




"""simple docstring"""

from typing import TYPE_CHECKING

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


UpperCamelCase__			:     Optional[Any]			       =				{"configuration_regnet": ["REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "RegNetConfig"]}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCamelCase__			:     Optional[int]			       =				[
		    "REGNET_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "RegNetForImageClassification",
		    "RegNetModel",
		    "RegNetPreTrainedModel",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCamelCase__			:     str			       =				[
		    "TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "TFRegNetForImageClassification",
		    "TFRegNetModel",
		    "TFRegNetPreTrainedModel",
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCamelCase__			:     Optional[int]			       =				[
		    "FlaxRegNetForImageClassification",
		    "FlaxRegNetModel",
		    "FlaxRegNetPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_regnet import (
				    REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RegNetForImageClassification,
				    RegNetModel,
				    RegNetPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_regnet import (
				    TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFRegNetForImageClassification,
				    TFRegNetModel,
				    TFRegNetPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_regnet import (
				    FlaxRegNetForImageClassification,
				    FlaxRegNetModel,
				    FlaxRegNetPreTrainedModel,
				)


else:
		import sys

		UpperCamelCase__			:     Optional[Any]			       =				_LazyModule(__name__, globals()["__file__"], _import_structure)








"""simple docstring"""

from .chunk_utils import chunk_layer
from .data_transforms import make_atomaa_masks
from .feats import atomaa_to_atomaa, frames_and_literature_positions_to_atomaa_pos, torsion_angles_to_frames
from .loss import compute_predicted_aligned_error, compute_tm
from .protein import Protein as OFProtein
from .protein import to_pdb
from .rigid_utils import Rigid, Rotation
from .tensor_utils import dict_multimap, flatten_final_dims, permute_final_dims


