

"""simple docstring"""




import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links

def 						A							(  snake_case__		,					snake_case__=7     ):




			'''simple docstring'''


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

			# The id of a workflow (not of a workflow run)
			SCREAMING_SNAKE_CASE__										=   """636036"""

			SCREAMING_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}"""

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

			return result["workflow_runs"]

def 						A							(  snake_case__     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   get_daily_ci_runs(snake_case__     )
			SCREAMING_SNAKE_CASE__										=   None
			for workflow_run in workflow_runs:
						if workflow_run["status"] == "completed":
									SCREAMING_SNAKE_CASE__										=   workflow_run["""id"""]
									break

			return workflow_run_id

def 						A							(  snake_case__		,					snake_case__		,					snake_case__     ):




			'''simple docstring'''


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




def 						A							(  snake_case__		,					snake_case__		,					snake_case__     ):




			'''simple docstring'''


			get_last_daily_ci_artifacts(snake_case__		,					snake_case__		,					snake_case__     )

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

			return results





"""simple docstring"""




from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


A_				:      Union[str, Any]           =			{
    "susnato/ernie-m-base_pytorch": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json",
    "susnato/ernie-m-large_pytorch": "https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json",
}





class  lowerCamelCase    (A__      ):
			lowerCamelCase__ :		int       		=				'ernie_m'
			lowerCamelCase__ :		Dict[str, str]       		=				{"dropout": "classifier_dropout", "num_classes": "num_labels"}

			def __init__(       self					:    List[str]     ,					__UpperCAmelCase					:    int = 2_5_0_0_0_2     ,					__UpperCAmelCase					:    int = 7_6_8     ,					__UpperCAmelCase					:    int = 1_2     ,					__UpperCAmelCase					:    int = 1_2     ,					__UpperCAmelCase					:    int = 3_0_7_2     ,					__UpperCAmelCase					:    str = "gelu"     ,					__UpperCAmelCase					:    float = 0.1     ,					__UpperCAmelCase					:    float = 0.1     ,					__UpperCAmelCase					:    int = 5_1_4     ,					__UpperCAmelCase					:    float = 0.02     ,					__UpperCAmelCase					:    int = 1     ,					__UpperCAmelCase					:    float = 1e-05     ,					__UpperCAmelCase					:    Union[str, Any]=None     ,					__UpperCAmelCase					:    List[Any]=False     ,					__UpperCAmelCase					:    Union[str, Any]=0.0     ,					**__UpperCAmelCase					:    Any     ,					) ->     Optional[Any]:
						super().__init__(pad_token_id=__UpperCAmelCase     ,					**__UpperCAmelCase							)
						SCREAMING_SNAKE_CASE__										=   vocab_size
						SCREAMING_SNAKE_CASE__										=   hidden_size
						SCREAMING_SNAKE_CASE__										=   num_hidden_layers
						SCREAMING_SNAKE_CASE__										=   num_attention_heads
						SCREAMING_SNAKE_CASE__										=   intermediate_size
						SCREAMING_SNAKE_CASE__										=   hidden_act
						SCREAMING_SNAKE_CASE__										=   hidden_dropout_prob
						SCREAMING_SNAKE_CASE__										=   attention_probs_dropout_prob
						SCREAMING_SNAKE_CASE__										=   max_position_embeddings
						SCREAMING_SNAKE_CASE__										=   initializer_range
						SCREAMING_SNAKE_CASE__										=   layer_norm_eps
						SCREAMING_SNAKE_CASE__										=   classifier_dropout
						SCREAMING_SNAKE_CASE__										=   is_decoder
						SCREAMING_SNAKE_CASE__										=   act_dropout


