



"""simple docstring"""

from ....configuration_utils import PretrainedConfig
from ....utils import logging


lowercase__			   =  logging.get_logger(__name__)

lowercase__			   =  {
    "Visual-Attention-Network/van-base": (
        "https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json"
    ),
}




class SCREAMING_SNAKE_CASE__					(		__snake_case      ):
						_lowerCAmelCase							=					"van"



						def __init__(self						,     _lowercase=224						,     _lowercase=3						,     _lowercase=[7, 3, 3, 3]						,     _lowercase=[4, 2, 2, 2]						,     _lowercase=[64, 128, 320, 512]						,     _lowercase=[3, 3, 12, 3]						,     _lowercase=[8, 8, 4, 4]						,     _lowercase="gelu"						,     _lowercase=0.02						,     _lowercase=1e-6						,     _lowercase=1e-2						,     _lowercase=0.0						,     _lowercase=0.0						,     **_lowercase						,     ):





													'''simple docstring'''

													super().__init__(**_lowercase							)
													__a		:		Optional[Any]									=       image_size
													__a		:		int									=       num_channels
													__a		:		Dict									=       patch_sizes
													__a		:		int									=       strides
													__a		:		List[str]									=       hidden_sizes
													__a		:		Optional[int]									=       depths
													__a		:		Any									=       mlp_ratios
													__a		:		List[Any]									=       hidden_act
													__a		:		Tuple									=       initializer_range
													__a		:		List[str]									=       layer_norm_eps
													__a		:		Tuple									=       layer_scale_init_value
													__a		:		Optional[Any]									=       drop_path_rate
													__a		:		Optional[int]									=       dropout_rate






"""simple docstring"""

from typing import TYPE_CHECKING

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


lowercase__			   =  {
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

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

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

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

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

