


from typing import Mapping

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


A	:		Dict    =       logging.get_logger(__name__)

A	:		List[str]    =       {
    '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 							A   (	UpperCAmelCase__							):
					'''simple docstring'''






					A__      =			'''t5'''
					A__      =			['''past_key_values''']
					A__      =			{'''hidden_size''': '''d_model''', '''num_attention_heads''': '''num_heads''', '''num_hidden_layers''': '''num_layers'''}

					def __init__(self   :						str				, _UpperCAmelCase   :						Optional[Any]=3_2128				, _UpperCAmelCase   :						Any=512				, _UpperCAmelCase   :						int=64				, _UpperCAmelCase   :						Any=2048				, _UpperCAmelCase   :						Optional[int]=6				, _UpperCAmelCase   :						Any=None				, _UpperCAmelCase   :						Any=8				, _UpperCAmelCase   :						Tuple=32				, _UpperCAmelCase   :						Tuple=128				, _UpperCAmelCase   :						Any=0.1				, _UpperCAmelCase   :						Any=1E-6				, _UpperCAmelCase   :						Union[str, Any]=1.0				, _UpperCAmelCase   :						Dict="relu"				, _UpperCAmelCase   :						Optional[int]=True				, _UpperCAmelCase   :						List[str]=True				, _UpperCAmelCase   :						Union[str, Any]=0				, _UpperCAmelCase   :						Tuple=1				, **_UpperCAmelCase   :						Tuple				, )						->       Union[str, Any]:




							"""simple docstring"""


							lowercase__					      =		vocab_size
							lowercase__					      =		d_model
							lowercase__					      =		d_kv
							lowercase__					      =		d_ff
							lowercase__					      =		num_layers
							lowercase__					      =		(
							    num_decoder_layers if num_decoder_layers is not None else self.num_layers
							)  # default = symmetry
							lowercase__					      =		num_heads
							lowercase__					      =		relative_attention_num_buckets
							lowercase__					      =		relative_attention_max_distance
							lowercase__					      =		dropout_rate
							lowercase__					      =		layer_norm_epsilon
							lowercase__					      =		initializer_factor
							lowercase__					      =		feed_forward_proj
							lowercase__					      =		use_cache

							lowercase__					      =		self.feed_forward_proj.split("""-"""		)
							lowercase__					      =		act_info[-1]
							lowercase__					      =		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":
									lowercase__					      =		"""gelu_new"""

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






class 							A   (	UpperCAmelCase__							):
					'''simple docstring'''






					@property
					def   lowerCamelCase__					(self   :						List[str]		)						->       Mapping[str, Mapping[int, str]]:




							"""simple docstring"""


							lowercase__					      =		{
							    """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
							    """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
							}
							if self.use_past:
									lowercase__					      =		"""past_encoder_sequence + sequence"""
									lowercase__					      =		{0: """batch"""}
									lowercase__					      =		{0: """batch""", 1: """past_decoder_sequence + sequence"""}
							else:
									lowercase__					      =		{0: """batch""", 1: """decoder_sequence"""}
									lowercase__					      =		{0: """batch""", 1: """decoder_sequence"""}

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

							return common_inputs


					@property
					def   lowerCamelCase__					(self   :						Dict		)						->       int:




							"""simple docstring"""


							return 13





def 			UpperCamelCase (     __magic_name__					:							str   ,   __magic_name__					:							str					)       ->  list:
		"""simple docstring"""




		lowercase__					      =		len(__magic_name__					)
		lowercase__					      =		[]
		for i in range(len(__magic_name__					) - pat_len + 1					):
				lowercase__					      =		True
				for j in range(__magic_name__					):
						if s[i + j] != pattern[j]:
								lowercase__					      =		False
								break
				if match_found:
						position.append(__magic_name__					)
		return position


if __name__ == "__main__":
	assert naive_pattern_search('ABCDEFG', 'DE') == [3]
	print(naive_pattern_search('ABAAABCDBBABCDDEBCABC', 'ABC'))

