
"""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 __lowerCAmelCase	(   __lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ):





					@register_to_config
					def __init__(			self			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase = False			,  ):

						'''simple docstring'''




						super().__init__()

						__UpperCamelCase       						= nn.Embedding(a_			,  a_   )

						__UpperCamelCase       						= nn.Embedding(a_			,  a_   )
						__UpperCamelCase       						= False

						__UpperCamelCase       						= nn.Dropout(p=a_   )

						__UpperCamelCase       						= TaConfig(
						    vocab_size=a_			,  d_model=a_			,  num_heads=a_			,  d_kv=a_			,  d_ff=a_			,  dropout_rate=a_			,  feed_forward_proj=a_			,  is_decoder=a_			,  is_encoder_decoder=a_			,  )

						__UpperCamelCase       						= nn.ModuleList()
						for lyr_num in range(a_   ):
							__UpperCamelCase       						= TaBlock(a_   )
							self.encoders.append(a_   )

						__UpperCamelCase       						= TaLayerNorm(a_   )
						__UpperCamelCase       						= nn.Dropout(p=a_   )







					def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase   ):

						'''simple docstring'''




						__UpperCamelCase       						= self.token_embedder(a_   )

						__UpperCamelCase       						= encoder_input_tokens.shape[1]
						__UpperCamelCase       						= torch.arange(a_			,  device=encoder_input_tokens.device   )
						x += self.position_encoding(a_   )

						__UpperCamelCase       						= self.dropout_pre(a_   )

						# inverted the attention mask
						__UpperCamelCase       						= encoder_input_tokens.size()
						__UpperCamelCase       						= self.get_extended_attention_mask(a_			,  a_   )

						for lyr in self.encoders:
							__UpperCamelCase       						= lyr(a_			,  a_   )[0]
						__UpperCamelCase       						= self.layer_norm(a_   )

						return self.dropout_post(a_   ), encoder_inputs_mask





"""simple docstring"""

from __future__ import annotations

import os
from typing import Any

import requests

UpperCamelCase			:       Union[str, Any]									=				"https://api.github.com"

# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
UpperCamelCase			:       Union[str, Any]									=				BASE_URL + "/user"

# https://github.com/settings/tokens
UpperCamelCase			:       Optional[int]									=				os.environ.get("USER_TOKEN", "")






def 							A		(       snake_case   :str	)   ->			dict[Any, Any]:
 __UpperCamelCase       						= {
     'Authorization': f'token {auth_token}',
     'Accept': 'application/vnd.github.v3+json',
 }
 return requests.get(snake_case       ,      headers=snake_case	).json()


if __name__ == "__main__":  # pragma: no cover
      if USER_TOKEN:
            for key, value in fetch_github_info(USER_TOKEN).items():
                  print(f'''{key}: {value}''')
      else:
            raise ValueError("'USER_TOKEN' field cannot be empty.")



