


"""simple docstring"""


from typing import Mapping

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


A  :     int    					=    logging.get_logger(__name__)

A  :     Tuple    					=    {
    "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 						_UpperCamelCase						(     lowerCAmelCase__	):
							'''simple docstring'''







							__UpperCAmelCase		:					Optional[int]          ="""t5"""
							__UpperCAmelCase		:					Dict          =["""past_key_values"""]
							__UpperCAmelCase		:					List[Any]          ={"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}

							def __init__(  self					,     __a=3_21_28					,     __a=5_12					,     __a=64					,     __a=20_48					,     __a=6					,     __a=None					,     __a=8					,     __a=32					,     __a=1_28					,     __a=0.1					,     __a=1e-6					,     __a=1.0					,     __a="relu"					,     __a=True					,     __a=True					,     __a=0					,     __a=1					,     **__a					,     ):
										__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(__a			) > 1 and act_info[0] != "gated" or len(__a			) > 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=__a					,     eos_token_id=__a					,     is_encoder_decoder=__a					,     **__a					,     )
class 						_UpperCamelCase						(     lowerCAmelCase__	):
							'''simple docstring'''







							@property
							def     snake_case       (  self			):
										__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_(__a					,     direction="inputs"			)

										return common_inputs



							@property
							def     snake_case       (  self			):
										return 13








"""simple docstring"""


import cmath
import math


def _lowerCamelCase			(	_UpperCamelCase					,				_UpperCamelCase					,				_UpperCamelCase					,				_UpperCamelCase   ):

			'''simple docstring'''




			__lowerCAmelCase       					=    math.radians(_UpperCamelCase   )
			__lowerCAmelCase       					=    math.radians(_UpperCamelCase   )

			# Convert voltage and current to rectangular form
			__lowerCAmelCase       					=    cmath.rect(_UpperCamelCase					,				_UpperCamelCase   )
			__lowerCAmelCase       					=    cmath.rect(_UpperCamelCase					,				_UpperCamelCase   )

			# Calculate apparent power
			return voltage_rect * current_rect


if __name__ == "__main__":
	import doctest

	doctest.testmod()




