



"""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    (				SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		def    UpperCAmelCase__							(					self   ) ->						int:







								'''simple docstring'''

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





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







								'''simple docstring'''

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





		def    UpperCAmelCase__							(					self   ) ->						str:







								'''simple docstring'''

								with self.assertRaises(_lowercase   ):
														snake_case_   : str						=			pa.array(TypedSequence([1, 2, 3]							,    try_type=Value("""bool"""   )							,    type=Value("""int64"""   )   )   )





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







								'''simple docstring'''

								snake_case_   : Dict						=			pa.array(TypedSequence([1, 2, 3]							,    type=Value("""int32"""   )   )   )
								self.assertEqual(arr.type							,    pa.intaa()   )





		def    UpperCAmelCase__							(					self   ) ->						Dict:







								'''simple docstring'''

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





		def    UpperCAmelCase__							(					self   ) ->						Optional[int]:







								'''simple docstring'''

								snake_case_   : Tuple						=			pa.array(TypedSequence([1, 2, 3]							,    try_type=Value("""int32"""   )   )   )
								self.assertEqual(arr.type							,    pa.intaa()   )





		def    UpperCAmelCase__							(					self   ) ->						Dict:







								'''simple docstring'''

								snake_case_   : Optional[int]						=			pa.array(TypedSequence(["""foo""", """bar"""]							,    try_type=Value("""int64"""   )   )   )
								self.assertEqual(arr.type							,    pa.string()   )





		def    UpperCAmelCase__							(					self   ) ->						int:







								'''simple docstring'''

								snake_case_   : List[Any]						=			pa.array(TypedSequence([[[1, 2, 3]]]							,    type=ArrayaD((1, 3)							,    """int64"""   )   )   )
								self.assertEqual(arr.type							,    ArrayaDExtensionType((1, 3)							,    """int64"""   )   )





		def    UpperCAmelCase__							(					self   ) ->						List[Any]:







								'''simple docstring'''

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





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







								'''simple docstring'''

								snake_case_   : List[Any]						=			pa.array(TypedSequence([[[1, 2, 3]]]							,    try_type=ArrayaD((1, 3)							,    """int64"""   )   )   )
								self.assertEqual(arr.type							,    ArrayaDExtensionType((1, 3)							,    """int64"""   )   )





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







								'''simple docstring'''

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





		@require_pil
		def    UpperCAmelCase__							(					self   ) ->						List[str]:







								'''simple docstring'''

								import PIL.Image

								snake_case_   : int						=			PIL.Image.fromarray(np.arange(1_0							,    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_   : Any						=			pa.array(TypedSequence([{"""path""": None, """bytes""": b"""image_bytes"""}, pil_image]							,    type=Image()   )   )
														snake_case_   : List[Any]						=			mock_cast_to_python_objects.call_args_list[-1]
														self.assertIn("""optimize_list_casting"""							,    _lowercase   )
														self.assertFalse(kwargs["""optimize_list_casting"""]   )




def 	__lowerCAmelCase						(		__UpperCamelCase      :			Tuple					, __UpperCamelCase      :			int    ):


						'''simple docstring'''






						snake_case_   : List[str]						=			pa.BufferReader(__UpperCamelCase    ) if isinstance(__UpperCamelCase					, pa.Buffer    ) else pa.memory_map(__UpperCamelCase    )
						snake_case_   : Optional[Any]						=			pa.ipc.open_stream(__UpperCamelCase    )
						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, 1_0]    )
@pytest.mark.parametrize(
    """fields"""					, [None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Tuple					, __UpperCamelCase      :			Union[str, Any]    ):


						'''simple docstring'''






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


						'''simple docstring'''






						snake_case_   : Union[str, Any]						=			pa.BufferOutputStream()
						snake_case_   : Optional[Any]						=			Features({"""labels""": ClassLabel(names=["""neg""", """pos"""]    )}    )
						with ArrowWriter(stream=__UpperCamelCase					, features=__UpperCamelCase    ) as writer:
												writer.write({"""labels""": 0}    )
												writer.write({"""labels""": 1}    )
												snake_case_   : int						=			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_   : int						=			pa.BufferReader(output.getvalue()    )
						snake_case_   : Optional[int]						=			pa.ipc.open_stream(__UpperCamelCase    )
						snake_case_   : pa.Table						=			f.read_all()
						snake_case_   : Optional[int]						=			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(__UpperCamelCase    )
@pytest.mark.parametrize("""writer_batch_size"""					, [None, 1, 1_0]    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Tuple    ):


						'''simple docstring'''






						snake_case_   : int						=			pa.BufferOutputStream()
						with ArrowWriter(
						    stream=__UpperCamelCase					, writer_batch_size=__UpperCamelCase					, hash_salt="""split_name"""					, check_duplicates=__UpperCamelCase					, ) as writer:
												with pytest.raises(__UpperCamelCase    ):
																		writer.write({"""col_1""": """foo""", """col_2""": 1}					, key=[1, 2]    )
																		snake_case_   : List[Any]						=			writer.finalize()
@pytest.mark.parametrize("""writer_batch_size"""					, [None, 2, 1_0]    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			str    ):


						'''simple docstring'''






						snake_case_   : List[str]						=			pa.BufferOutputStream()
						with ArrowWriter(
						    stream=__UpperCamelCase					, writer_batch_size=__UpperCamelCase					, hash_salt="""split_name"""					, check_duplicates=__UpperCamelCase					, ) as writer:
												with pytest.raises(__UpperCamelCase    ):
																		writer.write({"""col_1""": """foo""", """col_2""": 1}					, key=1_0    )
																		writer.write({"""col_1""": """bar""", """col_2""": 2}					, key=1_0    )
																		snake_case_   : Dict						=			writer.finalize()
@pytest.mark.parametrize("""writer_batch_size"""					, [None, 2, 1_0]    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			List[str]    ):


						'''simple docstring'''






						snake_case_   : List[Any]						=			pa.BufferOutputStream()
						with ArrowWriter(
						    stream=__UpperCamelCase					, writer_batch_size=__UpperCamelCase					, hash_salt="""split_name"""					, check_duplicates=__UpperCamelCase					, ) as writer:
												writer.write({"""col_1""": """foo""", """col_2""": 1}					, key=1    )
												writer.write({"""col_1""": """bar""", """col_2""": 2}					, key=2    )
												snake_case_   : List[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, 1_0]    )
@pytest.mark.parametrize(
    """fields"""					, [None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			int					, __UpperCamelCase      :			Optional[int]    ):


						'''simple docstring'''






						snake_case_   : Union[str, Any]						=			pa.BufferOutputStream()
						snake_case_   : int						=			pa.schema(__UpperCamelCase    ) if fields else None
						with ArrowWriter(stream=__UpperCamelCase					, schema=__UpperCamelCase					, writer_batch_size=__UpperCamelCase    ) as writer:
												writer.write_batch({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}    )
												writer.write_batch({"""col_1""": [], """col_2""": []}    )
												snake_case_   : List[Any]						=			writer.finalize()
						assert num_examples == 2
						assert num_bytes > 0
						if not fields:
												snake_case_   : Tuple						=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
						assert writer._schema == pa.schema(__UpperCamelCase					, 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, 1_0]    )
@pytest.mark.parametrize(
    """fields"""					, [None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			str					, __UpperCamelCase      :			int    ):


						'''simple docstring'''






						snake_case_   : Union[str, Any]						=			pa.BufferOutputStream()
						snake_case_   : str						=			pa.schema(__UpperCamelCase    ) if fields else None
						with ArrowWriter(stream=__UpperCamelCase					, schema=__UpperCamelCase					, writer_batch_size=__UpperCamelCase    ) as writer:
												writer.write_table(pa.Table.from_pydict({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}    )    )
												snake_case_   : Dict						=			writer.finalize()
						assert num_examples == 2
						assert num_bytes > 0
						if not fields:
												snake_case_   : List[str]						=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
						assert writer._schema == pa.schema(__UpperCamelCase					, 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, 1_0]    )
@pytest.mark.parametrize(
    """fields"""					, [None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			str					, __UpperCamelCase      :			Dict    ):


						'''simple docstring'''






						snake_case_   : str						=			pa.BufferOutputStream()
						snake_case_   : Optional[int]						=			pa.schema(__UpperCamelCase    ) if fields else None
						with ArrowWriter(stream=__UpperCamelCase					, schema=__UpperCamelCase					, writer_batch_size=__UpperCamelCase    ) 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_   : Optional[Any]						=			writer.finalize()
						assert num_examples == 2
						assert num_bytes > 0
						if not fields:
												snake_case_   : List[Any]						=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
						assert writer._schema == pa.schema(__UpperCamelCase					, 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:
												snake_case_   : str						=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
												snake_case_   : Any						=			os.path.join(__UpperCamelCase					, """test.arrow"""    )
												with ArrowWriter(path=__UpperCamelCase					, schema=pa.schema(__UpperCamelCase    )    ) as writer:
																		writer.write_batch({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}    )
																		snake_case_   : Dict						=			writer.finalize()
												assert num_examples == 2
												assert num_bytes > 0
												assert writer._schema == pa.schema(__UpperCamelCase					, metadata=writer._schema.metadata    )
												_check_output(__UpperCamelCase					, 1    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			Any    ):


						'''simple docstring'''






						if pa.types.is_list(__UpperCamelCase    ):
												return get_base_dtype(arr_type.value_type    )
						else:
												return arr_type
def 	__lowerCAmelCase						(		__UpperCamelCase      :			int					, __UpperCamelCase      :			Dict    ):


						'''simple docstring'''






						if isinstance(lst[0]					, __UpperCamelCase    ):
												change_first_primitive_element_in_list(lst[0]					, __UpperCamelCase    )
						else:
												snake_case_   : Tuple						=			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						(		__UpperCamelCase      :			Any					, __UpperCamelCase      :			List[str]					, __UpperCamelCase      :			List[str]    ):


						'''simple docstring'''






						snake_case_   : str						=			pa.array(TypedSequence(__UpperCamelCase					, optimized_int_type=__UpperCamelCase    )    )
						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						(		__UpperCamelCase      :			Dict					, __UpperCamelCase      :			str					, __UpperCamelCase      :			List[Any]    ):


						'''simple docstring'''






						snake_case_   : List[str]						=			pa.array(OptimizedTypedSequence(__UpperCamelCase					, col=__UpperCamelCase    )    )
						assert get_base_dtype(arr.type    ) == expected_dtype

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


						'''simple docstring'''






						snake_case_   : List[str]						=			str(tmp_path / """dataset-train.arrow"""    )
						try:
												with ArrowWriter(path=__UpperCamelCase    ) 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						(		__UpperCamelCase      :			Tuple    ):


						'''simple docstring'''






						snake_case_   : List[Any]						=			"""mock://dataset-train.arrow"""
						with ArrowWriter(path=__UpperCamelCase					, storage_options=mockfs.storage_options    ) as writer:
												assert isinstance(writer._fs					, type(__UpperCamelCase    )    )
												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_   : int						=			writer.finalize()
						assert num_examples == 2
						assert num_bytes > 0
						assert mockfs.exists(__UpperCamelCase    )
def 	__lowerCAmelCase						(		):


						'''simple docstring'''






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


						'''simple docstring'''






						import PIL.Image

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






						snake_case_   : Tuple						=			pa.schema([pa.field("""col_1"""					, pa.string()					, nullable=__UpperCamelCase    )]    )
						snake_case_   : Optional[Any]						=			pa.BufferOutputStream()
						with ArrowWriter(stream=__UpperCamelCase    ) as writer:
												writer._build_writer(inferred_schema=__UpperCamelCase    )
												assert writer._schema == pa.schema([pa.field("""col_1"""					, pa.string()    )]    )






"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__lowerCAmelCase       :					Tuple      					=					logging.get_logger(__name__)

__lowerCAmelCase       :					Dict      					=					{
    '''microsoft/swin-tiny-patch4-window7-224''': (
        '''https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json'''
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}



class    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__  ,				SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase			  =       '''swin'''

		_lowerCamelCase			  =       {
		    '''num_attention_heads''': '''num_heads''',
		    '''num_hidden_layers''': '''num_layers''',
		}





		def __init__(					self							,    _lowercase=2_2_4							,    _lowercase=4							,    _lowercase=3							,    _lowercase=9_6							,    _lowercase=[2, 2, 6, 2]							,    _lowercase=[3, 6, 1_2, 2_4]							,    _lowercase=7							,    _lowercase=4.0							,    _lowercase=True							,    _lowercase=0.0							,    _lowercase=0.0							,    _lowercase=0.1							,    _lowercase="gelu"							,    _lowercase=False							,    _lowercase=0.02							,    _lowercase=1E-5							,    _lowercase=3_2							,    _lowercase=None							,    _lowercase=None							,    **_lowercase							,    ) ->						Union[str, Any]:







								'''simple docstring'''

								super().__init__(**_lowercase   )

								snake_case_   : str						=			image_size
								snake_case_   : int						=			patch_size
								snake_case_   : Optional[int]						=			num_channels
								snake_case_   : Union[str, Any]						=			embed_dim
								snake_case_   : Optional[int]						=			depths
								snake_case_   : Optional[int]						=			len(_lowercase   )
								snake_case_   : Optional[Any]						=			num_heads
								snake_case_   : Optional[Any]						=			window_size
								snake_case_   : Optional[Any]						=			mlp_ratio
								snake_case_   : Optional[Any]						=			qkv_bias
								snake_case_   : Optional[Any]						=			hidden_dropout_prob
								snake_case_   : Tuple						=			attention_probs_dropout_prob
								snake_case_   : Union[str, Any]						=			drop_path_rate
								snake_case_   : List[Any]						=			hidden_act
								snake_case_   : str						=			use_absolute_embeddings
								snake_case_   : str						=			layer_norm_eps
								snake_case_   : Optional[Any]						=			initializer_range
								snake_case_   : Any						=			encoder_stride
								# we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
								# this indicates the channel dimension after the last stage of the model
								snake_case_   : Tuple						=			int(embed_dim * 2 ** (len(_lowercase   ) - 1)   )
								snake_case_   : Tuple						=			["""stem"""] + [f'stage{idx}' for idx in range(1							,    len(_lowercase   ) + 1   )]
								snake_case_			,		snake_case_   : Any						=			get_aligned_output_features_output_indices(
								    out_features=_lowercase							,    out_indices=_lowercase							,    stage_names=self.stage_names   )




class    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase			  =       version.parse('''1.11'''		)





		@property
		def    UpperCAmelCase__							(					self   ) ->						Mapping[str, Mapping[int, str]]:







								'''simple docstring'''

								return OrderedDict(
								    [
								        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
								    ]   )





		@property
		def    UpperCAmelCase__							(					self   ) ->						float:







								'''simple docstring'''

								return 1E-4

