"""simple docstring"""



import doctest
from collections import deque

import numpy as np
class 						__UpperCAmelCase    :







			'''simple docstring'''





			def __init__(			self							):







										'''simple docstring'''


										A__       :     List[Any]								=			[2, 1, 2, -1]
										A__       :     List[Any]								=			[1, 2, 3, 4]





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     int								=			len(self.first_signal							)
										A__       :     List[str]								=			len(self.second_signal							)

										A__       :     Union[str, Any]								=			max(__lowerCAmelCase   ,      __lowerCAmelCase							)

										# create a zero matrix of max_length x max_length
										A__       :     Any								=			[[0] * max_length for i in range(__lowerCAmelCase							)]

										# fills the smaller signal with zeros to make both signals of same length
										if length_first_signal < length_second_signal:
																	self.first_signal += [0] * (max_length - length_first_signal)
										elif length_first_signal > length_second_signal:
																	self.second_signal += [0] * (max_length - length_second_signal)
										for i in range(__lowerCAmelCase							):
																	A__       :     List[Any]								=			deque(self.second_signal							)
																	rotated_signal.rotate(__lowerCAmelCase							)
																	for j, item in enumerate(__lowerCAmelCase							):
																								matrix[i][j] += item

																	# multiply the matrix with the first signal
										A__       :     List[str]								=			np.matmul(np.transpose(__lowerCAmelCase							)   ,      np.transpose(self.first_signal							)							)

										# rounding-off to two decimal places
										return [round(__lowerCAmelCase   ,      2							) for i in final_signal]


if __name__ == "__main__":
				doctest.testmod()






"""simple docstring"""


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


UpperCAmelCase__			=    logging.get_logger(__name__)

UpperCAmelCase__			=    {
    """google/realm-cc-news-pretrained-embedder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-encoder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-scorer""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-openqa""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"""
    ),
    """google/realm-orqa-nq-openqa""": """https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json""",
    """google/realm-orqa-nq-reader""": """https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json""",
    """google/realm-orqa-wq-openqa""": """https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json""",
    """google/realm-orqa-wq-reader""": """https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json""",
    # See all REALM models at https://huggingface.co/models?filter=realm
}


class 							a					(		lowerCAmelCase_ ):
    _snake_case  :	List[Any]  				=				'realm'


    def __init__(       self						:	List[Any] ,					__lowerCAmelCase						:	List[str]=3_0522 ,					__lowerCAmelCase						:	Tuple=768 ,					__lowerCAmelCase						:	List[Any]=128 ,					__lowerCAmelCase						:	Tuple=12 ,					__lowerCAmelCase						:	List[str]=12 ,					__lowerCAmelCase						:	Union[str, Any]=8 ,					__lowerCAmelCase						:	List[str]=3072 ,					__lowerCAmelCase						:	Union[str, Any]="gelu_new" ,					__lowerCAmelCase						:	str=0.1 ,					__lowerCAmelCase						:	Tuple=0.1 ,					__lowerCAmelCase						:	List[str]=512 ,					__lowerCAmelCase						:	Dict=2 ,					__lowerCAmelCase						:	List[Any]=0.02 ,					__lowerCAmelCase						:	Optional[int]=1e-1_2 ,					__lowerCAmelCase						:	Any=256 ,					__lowerCAmelCase						:	Union[str, Any]=10 ,					__lowerCAmelCase						:	Dict=1e-3 ,					__lowerCAmelCase						:	str=5 ,					__lowerCAmelCase						:	str=320 ,					__lowerCAmelCase						:	Tuple=1335_3718 ,					__lowerCAmelCase						:	Optional[Any]=5000 ,					__lowerCAmelCase						:	int=1 ,					__lowerCAmelCase						:	Dict=0 ,					__lowerCAmelCase						:	Any=2 ,					**__lowerCAmelCase						:	Optional[int] ,					):
      super().__init__(pad_token_id=__lowerCAmelCase ,					bos_token_id=__lowerCAmelCase ,					eos_token_id=__lowerCAmelCase ,					**__lowerCAmelCase       )

      # Common config
      _UpperCAmelCase    			=   vocab_size
      _UpperCAmelCase    			=   max_position_embeddings
      _UpperCAmelCase    			=   hidden_size
      _UpperCAmelCase    			=   retriever_proj_size
      _UpperCAmelCase    			=   num_hidden_layers
      _UpperCAmelCase    			=   num_attention_heads
      _UpperCAmelCase    			=   num_candidates
      _UpperCAmelCase    			=   intermediate_size
      _UpperCAmelCase    			=   hidden_act
      _UpperCAmelCase    			=   hidden_dropout_prob
      _UpperCAmelCase    			=   attention_probs_dropout_prob
      _UpperCAmelCase    			=   initializer_range
      _UpperCAmelCase    			=   type_vocab_size
      _UpperCAmelCase    			=   layer_norm_eps

      # Reader config
      _UpperCAmelCase    			=   span_hidden_size
      _UpperCAmelCase    			=   max_span_width
      _UpperCAmelCase    			=   reader_layer_norm_eps
      _UpperCAmelCase    			=   reader_beam_size
      _UpperCAmelCase    			=   reader_seq_len

      # Retrieval config
      _UpperCAmelCase    			=   num_block_records
      _UpperCAmelCase    			=   searcher_beam_size
