




from typing import Callable, Optional, Union

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


lowerCamelCase_  						=       logging.get_logger(__name__)

lowerCamelCase_  						=       {
    "microsoft/prophetnet-large-uncased": (
        "https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"
    ),
}
class 				__a (			__lowerCamelCase					):


					"""simple docstring"""


					_A    :   List[Any]     =  "prophetnet"
					_A    :   Dict     =  ["past_key_values"]
					_A    :   Any     =  {
					    "num_attention_heads": "num_encoder_attention_heads",
					}




					def __init__(     self      :			Optional[int]    ,_UpperCamelCase      :			Optional[float] = 0.1    ,_UpperCamelCase      :			Optional[Union[str, Callable]] = "gelu"    ,_UpperCamelCase      :			Optional[int] = 3_0_5_2_2    ,_UpperCamelCase      :			Optional[int] = 1_0_2_4    ,_UpperCamelCase      :			Optional[int] = 4_0_9_6    ,_UpperCamelCase      :			Optional[int] = 1_2    ,_UpperCamelCase      :			Optional[int] = 1_6    ,_UpperCamelCase      :			Optional[int] = 4_0_9_6    ,_UpperCamelCase      :			Optional[int] = 1_2    ,_UpperCamelCase      :			Optional[int] = 1_6    ,_UpperCamelCase      :			Optional[float] = 0.1    ,_UpperCamelCase      :			Optional[float] = 0.1    ,_UpperCamelCase      :			Optional[int] = 5_1_2    ,_UpperCamelCase      :			Optional[float] = 0.02    ,_UpperCamelCase      :			Optional[bool] = True    ,_UpperCamelCase      :			Optional[bool] = True    ,_UpperCamelCase      :			Optional[int] = 0    ,_UpperCamelCase      :			Optional[int] = 2    ,_UpperCamelCase      :			Optional[int] = 3_2    ,_UpperCamelCase      :			Optional[int] = 1_2_8    ,_UpperCamelCase      :			Optional[bool] = False    ,_UpperCamelCase      :			Optional[float] = 0.0    ,_UpperCamelCase      :			Optional[bool] = True    ,_UpperCamelCase      :			Optional[int] = 0    ,_UpperCamelCase      :			Optional[int] = 1    ,_UpperCamelCase      :			Optional[int] = 2    ,**_UpperCamelCase      :			str    ,)		->       List[str]:


									'''simple docstring'''





									SCREAMING_SNAKE_CASE__       =vocab_size
									SCREAMING_SNAKE_CASE__       =hidden_size
									SCREAMING_SNAKE_CASE__       =encoder_ffn_dim
									SCREAMING_SNAKE_CASE__       =num_encoder_layers
									SCREAMING_SNAKE_CASE__       =num_encoder_attention_heads
									SCREAMING_SNAKE_CASE__       =decoder_ffn_dim
									SCREAMING_SNAKE_CASE__       =num_decoder_layers
									SCREAMING_SNAKE_CASE__       =num_decoder_attention_heads
									SCREAMING_SNAKE_CASE__       =max_position_embeddings
									SCREAMING_SNAKE_CASE__       =init_std  # Normal(0, this parameter)
									SCREAMING_SNAKE_CASE__       =activation_function

									# parameters for prophetnet
									SCREAMING_SNAKE_CASE__       =ngram
									SCREAMING_SNAKE_CASE__       =num_buckets
									SCREAMING_SNAKE_CASE__       =relative_max_distance
									SCREAMING_SNAKE_CASE__       =disable_ngram_loss
									SCREAMING_SNAKE_CASE__       =eps

									# 3 Types of Dropout
									SCREAMING_SNAKE_CASE__       =attention_dropout
									SCREAMING_SNAKE_CASE__       =activation_dropout
									SCREAMING_SNAKE_CASE__       =dropout

									SCREAMING_SNAKE_CASE__       =use_cache

									super().__init__(
									    pad_token_id=_UpperCamelCase    ,bos_token_id=_UpperCamelCase    ,eos_token_id=_UpperCamelCase    ,is_encoder_decoder=_UpperCamelCase    ,add_cross_attention=_UpperCamelCase    ,decoder_start_token_id=_UpperCamelCase    ,**_UpperCamelCase    ,)




					@property
					def   __A    (     self      :			int						)		->       int:


									'''simple docstring'''





									return self.num_encoder_layers + self.num_decoder_layers




					@num_hidden_layers.setter
					def   __A    (     self      :			Any    ,_UpperCamelCase      :			int						)		->       Union[str, Any]:


									'''simple docstring'''





									raise NotImplementedError(
									    """This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"""
									    """ `num_decoder_layers`."""						)












def      UpperCAmelCase_   (     __UpperCamelCase,    __UpperCamelCase     ):
    SCREAMING_SNAKE_CASE__       =len(__UpperCamelCase     )
    # Create a stack and push index of fist element to it
    SCREAMING_SNAKE_CASE__       =[]
    st.append(0     )

    # Span value of first element is always 1
    SCREAMING_SNAKE_CASE__       =1

    # Calculate span values for rest of the elements
    for i in range(1,    __UpperCamelCase     ):
        # Pop elements from stack while stack is not
        # empty and top of stack is smaller than price[i]
        while len(__UpperCamelCase     ) > 0 and price[st[0]] <= price[i]:
            st.pop()

        # If stack becomes empty, then price[i] is greater
        # than all elements on left of it, i.e. price[0],
        # price[1], ..price[i-1]. Else the price[i]  is
        # greater than elements after top of stack
        SCREAMING_SNAKE_CASE__       =i + 1 if len(__UpperCamelCase     ) <= 0 else (i - st[0])

        # Push this element to stack
        st.append(__UpperCamelCase     )



def      UpperCAmelCase_   (     __UpperCamelCase,    __UpperCamelCase     ):
    for i in range(0,    __UpperCamelCase     ):
        print(arr[i],    end=""" """     )


# Driver program to test above function
lowerCamelCase_  						=       [10, 4, 5, 90, 120, 80]
lowerCamelCase_  						=       [0 for i in range(len(price) + 1)]

# Fill the span values in array S[]
calculation_span(price, S)




print_array(S, len(price))






