





from typing import List, Optional

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


_lowerCamelCase      							=   logging.get_logger(__name__)

_lowerCamelCase      							=   {
    'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface/autoformer-tourism-monthly/resolve/main/config.json',
}







class       __A							(   lowerCamelCase__	):




      """simple docstring"""







      UpperCAmelCase__							=   """autoformer"""
      UpperCAmelCase__							=   {
          """hidden_size""": """d_model""",
          """num_attention_heads""": """encoder_attention_heads""",
          """num_hidden_layers""": """encoder_layers""",
      }


      def __init__(		self   ,				a__ = None   ,				a__ = None   ,				a__ = "student_t"   ,				a__ = "nll"   ,				a__ = 1   ,				a__ = [1, 2, 3, 4, 5, 6, 7]   ,				a__ = True   ,				a__ = 0   ,				a__ = 0   ,				a__ = 0   ,				a__ = 0   ,				a__ = None   ,				a__ = None   ,				a__ = 64   ,				a__ = 2   ,				a__ = 2   ,				a__ = 2   ,				a__ = 2   ,				a__ = 32   ,				a__ = 32   ,				a__ = "gelu"   ,				a__ = 0.1   ,				a__ = 0.1   ,				a__ = 0.1   ,				a__ = 0.1   ,				a__ = 0.1   ,				a__ = 100   ,				a__ = 0.02   ,				a__ = True   ,				a__=True   ,				a__ = 10   ,				a__ = 25   ,				a__ = 3   ,				**a__   ,				):



             """simple docstring"""





             _lowerCamelCase				:  int						=		prediction_length
             _lowerCamelCase				:  Optional[Any]						=		context_length if context_length is not None else prediction_length
             _lowerCamelCase				:  Tuple						=		distribution_output
             _lowerCamelCase				:  List[str]						=		loss
             _lowerCamelCase				:  int						=		input_size
             _lowerCamelCase				:  Union[str, Any]						=		num_time_features
             _lowerCamelCase				:  int						=		lags_sequence
             _lowerCamelCase				:  Union[str, Any]						=		scaling
             _lowerCamelCase				:  Union[str, Any]						=		num_dynamic_real_features
             _lowerCamelCase				:  Union[str, Any]						=		num_static_real_features
             _lowerCamelCase				:  Dict						=		num_static_categorical_features
             if cardinality is not None and num_static_categorical_features > 0:
                    if len(a__) != num_static_categorical_features:
                           raise ValueError(
                               '''The cardinality should be a list of the same length as `num_static_categorical_features`''')
                    _lowerCamelCase				:  List[str]						=		cardinality
             else:
                    _lowerCamelCase				:  Union[str, Any]						=		[0]
             if embedding_dimension is not None and num_static_categorical_features > 0:
                    if len(a__) != num_static_categorical_features:
                           raise ValueError(
                               '''The embedding dimension should be a list of the same length as `num_static_categorical_features`''')
                    _lowerCamelCase				:  Optional[int]						=		embedding_dimension
             else:
                    _lowerCamelCase				:  List[Any]						=		[min(50   ,				(cat + 1) // 2) for cat in self.cardinality]
             _lowerCamelCase				:  Any						=		num_parallel_samples

             # Transformer architecture configuration
             _lowerCamelCase				:  Dict						=		input_size * len(self.lags_sequence) + self._number_of_features
             _lowerCamelCase				:  Tuple						=		d_model
             _lowerCamelCase				:  Optional[Any]						=		encoder_attention_heads
             _lowerCamelCase				:  Dict						=		decoder_attention_heads
             _lowerCamelCase				:  Any						=		encoder_ffn_dim
             _lowerCamelCase				:  Union[str, Any]						=		decoder_ffn_dim
             _lowerCamelCase				:  str						=		encoder_layers
             _lowerCamelCase				:  Dict						=		decoder_layers

             _lowerCamelCase				:  Dict						=		dropout
             _lowerCamelCase				:  Optional[Any]						=		attention_dropout
             _lowerCamelCase				:  int						=		activation_dropout
             _lowerCamelCase				:  Tuple						=		encoder_layerdrop
             _lowerCamelCase				:  List[Any]						=		decoder_layerdrop

             _lowerCamelCase				:  Any						=		activation_function
             _lowerCamelCase				:  Union[str, Any]						=		init_std

             _lowerCamelCase				:  Dict						=		use_cache

             # Autoformer
             _lowerCamelCase				:  Any						=		label_length
             _lowerCamelCase				:  List[str]						=		moving_average
             _lowerCamelCase				:  List[Any]						=		autocorrelation_factor

             super().__init__(is_encoder_decoder=a__   ,				**a__)



      @property
      def 					__snake_case      (		self):



             """simple docstring"""





             return (
                 sum(self.embedding_dimension)
                 + self.num_dynamic_real_features
                 + self.num_time_features
                 + self.num_static_real_features
                 + self.input_size * 2  # the log1p(abs(loc)) and log(scale) features
             )








import mpmath  # for roots of unity
import numpy as np







class       __A							:




      """simple docstring"""







      def __init__(		self   ,				a__=None   ,				a__=None):



             """simple docstring"""





             _lowerCamelCase				:  List[str]						=		list(poly_a or [0])[:]
             _lowerCamelCase				:  Union[str, Any]						=		list(poly_b or [0])[:]

             # Remove leading zero coefficients
             while self.polyA[-1] == 0:
                    self.polyA.pop()
             _lowerCamelCase				:  Optional[int]						=		len(self.polyA)

             while self.polyB[-1] == 0:
                    self.polyB.pop()
             _lowerCamelCase				:  Any						=		len(self.polyB)

             # Add 0 to make lengths equal a power of 2
             _lowerCamelCase				:  Dict						=		int(
                 2 ** np.ceil(np.loga(len(self.polyA) + len(self.polyB) - 1)))

             while len(self.polyA) < self.c_max_length:
                    self.polyA.append(0)
             while len(self.polyB) < self.c_max_length:
                    self.polyB.append(0)
             # A complex root used for the fourier transform
             _lowerCamelCase				:  int						=		complex(mpmath.root(x=1   ,				n=self.c_max_length   ,				k=1))

             # The product
             _lowerCamelCase				:  Optional[int]						=		self.__multiply()


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





             _lowerCamelCase				:  List[Any]						=		[[x] for x in self.polyA] if which == '''A''' else [[x] for x in self.polyB]
             # Corner case
             if len(a__) <= 1:
                    return dft[0]
             #
             _lowerCamelCase				:  Optional[Any]						=		self.c_max_length // 2
             while next_ncol > 0:
                    _lowerCamelCase				:  Optional[Any]						=		[[] for i in range(a__)]
                    _lowerCamelCase				:  List[str]						=		self.root**next_ncol

                    # First half of next step
                    _lowerCamelCase				:  Tuple						=		1
                    for j in range(self.c_max_length // (next_ncol * 2)):
                           for i in range(a__):
                                  new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j])
                           current_root *= root
                    # Second half of next step
                    _lowerCamelCase				:  Tuple						=		1
                    for j in range(self.c_max_length // (next_ncol * 2)):
                           for i in range(a__):
                                  new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j])
                           current_root *= root
                    # Update
                    _lowerCamelCase				:  Tuple						=		new_dft
                    _lowerCamelCase				:  Union[str, Any]						=		next_ncol // 2
             return dft[0]


      def 					__snake_case      (		self):



             """simple docstring"""





             _lowerCamelCase				:  Optional[int]						=		self.__dft('''A''')
             _lowerCamelCase				:  Optional[Any]						=		self.__dft('''B''')
             _lowerCamelCase				:  List[str]						=		[[dft_a[i] * dft_b[i] for i in range(self.c_max_length)]]
             del dft_a
             del dft_b

             # Corner Case
             if len(inverce_c[0]) <= 1:
                    return inverce_c[0]
             # Inverse DFT
             _lowerCamelCase				:  str						=		2
             while next_ncol <= self.c_max_length:
                    _lowerCamelCase				:  Optional[int]						=		[[] for i in range(a__)]
                    _lowerCamelCase				:  Dict						=		self.root ** (next_ncol // 2)
                    _lowerCamelCase				:  List[str]						=		1
                    # First half of next step
                    for j in range(self.c_max_length // next_ncol):
                           for i in range(next_ncol // 2):
                                  # Even positions
                                  new_inverse_c[i].append(
                                      (
                                          inverce_c[i][j]
                                          + inverce_c[i][j + self.c_max_length // next_ncol]
                                      )
                                      / 2)
                                  # Odd positions
                                  new_inverse_c[i + next_ncol // 2].append(
                                      (
                                          inverce_c[i][j]
                                          - inverce_c[i][j + self.c_max_length // next_ncol]
                                      )
                                      / (2 * current_root))
                           current_root *= root
                    # Update
                    _lowerCamelCase				:  Any						=		new_inverse_c
                    next_ncol *= 2
             # Unpack
             _lowerCamelCase				:  Optional[int]						=		[round(x[0].real   ,				8) + round(x[0].imag   ,				8) * 1j for x in inverce_c]

             # Remove leading 0's
             while inverce_c[-1] == 0:
                    inverce_c.pop()
             return inverce_c



      def __str__(		self):



             """simple docstring"""





             _lowerCamelCase				:  Union[str, Any]						=		'''A = ''' + ''' + '''.join(
                 F"""{coef}*x^{i}""" for coef, i in enumerate(self.polyA[: self.len_A]))
             _lowerCamelCase				:  List[str]						=		'''B = ''' + ''' + '''.join(
                 F"""{coef}*x^{i}""" for coef, i in enumerate(self.polyB[: self.len_B]))
             _lowerCamelCase				:  Tuple						=		'''A*B = ''' + ''' + '''.join(
                 F"""{coef}*x^{i}""" for coef, i in enumerate(self.product))

             return F"""{a}\n{b}\n{c}"""


# Unit tests
if __name__ == "__main__":
       import doctest

       doctest.testmod()

