from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE		:     Tuple         =	{
    "configuration_clipseg": [
        "CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "CLIPSegConfig",
        "CLIPSegTextConfig",
        "CLIPSegVisionConfig",
    ],
    "processing_clipseg": ["CLIPSegProcessor"],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	SCREAMING_SNAKE_CASE		:     List[str]         =	[
	    "CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "CLIPSegModel",
	    "CLIPSegPreTrainedModel",
	    "CLIPSegTextModel",
	    "CLIPSegVisionModel",
	    "CLIPSegForImageSegmentation",
	]

if TYPE_CHECKING:
	from .configuration_clipseg import (
	    CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    CLIPSegConfig,
	    CLIPSegTextConfig,
	    CLIPSegVisionConfig,
	)
	from .processing_clipseg import CLIPSegProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_clipseg import (
		    CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
		    CLIPSegForImageSegmentation,
		    CLIPSegModel,
		    CLIPSegPreTrainedModel,
		    CLIPSegTextModel,
		    CLIPSegVisionModel,
		)

else:
	import sys

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







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


SCREAMING_SNAKE_CASE		:     int         =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:     Union[str, Any]         =	{
    # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}

class        UpperCamelCase						(				__a				):
						a__		:List[str]      =			'''megatron-bert'''





						def __init__(self			,     __UpperCamelCase=29_056			,     __UpperCamelCase=1_024			,     __UpperCamelCase=24			,     __UpperCamelCase=16			,     __UpperCamelCase=4_096			,     __UpperCamelCase="gelu"			,     __UpperCamelCase=0.1			,     __UpperCamelCase=0.1			,     __UpperCamelCase=512			,     __UpperCamelCase=2			,     __UpperCamelCase=0.02			,     __UpperCamelCase=1E-1_2			,     __UpperCamelCase=0			,     __UpperCamelCase="absolute"			,     __UpperCamelCase=True			,     **__UpperCamelCase			,     )				->				List[Any]:
												super().__init__(pad_token_id=__UpperCamelCase			,     **__UpperCamelCase						)

												UpperCamelCase_		:							Union[str, Any]  =		vocab_size
												UpperCamelCase_		:							Union[str, Any]  =		hidden_size
												UpperCamelCase_		:							Any  =		num_hidden_layers
												UpperCamelCase_		:							str  =		num_attention_heads
												UpperCamelCase_		:							List[Any]  =		hidden_act
												UpperCamelCase_		:							Dict  =		intermediate_size
												UpperCamelCase_		:							Optional[int]  =		hidden_dropout_prob
												UpperCamelCase_		:							Dict  =		attention_probs_dropout_prob
												UpperCamelCase_		:							Any  =		max_position_embeddings
												UpperCamelCase_		:							str  =		type_vocab_size
												UpperCamelCase_		:							Tuple  =		initializer_range
												UpperCamelCase_		:							List[str]  =		layer_norm_eps
												UpperCamelCase_		:							Tuple  =		position_embedding_type
												UpperCamelCase_		:							Tuple  =		use_cache






