			'''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 __lowercase			(							):
    snake_case_ :     Union[str, Any]				=	pa.schema([pa.field('''col_1'''		,			pa.string()		,			nullable=_a    )]    )
    snake_case_ :     Tuple				=	pa.BufferOutputStream()
    with ArrowWriter(stream=_a    ) as writer:
        writer._build_writer(inferred_schema=_a    )
        assert writer._schema == pa.schema([pa.field('''col_1'''		,			pa.string()    )]    )










"""simple docstring"""

import copy
import os

import cva
import numpy as np
from matplotlib import pyplot as plt




class        _UpperCAmelCase       :

 def __init__(     self		:       List[Any]				):
     snake_case_ :     List[str]				=	''''''
     snake_case_ :     Tuple				=	''''''
     snake_case_ :     int				=	[]
     snake_case_ :     Optional[int]				=	0
     snake_case_ :     Optional[Any]				=	256
     snake_case_ :     Tuple				=	0
     snake_case_ :     Tuple				=	0
     snake_case_ :     Optional[Any]				=	0
     snake_case_ :     Any				=	0

 def 						_snake_case					(     self		:       Optional[Any]  ,     lowercase_		:       List[Any]				):
     snake_case_ :     List[Any]				=	cva.imread(lowercase_  ,     0				)
     snake_case_ :     Tuple				=	copy.deepcopy(self.img				)
     snake_case_,	snake_case_,	snake_case_ :     List[Any]				=	plt.hist(self.img.ravel()  ,     256  ,     [0, 256]  ,     label='''x'''				)
     snake_case_ :     str				=	np.sum(lowercase_				)
     for i in range(len(lowercase_				)				):
         snake_case_ :     Optional[Any]				=	x[i] / self.k
         self.sk += prk
         snake_case_ :     Any				=	(self.L - 1) * self.sk
         if self.rem != 0:
             snake_case_ :     Dict				=	int(last % last				)
         snake_case_ :     Union[str, Any]				=	int(last + 1 if self.rem >= 0.5 else last				)
         self.last_list.append(lowercase_				)
         snake_case_ :     int				=	int(np.ma.count(self.img				) / self.img[1].size				)
         snake_case_ :     Tuple				=	self.img[1].size
     for i in range(self.number_of_cols				):
         for j in range(self.number_of_rows				):
             snake_case_ :     Union[str, Any]				=	self.img[j][i]
             if num != self.last_list[num]:
                 snake_case_ :     List[str]				=	self.last_list[num]
     cva.imwrite('''output_data/output.jpg'''  ,     self.img				)

 def 						_snake_case					(     self		:       Tuple				):
     plt.hist(self.img.ravel()  ,     256  ,     [0, 256]				)






 def 						_snake_case					(     self		:       int				):
     cva.imshow('''Output-Image'''  ,     self.img				)
     cva.imshow('''Input-Image'''  ,     self.original_image				)
     cva.waitKey(5000				)
     cva.destroyAllWindows()


if __name__ == "__main__":
     lowercase__    :  Any							    =	os.path.join(os.path.basename(__file__), '''image_data/input.jpg''')
     lowercase__    :  Any							    =	ConstantStretch()
     stretcher.stretch(file_path)
     stretcher.plot_histogram()
     stretcher.show_image()





