




'''simple docstring'''





from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE							:   Optional[int]      		= {
    'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LlamaConfig'],
}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_SCREAMING_SNAKE_CASE							:   List[Any]      		= ['LlamaTokenizer']

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_SCREAMING_SNAKE_CASE							:   List[str]      		= ['LlamaTokenizerFast']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_SCREAMING_SNAKE_CASE							:   Union[str, 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

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





from typing import TYPE_CHECKING

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


__UpperCamelCase		:       List[Any]									=     {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       Optional[Any]									=     ['GLPNFeatureExtractor']
					__UpperCamelCase		:       List[str]									=     ['GLPNImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       str									=     [
					    'GLPN_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'GLPNForDepthEstimation',
					    'GLPNLayer',
					    'GLPNModel',
					    'GLPNPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_glpn import GLPNFeatureExtractor
										from .image_processing_glpn import GLPNImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_glpn import (
										    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GLPNForDepthEstimation,
										    GLPNLayer,
										    GLPNModel,
										    GLPNPreTrainedModel,
										)


else:
					import sys

					__UpperCamelCase		:       Optional[Any]									=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





