


"""simple docstring"""






import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import (
    TaBlock,
    TaConfig,
    TaLayerNorm,
)

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin


class 			SCREAMING_SNAKE_CASE_  (   __UpperCAmelCase	,      __UpperCAmelCase	,      __UpperCAmelCase):




							'''simple docstring'''





							@register_to_config
							def __init__(						self	,					lowerCamelCase__	,					lowerCamelCase__	,					lowerCamelCase__	,					lowerCamelCase__	,					lowerCamelCase__	,					lowerCamelCase__	,					lowerCamelCase__	,					lowerCamelCase__	,					lowerCamelCase__	,					lowerCamelCase__ = False	,					)   ->	Dict:







								'''simple docstring'''




								super().__init__()

								snake_case__  :						Optional[int]		=      nn.Linear(__SCREAMING_SNAKE_CASE	,					__SCREAMING_SNAKE_CASE	,					bias=__SCREAMING_SNAKE_CASE)

								snake_case__  :						Any		=      nn.Embedding(__SCREAMING_SNAKE_CASE	,					__SCREAMING_SNAKE_CASE)
								snake_case__  :						int		=      False

								snake_case__  :						Optional[Any]		=      nn.Dropout(p=__SCREAMING_SNAKE_CASE)

								snake_case__  :						Optional[int]		=      TaConfig(
								    d_model=__SCREAMING_SNAKE_CASE	,					num_heads=__SCREAMING_SNAKE_CASE	,					d_kv=__SCREAMING_SNAKE_CASE	,					d_ff=__SCREAMING_SNAKE_CASE	,					feed_forward_proj=__SCREAMING_SNAKE_CASE	,					dropout_rate=__SCREAMING_SNAKE_CASE	,					is_decoder=__SCREAMING_SNAKE_CASE	,					is_encoder_decoder=__SCREAMING_SNAKE_CASE	,					)
								snake_case__  :						Tuple		=      nn.ModuleList()
								for lyr_num in range(__SCREAMING_SNAKE_CASE):
									snake_case__  :						List[str]		=      TaBlock(__SCREAMING_SNAKE_CASE)
									self.encoders.append(__SCREAMING_SNAKE_CASE)

								snake_case__  :						Tuple		=      TaLayerNorm(__SCREAMING_SNAKE_CASE)
								snake_case__  :						Optional[int]		=      nn.Dropout(p=__SCREAMING_SNAKE_CASE)







							def        UpperCAmelCase (						self	,					lowerCamelCase__	,					lowerCamelCase__)   ->	Any:







								'''simple docstring'''




								snake_case__  :						Optional[int]		=      self.input_proj(__SCREAMING_SNAKE_CASE)

								# terminal relative positional encodings
								snake_case__  :						Tuple		=      encoder_inputs.shape[1]
								snake_case__  :						int		=      torch.arange(__SCREAMING_SNAKE_CASE	,					device=encoder_inputs.device)

								snake_case__  :						int		=      encoder_inputs_mask.sum(-1)
								snake_case__  :						str		=      torch.roll(input_positions.unsqueeze(0)	,					tuple(seq_lens.tolist())	,					dims=0)
								x += self.position_encoding(__SCREAMING_SNAKE_CASE)

								snake_case__  :						Optional[Any]		=      self.dropout_pre(__SCREAMING_SNAKE_CASE)

								# inverted the attention mask
								snake_case__  :						Dict		=      encoder_inputs.size()
								snake_case__  :						str		=      self.get_extended_attention_mask(__SCREAMING_SNAKE_CASE	,					__SCREAMING_SNAKE_CASE)

								for lyr in self.encoders:
									snake_case__  :						Optional[int]		=      lyr(__SCREAMING_SNAKE_CASE	,					__SCREAMING_SNAKE_CASE)[0]
								snake_case__  :						Tuple		=      self.layer_norm(__SCREAMING_SNAKE_CASE)

								return self.dropout_post(__SCREAMING_SNAKE_CASE), encoder_inputs_mask










def 	__snake_case      (     _UpperCAmelCase							):
    __a					=							1
    __a					=							0
    __a					=							1
    __a					=							1
    __a					=							3
    __a					=							3
    __a					=							limit
    __a					=							0

    __a					=							''''''
    while counter != decimal + 1:
        if 4 * q + r - t < n * t:
            result += str(_UpperCAmelCase							)
            if counter == 0:
                result += "."

            if decimal == counter:
                break

            counter += 1
            __a					=							10 * (r - n * t)
            __a					=							((10 * (3 * q + r)) // t) - 10 * n
            q *= 10
            __a					=							nr
        else:
            __a					=							(2 * q + r) * l
            __a					=							(q * (7 * k) + 2 + (r * l)) // (t * l)
            q *= k
            t *= l
            l += 2
            k += 1
            __a					=							nn
            __a					=							nr
    return result





def 	__snake_case      (     ):
    print(f'{calculate_pi(50							) = }'							)
    import doctest

    doctest.testmod()


if __name__ == "__main__":
 main()





