
"""simple docstring"""







from typing import TYPE_CHECKING

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


lowerCamelCase__        =		{
    """configuration_swiftformer""": [
        """SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwiftFormerConfig""",
        """SwiftFormerOnnxConfig""",
    ]
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCamelCase__        =		[
							    """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

							lowerCamelCase__        =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

"""simple docstring"""







lowerCamelCase__        =		"""0.21.0"""

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
							from .utils import rich