


from typing import Mapping

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


UpperCAmelCase      =   logging.get_logger(__name__)

UpperCAmelCase      =   {
    """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 lowerCAmelCase_						(			lowerCamelCase__	):

 '''simple docstring'''

 __snake_case												=  "t5"
 __snake_case												=  ["past_key_values"]
 __snake_case												=  {"hidden_size": "d_model", "num_attention_heads": "num_heads", "num_hidden_layers": "num_layers"}



 def __init__(     self		,				_UpperCAmelCase=3_21_28		,				_UpperCAmelCase=5_12		,				_UpperCAmelCase=64		,				_UpperCAmelCase=20_48		,				_UpperCAmelCase=6		,				_UpperCAmelCase=None		,				_UpperCAmelCase=8		,				_UpperCAmelCase=32		,				_UpperCAmelCase=1_28		,				_UpperCAmelCase=0.1		,				_UpperCAmelCase=1E-6		,				_UpperCAmelCase=1.0		,				_UpperCAmelCase="relu"		,				_UpperCAmelCase=True		,				_UpperCAmelCase=True		,				_UpperCAmelCase=0		,				_UpperCAmelCase=1		,				**_UpperCAmelCase		,				):
       snake_case_	=				vocab_size
       snake_case_	=				d_model
       snake_case_	=				d_kv
       snake_case_	=				d_ff
       snake_case_	=				num_layers
       snake_case_	=				(
           num_decoder_layers if num_decoder_layers is not None else self.num_layers
       )  # default = symmetry
       snake_case_	=				num_heads
       snake_case_	=				relative_attention_num_buckets
       snake_case_	=				relative_attention_max_distance
       snake_case_	=				dropout_rate
       snake_case_	=				layer_norm_epsilon
       snake_case_	=				initializer_factor
       snake_case_	=				feed_forward_proj
       snake_case_	=				use_cache

       snake_case_	=				self.feed_forward_proj.split('''-''' )
       snake_case_	=				act_info[-1]
       snake_case_	=				act_info[0] == '''gated'''

       if len(_UpperCAmelCase ) > 1 and act_info[0] != "gated" or len(_UpperCAmelCase ) > 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":
             snake_case_	=				'''gelu_new'''

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







class lowerCAmelCase_						(			lowerCamelCase__	):

 '''simple docstring'''

 @property
 def 						UpperCamelCase__					(     self ):
       snake_case_	=				{
           '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
           '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
       }
       if self.use_past:
             snake_case_	=				'''past_encoder_sequence + sequence'''
             snake_case_	=				{0: '''batch'''}
             snake_case_	=				{0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
       else:
             snake_case_	=				{0: '''batch''', 1: '''decoder_sequence'''}
             snake_case_	=				{0: '''batch''', 1: '''decoder_sequence'''}

       if self.use_past:
             self.fill_with_past_key_values_(_UpperCAmelCase		,				direction='''inputs''' )

       return common_inputs





 @property
 def 						UpperCamelCase__					(     self ):
       return 13



from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase      =   logging.get_logger(__name__)

UpperCAmelCase      =   {
    """facebook/convnextv2-tiny-1k-224""": """https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json""",
}







class lowerCAmelCase_						(			lowerCamelCase__ ,						lowerCamelCase__	):

 '''simple docstring'''

 __snake_case												=  "convnextv2"



 def __init__(     self		,				_UpperCAmelCase=3		,				_UpperCAmelCase=4		,				_UpperCAmelCase=4		,				_UpperCAmelCase=None		,				_UpperCAmelCase=None		,				_UpperCAmelCase="gelu"		,				_UpperCAmelCase=0.02		,				_UpperCAmelCase=1E-12		,				_UpperCAmelCase=0.0		,				_UpperCAmelCase=2_24		,				_UpperCAmelCase=None		,				_UpperCAmelCase=None		,				**_UpperCAmelCase		,				):
       super().__init__(**_UpperCAmelCase )

       snake_case_	=				num_channels
       snake_case_	=				patch_size
       snake_case_	=				num_stages
       snake_case_	=				[96, 1_92, 3_84, 7_68] if hidden_sizes is None else hidden_sizes
       snake_case_	=				[3, 3, 9, 3] if depths is None else depths
       snake_case_	=				hidden_act
       snake_case_	=				initializer_range
       snake_case_	=				layer_norm_eps
       snake_case_	=				drop_path_rate
       snake_case_	=				image_size
       snake_case_	=				['''stem'''] + [F'''stage{idx}''' for idx in range(1		,				len(self.depths ) + 1 )]
       snake_case_	,   snake_case_	=				get_aligned_output_features_output_indices(
           out_features=_UpperCAmelCase		,				out_indices=_UpperCAmelCase		,				stage_names=self.stage_names )