


from typing import List, Optional, Union

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


__a	 =      logging.get_logger(__name__)

__a	 =      {
    """huggingface/informer-tourism-monthly""": (
        """https://huggingface.co/huggingface/informer-tourism-monthly/resolve/main/config.json"""
    ),
    # See all Informer models at https://huggingface.co/models?filter=informer
}






class 	__lowercase					(	__snake_case	):
      UpperCamelCase										=							'''informer'''
      UpperCamelCase										=							{
          '''hidden_size''': '''d_model''',
          '''num_attention_heads''': '''encoder_attention_heads''',
          '''num_hidden_layers''': '''encoder_layers''',
      }





      def __init__(		self    :       Optional[int]       ,							__lowerCamelCase    :       Optional[int] = None       ,							__lowerCamelCase    :       Optional[int] = None       ,							__lowerCamelCase    :       str = "student_t"       ,							__lowerCamelCase    :       str = "nll"       ,							__lowerCamelCase    :       int = 1       ,							__lowerCamelCase    :       List[int] = None       ,							__lowerCamelCase    :       Optional[Union[str, bool]] = "mean"       ,							__lowerCamelCase    :       int = 0       ,							__lowerCamelCase    :       int = 0       ,							__lowerCamelCase    :       int = 0       ,							__lowerCamelCase    :       int = 0       ,							__lowerCamelCase    :       Optional[List[int]] = None       ,							__lowerCamelCase    :       Optional[List[int]] = None       ,							__lowerCamelCase    :       int = 6_4       ,							__lowerCamelCase    :       int = 3_2       ,							__lowerCamelCase    :       int = 3_2       ,							__lowerCamelCase    :       int = 2       ,							__lowerCamelCase    :       int = 2       ,							__lowerCamelCase    :       int = 2       ,							__lowerCamelCase    :       int = 2       ,							__lowerCamelCase    :       bool = True       ,							__lowerCamelCase    :       str = "gelu"       ,							__lowerCamelCase    :       float = 0.05       ,							__lowerCamelCase    :       float = 0.1       ,							__lowerCamelCase    :       float = 0.1       ,							__lowerCamelCase    :       float = 0.1       ,							__lowerCamelCase    :       float = 0.1       ,							__lowerCamelCase    :       int = 1_0_0       ,							__lowerCamelCase    :       float = 0.02       ,							__lowerCamelCase    :       Optional[Any]=True       ,							__lowerCamelCase    :       str = "prob"       ,							__lowerCamelCase    :       int = 5       ,							__lowerCamelCase    :       bool = True       ,							**__lowerCamelCase    :       Optional[int]       ,							)     -> Optional[int]:






         """simple docstring"""







         UpperCAmelCase      					=  prediction_length
         UpperCAmelCase      					=  context_length or prediction_length
         UpperCAmelCase      					=  distribution_output
         UpperCAmelCase      					=  loss
         UpperCAmelCase      					=  input_size
         UpperCAmelCase      					=  num_time_features
         UpperCAmelCase      					=  lags_sequence if lags_sequence is not None else [1, 2, 3, 4, 5, 6, 7]
         UpperCAmelCase      					=  scaling
         UpperCAmelCase      					=  num_dynamic_real_features
         UpperCAmelCase      					=  num_static_real_features
         UpperCAmelCase      					=  num_static_categorical_features

         # set cardinality
         if cardinality and num_static_categorical_features > 0:
            if len(__lowerCamelCase							) != num_static_categorical_features:
               raise ValueError(
                   """The cardinality should be a list of the same length as `num_static_categorical_features`"""							)
            UpperCAmelCase      					=  cardinality
         else:
            UpperCAmelCase      					=  [0]

         # set embedding_dimension
         if embedding_dimension and num_static_categorical_features > 0:
            if len(__lowerCamelCase							) != num_static_categorical_features:
               raise ValueError(
                   """The embedding dimension should be a list of the same length as `num_static_categorical_features`"""							)
            UpperCAmelCase      					=  embedding_dimension
         else:
            UpperCAmelCase      					=  [min(5_0       ,							(cat + 1) // 2							) for cat in self.cardinality]

         UpperCAmelCase      					=  num_parallel_samples

         # Transformer architecture configuration
         UpperCAmelCase      					=  input_size * len(self.lags_sequence							) + self._number_of_features
         UpperCAmelCase      					=  d_model
         UpperCAmelCase      					=  encoder_attention_heads
         UpperCAmelCase      					=  decoder_attention_heads
         UpperCAmelCase      					=  encoder_ffn_dim
         UpperCAmelCase      					=  decoder_ffn_dim
         UpperCAmelCase      					=  encoder_layers
         UpperCAmelCase      					=  decoder_layers

         UpperCAmelCase      					=  dropout
         UpperCAmelCase      					=  attention_dropout
         UpperCAmelCase      					=  activation_dropout
         UpperCAmelCase      					=  encoder_layerdrop
         UpperCAmelCase      					=  decoder_layerdrop

         UpperCAmelCase      					=  activation_function
         UpperCAmelCase      					=  init_std

         UpperCAmelCase      					=  use_cache

         # Informer
         UpperCAmelCase      					=  attention_type
         UpperCAmelCase      					=  sampling_factor
         UpperCAmelCase      					=  distil

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





      @property
      def 							_lowercase					(		self    :       Tuple							)     -> int:






         """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
         )







def 	_UpperCamelCase					(    )    ->list[list[int]]:
   return [list(range(1_0_0_0 - i	,    -1_0_0_0 - i	,    -1 ) ) for i in range(1_0_0_0 )]


__a	 =      generate_large_matrix()
__a	 =      (
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->None:
   assert all(row == sorted(lowerCAmelCase_	,    reverse=lowerCAmelCase_ ) for row in grid )
   assert all(list(lowerCAmelCase_ ) == sorted(lowerCAmelCase_	,    reverse=lowerCAmelCase_ ) for col in zip(*lowerCAmelCase_ ) )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  len(lowerCAmelCase_ ) - 1

   # Edge cases such as no values or all numbers are negative.
   if not array or array[0] < 0:
      return 0

   while right + 1 > left:
      UpperCAmelCase      					=  (left + right) // 2
      UpperCAmelCase      					=  array[mid]

      # Num must be negative and the index must be greater than or equal to 0.
      if num < 0 and array[mid - 1] >= 0:
         return mid

      if num >= 0:
         UpperCAmelCase      					=  mid + 1
      else:
         UpperCAmelCase      					=  mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
   return len(lowerCAmelCase_ )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  len(grid[0] )

   for i in range(len(lowerCAmelCase_ ) ):
      UpperCAmelCase      					=  find_negative_index(grid[i][:bound] )
      total += bound
   return (len(lowerCAmelCase_ ) * len(grid[0] )) - total
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   return len([number for row in grid for number in row if number < 0] )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   for row in grid:
      for i, number in enumerate(lowerCAmelCase_ ):
         if number < 0:
            total += len(lowerCAmelCase_ ) - i
            break
   return total
def 	_UpperCamelCase					(    )    ->None:
   from timeit import timeit

   print("""Running benchmarks""" )
   UpperCAmelCase      					=  (
       """from __main__ import count_negatives_binary_search, """
       """count_negatives_brute_force, count_negatives_brute_force_with_break, grid"""
   )
   for func in (
       "count_negatives_binary_search",  # took 0.7727 seconds
       "count_negatives_brute_force_with_break",  # took 4.6505 seconds
       "count_negatives_brute_force",  # took 12.8160 seconds
   ):
      UpperCAmelCase      					=  timeit(F"""{func}(grid=grid)"""	,    setup=lowerCAmelCase_	,    number=5_0_0 )
      print(F"""{func}() took {time:0.4f} seconds""" )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 benchmark()



