


'''simple docstring'''
from typing import TYPE_CHECKING

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


lowerCAmelCase   : Optional[Any]             =				{
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase   : Optional[int]             =				["""LlamaTokenizer"""]

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase   : Dict             =				["""LlamaTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase   : List[Any]             =				[
					    """LlamaForCausalLM""",
					    """LlamaModel""",
					    """LlamaPreTrainedModel""",
					    """LlamaForSequenceClassification""",
					]


if TYPE_CHECKING:
					from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_llama import LlamaTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_llama_fast import LlamaTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
					import sys

					lowerCAmelCase   : Union[str, Any]             =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






'''simple docstring'''
from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCAmelCase   : Dict             =				{"""configuration_van""": ["""VAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VanConfig"""]}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase   : int             =				[
					    """VAN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """VanForImageClassification""",
					    """VanModel""",
					    """VanPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_van import (
										    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    VanForImageClassification,
										    VanModel,
										    VanPreTrainedModel,
										)

else:
					import sys

					lowerCAmelCase   : Tuple             =				_LazyModule(__name__, globals()["""__file__"""], _import_structure)


