




'''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      A       (						_a       ):







							def   __lowerCAmelCase     (    self			:    Any   )     ->				Optional[int]:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    Tuple   )     ->				List[str]:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    List[str]   )     ->				Any:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    List[str]   )     ->				Tuple:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    List[str]   )     ->				int:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    str   )     ->				int:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    Tuple   )     ->				Tuple:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    Any   )     ->				Any:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    str   )     ->				Optional[int]:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    Union[str, Any]   )     ->				Dict:


														"""simple docstring"""


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







							def   __lowerCAmelCase     (    self			:    Dict   )     ->				Tuple:


														"""simple docstring"""


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







							@require_pil
							def   __lowerCAmelCase     (    self			:    Optional[int]   )     ->				List[Any]:


														"""simple docstring"""


														import PIL.Image

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



def 						snake_case_       (UpperCamelCase			:    Optional[Any]					,		UpperCamelCase			:    Any ):





							'''simple docstring'''


							_a      	=							pa.BufferReader(__snake_case ) if isinstance(__snake_case					,		pa.Buffer ) else pa.memory_map(__snake_case )
							_a      	=							pa.ipc.open_stream(__snake_case )
							_a      	=							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 						snake_case_       (UpperCamelCase			:    Dict					,		UpperCamelCase			:    Any ):





							'''simple docstring'''


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





							'''simple docstring'''


							_a      	=							pa.BufferOutputStream()
							_a      	=							Features({'''labels''': ClassLabel(names=['''neg''', '''pos'''] )} )
							with ArrowWriter(stream=__snake_case					,		features=__snake_case ) as writer:
														writer.write({'''labels''': 0} )
														writer.write({'''labels''': 1} )
														_a	,				_a      	=							writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							assert writer._schema == features.arrow_schema
							assert writer._schema.metadata == features.arrow_schema.metadata
							_a      	=							pa.BufferReader(output.getvalue() )
							_a      	=							pa.ipc.open_stream(__snake_case )
							_a      	=							f.read_all()
							_a      	=							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(__snake_case )
@pytest.mark.parametrize('''writer_batch_size'''					,		[None, 1, 10] )
def 						snake_case_       (UpperCamelCase			:    Dict ):





							'''simple docstring'''


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





							'''simple docstring'''


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





							'''simple docstring'''


							_a      	=							pa.BufferOutputStream()
							with ArrowWriter(
							    stream=__snake_case					,		writer_batch_size=__snake_case					,		hash_salt='''split_name'''					,		check_duplicates=__snake_case					,		) as writer:
														writer.write({'''col_1''': '''foo''', '''col_2''': 1}					,		key=1 )
														writer.write({'''col_1''': '''bar''', '''col_2''': 2}					,		key=2 )
														_a	,				_a      	=							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 						snake_case_       (UpperCamelCase			:    int					,		UpperCamelCase			:    Dict ):





							'''simple docstring'''


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





							'''simple docstring'''


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





							'''simple docstring'''


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





							'''simple docstring'''


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





							'''simple docstring'''


							if pa.types.is_list(__snake_case ):
														return get_base_dtype(arr_type.value_type )
							else:
														return arr_type
def 						snake_case_       (UpperCamelCase			:    List[str]					,		UpperCamelCase			:    Tuple ):





							'''simple docstring'''


							if isinstance(lst[0]					,		__snake_case ):
														change_first_primitive_element_in_list(lst[0]					,		__snake_case )
							else:
														_a      	=							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 						snake_case_       (UpperCamelCase			:    Optional[Any]					,		UpperCamelCase			:    Union[str, Any]					,		UpperCamelCase			:    List[Any] ):





							'''simple docstring'''


							_a      	=							pa.array(TypedSequence(__snake_case					,		optimized_int_type=__snake_case ) )
							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 						snake_case_       (UpperCamelCase			:    int					,		UpperCamelCase			:    str					,		UpperCamelCase			:    Tuple ):





							'''simple docstring'''


							_a      	=							pa.array(OptimizedTypedSequence(__snake_case					,		col=__snake_case ) )
							assert get_base_dtype(arr.type ) == expected_dtype

							# not in range
							if col != "other":
														# avoids errors due to in-place modifications
														_a      	=							copy.deepcopy(__snake_case )
														_a      	=							np.iinfo(expected_dtype.to_pandas_dtype() ).max + 1
														change_first_primitive_element_in_list(__snake_case					,		__snake_case )
														_a      	=							pa.array(OptimizedTypedSequence(__snake_case					,		col=__snake_case ) )
														assert get_base_dtype(arr.type ) == pa.intaa()
@pytest.mark.parametrize('''raise_exception'''					,		[False, True] )
def 						snake_case_       (UpperCamelCase			:    Dict					,		UpperCamelCase			:    Optional[int] ):





							'''simple docstring'''


							_a      	=							str(tmp_path / '''dataset-train.arrow''' )
							try:
														with ArrowWriter(path=__snake_case ) as writer:
																					if raise_exception:
																												raise pa.lib.ArrowInvalid()
																					else:
																												writer.stream.close()
							except pa.lib.ArrowInvalid:
														pass
							finally:
														assert writer.stream.closed
def 						snake_case_       (UpperCamelCase			:    Union[str, Any] ):





							'''simple docstring'''


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





							'''simple docstring'''


							_a      	=							pa.BufferOutputStream()
							with ParquetWriter(stream=__snake_case ) as writer:
														writer.write({'''col_1''': '''foo''', '''col_2''': 1} )
														writer.write({'''col_1''': '''bar''', '''col_2''': 2} )
														_a	,				_a      	=							writer.finalize()
							assert num_examples == 2
							assert num_bytes > 0
							_a      	=							pa.BufferReader(output.getvalue() )
							_a      	=							pq.read_table(__snake_case )
							assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
@require_pil
@pytest.mark.parametrize('''embed_local_files'''					,		[False, True] )
def 						snake_case_       (UpperCamelCase			:    List[Any]					,		UpperCamelCase			:    str ):





							'''simple docstring'''


							import PIL.Image

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





							'''simple docstring'''


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



"""simple docstring"""





import fire

from utils import calculate_rouge, save_json



def  lowerCamelCase__						(     __snake_case,	__snake_case,	__snake_case=None,	**__snake_case      )				->						Optional[int]:


					"""simple docstring"""





					_UpperCamelCase									=    [x.strip() for x in open(__snake_case      ).readlines()]
					_UpperCamelCase									=    [x.strip() for x in open(__snake_case      ).readlines()][: len(__snake_case      )]
					_UpperCamelCase									=    calculate_rouge(__snake_case,	__snake_case,	**__snake_case      )
					if save_path is not None:
										save_json(__snake_case,	__snake_case,	indent=__snake_case      )
					return metrics  # these print nicely


if __name__ == "__main__":
				fire.Fire(calculate_rouge_path)






