



"""simple docstring"""
from __future__ import annotations

import os
from typing import Any

import requests

SCREAMING_SNAKE_CASE_				= """https://api.github.com"""

# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
SCREAMING_SNAKE_CASE_				= BASE_URL + """/user"""

# https://github.com/settings/tokens
SCREAMING_SNAKE_CASE_				= os.environ.get("""USER_TOKEN""", """""")



def        lowerCAmelCase_						(							SCREAMING_SNAKE_CASE__	)			->      dict[Any, Any]:
		a_     :      Dict 						=     {
		    "Authorization": F"""token {auth_token}""",
		    "Accept": "application/vnd.github.v3+json",
		}
		return requests.get(SCREAMING_SNAKE_CASE__, headers=SCREAMING_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.""")




"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE_				= {
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_				= ["""LlamaTokenizer"""]

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_				= ["""LlamaTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_				= [
					    """LlamaForCausalLM""",
					    """LlamaModel""",
					    """LlamaPreTrainedModel""",
					    """LlamaForSequenceClassification""",
					]


if TYPE_CHECKING:
					from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_llama import LlamaTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_llama_fast import LlamaTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
					import sys

					SCREAMING_SNAKE_CASE_				= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)