
"""simple docstring"""







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


lowerCamelCase__        =		logging.get_logger(__name__)




class 			A__	(     _lowerCamelCase	,					_lowerCamelCase):
		A_						:	Dict           =     'maskformer-swin'

		A_						:	str           =     {
		    'num_attention_heads': 'num_heads',
		    'num_hidden_layers': 'num_layers',
		}

		def __init__(				self	,		_SCREAMING_SNAKE_CASE=2_24	,		_SCREAMING_SNAKE_CASE=4	,		_SCREAMING_SNAKE_CASE=3	,		_SCREAMING_SNAKE_CASE=96	,		_SCREAMING_SNAKE_CASE=[2, 2, 6, 2]	,		_SCREAMING_SNAKE_CASE=[3, 6, 12, 24]	,		_SCREAMING_SNAKE_CASE=7	,		_SCREAMING_SNAKE_CASE=4.0	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=0.0	,		_SCREAMING_SNAKE_CASE=0.0	,		_SCREAMING_SNAKE_CASE=0.1	,		_SCREAMING_SNAKE_CASE="gelu"	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=0.02	,		_SCREAMING_SNAKE_CASE=1E-5	,		_SCREAMING_SNAKE_CASE=None	,		_SCREAMING_SNAKE_CASE=None	,		**_SCREAMING_SNAKE_CASE	,		):
			super().__init__(**_SCREAMING_SNAKE_CASE			)

			__lowerCAmelCase      :						Tuple						      =				image_size
			__lowerCAmelCase      :						str						      =				patch_size
			__lowerCAmelCase      :						List[Any]						      =				num_channels
			__lowerCAmelCase      :						Optional[Any]						      =				embed_dim
			__lowerCAmelCase      :						List[str]						      =				depths
			__lowerCAmelCase      :						List[str]						      =				len(_SCREAMING_SNAKE_CASE			)
			__lowerCAmelCase      :						Tuple						      =				num_heads
			__lowerCAmelCase      :						Optional[Any]						      =				window_size
			__lowerCAmelCase      :						Tuple						      =				mlp_ratio
			__lowerCAmelCase      :						Optional[int]						      =				qkv_bias
			__lowerCAmelCase      :						Union[str, Any]						      =				hidden_dropout_prob
			__lowerCAmelCase      :						Tuple						      =				attention_probs_dropout_prob
			__lowerCAmelCase      :						Tuple						      =				drop_path_rate
			__lowerCAmelCase      :						int						      =				hidden_act
			__lowerCAmelCase      :						List[Any]						      =				use_absolute_embeddings
			__lowerCAmelCase      :						List[str]						      =				layer_norm_eps
			__lowerCAmelCase      :						Tuple						      =				initializer_range
			# 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
			__lowerCAmelCase      :						Optional[Any]						      =				int(embed_dim * 2 ** (len(_SCREAMING_SNAKE_CASE			) - 1)			)
			__lowerCAmelCase      :						int						      =				['stem'] + [f"stage{idx}" for idx in range(1	,		len(_SCREAMING_SNAKE_CASE			) + 1			)]
			__lowerCAmelCase      ,       __lowerCAmelCase      :						Optional[int]						      =				get_aligned_output_features_output_indices(
			    out_features=_SCREAMING_SNAKE_CASE	,		out_indices=_SCREAMING_SNAKE_CASE	,		stage_names=self.stage_names			)

"""simple docstring"""







# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


lowerCamelCase__        =		logging.get_logger(__name__)

lowerCamelCase__        =		{}
lowerCamelCase__        =		{}
lowerCamelCase__        =		{}
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase	,  _UpperCamelCase = None	,  ):
	__lowerCAmelCase      :						Union[str, Any]						      =				aliases if aliases is not None else []
	if format_type in _FORMAT_TYPES:
		logger.warning(
		    F"Overwriting format type '{format_type}' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})"		)
	__lowerCAmelCase      :						str						      =				formatter_cls
	for alias in set(aliases + [format_type]		):
		if alias in _FORMAT_TYPES_ALIASES:
			logger.warning(
			    F"Overwriting format type alias '{alias}' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})"		)
		__lowerCAmelCase      :						Any						      =				format_type
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase	,  _UpperCamelCase = None		):
	__lowerCAmelCase      :						int						      =				aliases if aliases is not None else []
	for alias in set(aliases + [format_type]		):
		__lowerCAmelCase      :						str						      =				unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=["""python"""])
_register_formatter(ArrowFormatter, """arrow""", aliases=["""pa""", """pyarrow"""])
_register_formatter(NumpyFormatter, """numpy""", aliases=["""np"""])
_register_formatter(PandasFormatter, """pandas""", aliases=["""pd"""])
_register_formatter(CustomFormatter, """custom""")

if config.TORCH_AVAILABLE:
							from .torch_formatter import TorchFormatter

							_register_formatter(TorchFormatter, """torch""", aliases=["""pt""", """pytorch"""])
else:
							lowerCamelCase__        =		ValueError("""PyTorch needs to be installed to be able to return PyTorch tensors.""")
							_register_unavailable_formatter(_torch_error, """torch""", aliases=["""pt""", """pytorch"""])

if config.TF_AVAILABLE:
							from .tf_formatter import TFFormatter

							_register_formatter(TFFormatter, """tensorflow""", aliases=["""tf"""])
else:
							lowerCamelCase__        =		ValueError("""Tensorflow needs to be installed to be able to return Tensorflow tensors.""")
							_register_unavailable_formatter(_tf_error, """tensorflow""", aliases=["""tf"""])

if config.JAX_AVAILABLE:
							from .jax_formatter import JaxFormatter

							_register_formatter(JaxFormatter, """jax""", aliases=[])
else:
							lowerCamelCase__        =		ValueError("""JAX needs to be installed to be able to return JAX arrays.""")
							_register_unavailable_formatter(_jax_error, """jax""", aliases=[])
def    __lowerCAmelCase    (_UpperCamelCase		):
	if format_type in _FORMAT_TYPES_ALIASES:
		return _FORMAT_TYPES_ALIASES[format_type]
	else:
		return format_type
def    __lowerCAmelCase    (_UpperCamelCase	,  **_UpperCamelCase		):
	__lowerCAmelCase      :						Any						      =				get_format_type_from_alias(_UpperCamelCase		)
	if format_type in _FORMAT_TYPES:
		return _FORMAT_TYPES[format_type](**_UpperCamelCase		)
	if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
		raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
	else:
		raise ValueError(
		    F"Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None		)}, but got '{format_type}'"		)