






import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def      a_ (      _A      ,   _A=7  )			->			Tuple:







				"""simple docstring"""
				snake_case__									=     None
				if token is not None:
								snake_case__									=     {'Accept': 'application/vnd.github+json', 'Authorization': f'''Bearer {token}'''}

				# The id of a workflow (not of a workflow run)
				snake_case__									=     '636036'

				snake_case__									=     f'''https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs'''
				# On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
				url += f'''?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}'''

				snake_case__									=     requests.get(A__      ,   headers=A__  ).json()

				return result["workflow_runs"]
def      a_ (      _A  )			->			List[Any]:







				"""simple docstring"""
				snake_case__									=     get_daily_ci_runs(A__  )
				snake_case__									=     None
				for workflow_run in workflow_runs:
								if workflow_run["status"] == "completed":
												snake_case__									=     workflow_run['id']
												break

				return workflow_run_id
def      a_ (      _A      ,   _A      ,   _A  )			->			Dict:







				"""simple docstring"""
				snake_case__									=     get_last_daily_ci_runs(A__  )
				if workflow_run_id is not None:
								snake_case__									=     get_artifacts_links(worflow_run_id=A__      ,   token=A__  )
								for artifact_name in artifact_names:
												if artifact_name in artifacts_links:
																snake_case__									=     artifacts_links[artifact_name]
																download_artifact(
																    artifact_name=A__      ,   artifact_url=A__      ,   output_dir=A__      ,   token=A__  )


def      a_ (      _A      ,   _A      ,   _A  )			->			str:







				"""simple docstring"""
				get_last_daily_ci_artifacts(A__      ,   A__      ,   A__  )

				snake_case__									=     {}
				for artifact_name in artifact_names:
								snake_case__									=     os.path.join(A__      ,   f'''{artifact_name}.zip'''  )
								if os.path.isfile(A__  ):
												snake_case__									=     {}
												with zipfile.ZipFile(A__  ) as z:
																for filename in z.namelist():
																				if not os.path.isdir(A__  ):
																								# read the file
																								with z.open(A__  ) as f:
																												snake_case__									=     f.read().decode('UTF-8'  )

				return results












from typing import TYPE_CHECKING

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


__UpperCamelCase					:		int	  =						{"""configuration_xglm""": ["""XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XGLMConfig"""]}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		Dict	  =						["""XGLMTokenizer"""]

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		Optional[int]	  =						["""XGLMTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		List[str]	  =						[
							    """XGLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """XGLMForCausalLM""",
							    """XGLMModel""",
							    """XGLMPreTrainedModel""",
							]


try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		Any	  =						[
							    """FlaxXGLMForCausalLM""",
							    """FlaxXGLMModel""",
							    """FlaxXGLMPreTrainedModel""",
							]


try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		str	  =						[
							    """TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFXGLMForCausalLM""",
							    """TFXGLMModel""",
							    """TFXGLMPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_xglm import XGLMTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_xglm_fast import XGLMTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_xglm import (
														    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFXGLMForCausalLM,
														    TFXGLMModel,
														    TFXGLMPreTrainedModel,
														)


else:
							import sys

							__UpperCamelCase					:		Union[str, Any]	  =						_LazyModule(__name__, globals()["""__file__"""], _import_structure)




