






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


a__       =     logging.get_logger(__name__)

a__       =     {
    """vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}


class    _lowerCAmelCase			(		lowercase_      ):



				"""simple docstring"""



				_lowercase				:   Optional[int]      =  '''glpn'''



				def __init__(      self    :    Any			,		UpperCamelCase__    :    List[str]=3			,		UpperCamelCase__    :    Tuple=4			,		UpperCamelCase__    :    int=[2, 2, 2, 2]			,		UpperCamelCase__    :    Tuple=[8, 4, 2, 1]			,		UpperCamelCase__    :    int=[3_2, 6_4, 1_6_0, 2_5_6]			,		UpperCamelCase__    :    Dict=[7, 3, 3, 3]			,		UpperCamelCase__    :    Union[str, Any]=[4, 2, 2, 2]			,		UpperCamelCase__    :    List[Any]=[1, 2, 5, 8]			,		UpperCamelCase__    :    Optional[int]=[4, 4, 4, 4]			,		UpperCamelCase__    :    Optional[int]="gelu"			,		UpperCamelCase__    :    int=0.0			,		UpperCamelCase__    :    int=0.0			,		UpperCamelCase__    :    Dict=0.02			,		UpperCamelCase__    :    str=0.1			,		UpperCamelCase__    :    Dict=1E-6			,		UpperCamelCase__    :    Union[str, Any]=6_4			,		UpperCamelCase__    :    int=1_0			,		UpperCamelCase__    :    Tuple=-1			,		**UpperCamelCase__    :    Optional[Any]			,		):






											'''simple docstring'''







											super().__init__(**UpperCamelCase__)

											snake_case__	  =       num_channels
											snake_case__	  =       num_encoder_blocks
											snake_case__	  =       depths
											snake_case__	  =       sr_ratios
											snake_case__	  =       hidden_sizes
											snake_case__	  =       patch_sizes
											snake_case__	  =       strides
											snake_case__	  =       mlp_ratios
											snake_case__	  =       num_attention_heads
											snake_case__	  =       hidden_act
											snake_case__	  =       hidden_dropout_prob
											snake_case__	  =       attention_probs_dropout_prob
											snake_case__	  =       initializer_range
											snake_case__	  =       drop_path_rate
											snake_case__	  =       layer_norm_eps
											snake_case__	  =       decoder_hidden_size
											snake_case__	  =       max_depth
											snake_case__	  =       head_in_index








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


a__       =     {
    """configuration_clip""": [
        """CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """CLIPConfig""",
        """CLIPOnnxConfig""",
        """CLIPTextConfig""",
        """CLIPVisionConfig""",
    ],
    """processing_clip""": ["""CLIPProcessor"""],
    """tokenization_clip""": ["""CLIPTokenizer"""],
}

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

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     ["""CLIPFeatureExtractor"""]
	a__       =     ["""CLIPImageProcessor"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     [
	    """CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """CLIPModel""",
	    """CLIPPreTrainedModel""",
	    """CLIPTextModel""",
	    """CLIPTextModelWithProjection""",
	    """CLIPVisionModel""",
	    """CLIPVisionModelWithProjection""",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     [
	    """TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TFCLIPModel""",
	    """TFCLIPPreTrainedModel""",
	    """TFCLIPTextModel""",
	    """TFCLIPVisionModel""",
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     [
	    """FlaxCLIPModel""",
	    """FlaxCLIPPreTrainedModel""",
	    """FlaxCLIPTextModel""",
	    """FlaxCLIPTextPreTrainedModel""",
	    """FlaxCLIPVisionModel""",
	    """FlaxCLIPVisionPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_clip import (
	    CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    CLIPConfig,
	    CLIPOnnxConfig,
	    CLIPTextConfig,
	    CLIPVisionConfig,
	)
	from .processing_clip import CLIPProcessor
	from .tokenization_clip import CLIPTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_clip_fast import CLIPTokenizerFast

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_clip import CLIPFeatureExtractor
		from .image_processing_clip import CLIPImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_clip import (
		    CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    CLIPModel,
		    CLIPPreTrainedModel,
		    CLIPTextModel,
		    CLIPTextModelWithProjection,
		    CLIPVisionModel,
		    CLIPVisionModelWithProjection,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_clip import (
		    TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFCLIPModel,
		    TFCLIPPreTrainedModel,
		    TFCLIPTextModel,
		    TFCLIPVisionModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_clip import (
		    FlaxCLIPModel,
		    FlaxCLIPPreTrainedModel,
		    FlaxCLIPTextModel,
		    FlaxCLIPTextPreTrainedModel,
		    FlaxCLIPVisionModel,
		    FlaxCLIPVisionPreTrainedModel,
		)


else:
	import sys

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