'''simple docstring'''




import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
_lowercase		:				Dict	       =		object()

# For specifying empty leaf dict `{}`
_lowercase		:				Any	       =		object()




def 							lowerCamelCase			(   UpperCAmelCase__ :      List[str]   ,   UpperCAmelCase__ :      List[str]				)    ->   Dict:
							lowercase_      :    str       		= tuple((re.compile(x + """$"""				) for x in qs)				)
							for i in range(len(UpperCAmelCase__				) - len(UpperCAmelCase__				) + 1				):
														lowercase_      :    Any       		= [x.match(UpperCAmelCase__				) for x, y in zip(UpperCAmelCase__   ,   ks[i:]				)]
														if matches and all(UpperCAmelCase__				):
																					return True
							return False




def 							lowerCamelCase			(   UpperCAmelCase__ :      Optional[Any]				)    ->   List[Any]:
							def replace(UpperCAmelCase__ :      List[Any]   ,   UpperCAmelCase__ :      Any				):
														for rule, replacement in rules:
																					if _match(UpperCAmelCase__   ,   UpperCAmelCase__				):
																												return replacement
														return val

							return replace




def 							lowerCamelCase			(   )    ->   Union[str, Any]:
							return [
							    # embeddings
							    (("transformer", "wpe", "embedding"), P("""mp"""   ,   UpperCAmelCase__				)),
							    (("transformer", "wte", "embedding"), P("""mp"""   ,   UpperCAmelCase__				)),
							    # atention
							    (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(UpperCAmelCase__   ,   """mp"""				)),
							    (("attention", "out_proj", "kernel"), P("""mp"""   ,   UpperCAmelCase__				)),
							    (("attention", "out_proj", "bias"), None),
							    # mlp
							    (("mlp", "c_fc", "kernel"), P(UpperCAmelCase__   ,   """mp"""				)),
							    (("mlp", "c_fc", "bias"), P("""mp"""				)),
							    (("mlp", "c_proj", "kernel"), P("""mp"""   ,   UpperCAmelCase__				)),
							    (("mlp", "c_proj", "bias"), None),
							    # layer norms
							    ((r"ln_\d+", "bias"), None),
							    ((r"\d+", r"ln_\d+", "scale"), None),
							    (("ln_f", "bias"), None),
							    (("ln_f", "scale"), None),
							]




def 							lowerCamelCase			(   UpperCAmelCase__ :      List[str]				)    ->   str:
							lowercase_      :    Dict       		= _get_partition_rules()
							lowercase_      :    Optional[int]       		= _replacement_rules(UpperCAmelCase__				)
							lowercase_      :    Dict       		= {k: _unmatched for k in flatten_dict(UpperCAmelCase__				)}
							lowercase_      :    Tuple       		= {k: replace(UpperCAmelCase__   ,   UpperCAmelCase__				) for k, v in initd.items()}
							assert _unmatched not in result.values(), "Incomplete partition spec."
							return freeze(unflatten_dict(UpperCAmelCase__				)				)






'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_lowercase		:				Optional[Any]	       =		{
    "configuration_swiftformer": [
        "SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SwiftFormerConfig",
        "SwiftFormerOnnxConfig",
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase		:				Any	       =		[
						    "SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SwiftFormerForImageClassification",
						    "SwiftFormerModel",
						    "SwiftFormerPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_swiftformer import (
						    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SwiftFormerConfig,
						    SwiftFormerOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_swiftformer import (
												    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SwiftFormerForImageClassification,
												    SwiftFormerModel,
												    SwiftFormerPreTrainedModel,
												)

else:
						import sys

						_lowercase		:				Optional[int]	       =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





