




"""simple docstring"""







from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


a      =							logging.get_logger(__name__)

a      =							{
    't5-small': 'https://huggingface.co/t5-small/resolve/main/config.json',
    't5-base': 'https://huggingface.co/t5-base/resolve/main/config.json',
    't5-large': 'https://huggingface.co/t5-large/resolve/main/config.json',
    't5-3b': 'https://huggingface.co/t5-3b/resolve/main/config.json',
    't5-11b': 'https://huggingface.co/t5-11b/resolve/main/config.json',
}






class       SCREAMING_SNAKE_CASE__					(					_a					):
						_a    						=						't5'
						_a    						=						['past_key_values']
						_a    						=						{'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}


						def __init__(							self				:			Dict						,						lowerCAmelCase				:			Optional[Any]=3_2128						,						lowerCAmelCase				:			Tuple=512						,						lowerCAmelCase				:			int=64						,						lowerCAmelCase				:			Dict=2048						,						lowerCAmelCase				:			Any=6						,						lowerCAmelCase				:			List[str]=None						,						lowerCAmelCase				:			Tuple=8						,						lowerCAmelCase				:			int=32						,						lowerCAmelCase				:			int=128						,						lowerCAmelCase				:			Tuple=0.1						,						lowerCAmelCase				:			Dict=1e-6						,						lowerCAmelCase				:			int=1.0						,						lowerCAmelCase				:			List[Any]="relu"						,						lowerCAmelCase				:			Optional[Any]=True						,						lowerCAmelCase				:			Any=True						,						lowerCAmelCase				:			Optional[Any]=0						,						lowerCAmelCase				:			Optional[int]=1						,						**lowerCAmelCase				:			List[Any]						,						):
										lowerCAmelCase  =				vocab_size
										lowerCAmelCase  =				d_model
										lowerCAmelCase  =				d_kv
										lowerCAmelCase  =				d_ff
										lowerCAmelCase  =				num_layers
										lowerCAmelCase  =				(
										    num_decoder_layers if num_decoder_layers is not None else self.num_layers
										)  # default = symmetry
										lowerCAmelCase  =				num_heads
										lowerCAmelCase  =				relative_attention_num_buckets
										lowerCAmelCase  =				relative_attention_max_distance
										lowerCAmelCase  =				dropout_rate
										lowerCAmelCase  =				layer_norm_epsilon
										lowerCAmelCase  =				initializer_factor
										lowerCAmelCase  =				feed_forward_proj
										lowerCAmelCase  =				use_cache

										lowerCAmelCase  =				self.feed_forward_proj.split("""-"""					)
										lowerCAmelCase  =				act_info[-1]
										lowerCAmelCase  =				act_info[0] == """gated"""

										if len(lowerCAmelCase					) > 1 and act_info[0] != "gated" or len(lowerCAmelCase					) > 2:
														raise ValueError(
														    f'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
														    """Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. """
														    """'gated-gelu' or 'relu'"""					)

										# for backwards compatibility
										if feed_forward_proj == "gated-gelu":
														lowerCAmelCase  =				"""gelu_new"""

										super().__init__(
										    pad_token_id=lowerCAmelCase						,						eos_token_id=lowerCAmelCase						,						is_encoder_decoder=lowerCAmelCase						,						**lowerCAmelCase						,						)






class       SCREAMING_SNAKE_CASE__					(					_a					):


						@property
						def   __lowercase (							self				:			str					):
										lowerCAmelCase  =				{
										    """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
										    """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
										}
										if self.use_past:
														lowerCAmelCase  =				"""past_encoder_sequence + sequence"""
														lowerCAmelCase  =				{0: """batch"""}
														lowerCAmelCase  =				{0: """batch""", 1: """past_decoder_sequence + sequence"""}
										else:
														lowerCAmelCase  =				{0: """batch""", 1: """decoder_sequence"""}
														lowerCAmelCase  =				{0: """batch""", 1: """decoder_sequence"""}

										if self.use_past:
														self.fill_with_past_key_values_(lowerCAmelCase						,						direction="""inputs"""					)

										return common_inputs




						@property
						def   __lowercase (							self				:			Optional[Any]					):
										return 13











"""simple docstring"""







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_owlvit': [
        'OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'OwlViTConfig',
        'OwlViTOnnxConfig',
        'OwlViTTextConfig',
        'OwlViTVisionConfig',
    ],
    'processing_owlvit': ['OwlViTProcessor'],
}


try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a      =							['OwlViTFeatureExtractor']
		a      =							['OwlViTImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a      =							[
		    'OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'OwlViTModel',
		    'OwlViTPreTrainedModel',
		    'OwlViTTextModel',
		    'OwlViTVisionModel',
		    'OwlViTForObjectDetection',
		]

if TYPE_CHECKING:
		from .configuration_owlvit import (
		    OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    OwlViTConfig,
		    OwlViTOnnxConfig,
		    OwlViTTextConfig,
		    OwlViTVisionConfig,
		)
		from .processing_owlvit import OwlViTProcessor

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_owlvit import OwlViTFeatureExtractor
				from .image_processing_owlvit import OwlViTImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_owlvit import (
				    OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    OwlViTForObjectDetection,
				    OwlViTModel,
				    OwlViTPreTrainedModel,
				    OwlViTTextModel,
				    OwlViTVisionModel,
				)

else:
		import sys

		a      =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





