
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
__lowerCAmelCase       :      Optional[int]         =		object()

# For specifying empty leaf dict `{}`
__lowerCAmelCase       :      List[str]         =		object()


def      UpperCAmelCase_	(    __lowerCAmelCase						,       __lowerCAmelCase						)			->    Tuple:
    __lowercase		:      List[Any]						     =							tuple((re.compile(x + '''$'''						) for x in qs)						)
    for i in range(len(__A						) - len(__A						) + 1						):
        __lowercase		:      Union[str, Any]						     =							[x.match(__A						) for x, y in zip(__A						,       ks[i:]						)]
        if matches and all(__A						):
            return True
    return False


def      UpperCAmelCase_	(    __lowerCAmelCase						)			->    List[str]:
    def replace(__lowerCAmelCase						,       __lowerCAmelCase						):
        for rule, replacement in rules:
            if _match(__A						,       __A						):
                return replacement
        return val

    return replace


def      UpperCAmelCase_	(    )			->    List[Any]:
    return [
        # embeddings
        (("transformer", "wpe", "embedding"), P('''mp'''						,       __A						)),
        (("transformer", "wte", "embedding"), P('''mp'''						,       __A						)),
        # atention
        (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(__A						,       '''mp'''						)),
        (("attention", "out_proj", "kernel"), P('''mp'''						,       __A						)),
        (("attention", "out_proj", "bias"), None),
        # mlp
        (("mlp", "c_fc", "kernel"), P(__A						,       '''mp'''						)),
        (("mlp", "c_fc", "bias"), P('''mp'''						)),
        (("mlp", "c_proj", "kernel"), P('''mp'''						,       __A						)),
        (("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      UpperCAmelCase_	(    __lowerCAmelCase						)			->    str:
    __lowercase		:      Tuple						     =							_get_partition_rules()
    __lowercase		:      Tuple						     =							_replacement_rules(__A						)
    __lowercase		:      Optional[Any]						     =							{k: _unmatched for k in flatten_dict(__A						)}
    __lowercase		:      Optional[Any]						     =							{k: replace(__A						,       __A						) for k, v in initd.items()}
    assert _unmatched not in result.values(), "Incomplete partition spec."
    return freeze(unflatten_dict(__A						)						)










'''simple docstring'''







from typing import TYPE_CHECKING

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


__lowerCAmelCase									=   {'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DeiTConfig', 'DeiTOnnxConfig']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase									=   ['DeiTFeatureExtractor']
		__lowerCAmelCase									=   ['DeiTImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase									=   [
		    'DEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'DeiTForImageClassification',
		    'DeiTForImageClassificationWithTeacher',
		    'DeiTForMaskedImageModeling',
		    'DeiTModel',
		    'DeiTPreTrainedModel',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase									=   [
		    'TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TFDeiTForImageClassification',
		    'TFDeiTForImageClassificationWithTeacher',
		    'TFDeiTForMaskedImageModeling',
		    'TFDeiTModel',
		    'TFDeiTPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_deit import DeiTFeatureExtractor
				from .image_processing_deit import DeiTImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_deit import (
				    DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DeiTForImageClassification,
				    DeiTForImageClassificationWithTeacher,
				    DeiTForMaskedImageModeling,
				    DeiTModel,
				    DeiTPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_deit import (
				    TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFDeiTForImageClassification,
				    TFDeiTForImageClassificationWithTeacher,
				    TFDeiTForMaskedImageModeling,
				    TFDeiTModel,
				    TFDeiTPreTrainedModel,
				)


else:
		import sys

		__lowerCAmelCase									=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




