



from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase_							:      Optional[int]      =  logging.get_logger(__name__)

UpperCAmelCase_							:      List[Any]      =  {
    "shi-labs/nat-mini-in1k-224": "https://huggingface.co/shi-labs/nat-mini-in1k-224/resolve/main/config.json",
    # See all Nat models at https://huggingface.co/models?filter=nat
}
class      UpperCamelCase    (						__lowercase       ,    __lowercase     ):
	lowerCAmelCase	:   Union[str, Any]				=	"nat"

	lowerCAmelCase	:   List[str]				=	{
	    "num_attention_heads": "num_heads",
	    "num_hidden_layers": "num_layers",
	}



	def __init__(       self			,	UpperCAmelCase__=4			,	UpperCAmelCase__=3			,	UpperCAmelCase__=64			,	UpperCAmelCase__=[3, 4, 6, 5]			,	UpperCAmelCase__=[2, 4, 8, 16]			,	UpperCAmelCase__=7			,	UpperCAmelCase__=3.0			,	UpperCAmelCase__=True			,	UpperCAmelCase__=0.0			,	UpperCAmelCase__=0.0			,	UpperCAmelCase__=0.1			,	UpperCAmelCase__="gelu"			,	UpperCAmelCase__=0.02			,	UpperCAmelCase__=1e-5			,	UpperCAmelCase__=0.0			,	UpperCAmelCase__=None			,	UpperCAmelCase__=None			,	**UpperCAmelCase__			,	):
							super().__init__(**snake_case_		)

							A__							=       patch_size
							A__							=       num_channels
							A__							=       embed_dim
							A__							=       depths
							A__							=       len(snake_case_		)
							A__							=       num_heads
							A__							=       kernel_size
							A__							=       mlp_ratio
							A__							=       qkv_bias
							A__							=       hidden_dropout_prob
							A__							=       attention_probs_dropout_prob
							A__							=       drop_path_rate
							A__							=       hidden_act
							A__							=       layer_norm_eps
							A__							=       initializer_range
							# we set the hidden_size attribute in order to make Nat work with VisionEncoderDecoderModel
							# this indicates the channel dimension after the last stage of the model
							A__							=       int(embed_dim * 2 ** (len(snake_case_		) - 1)		)
							A__							=       layer_scale_init_value
							A__							=       ['''stem'''] + [F"""stage{idx}""" for idx in range(1			,	len(snake_case_		) + 1		)]
							A__							=       get_aligned_output_features_output_indices(
							    out_features=snake_case_			,	out_indices=snake_case_			,	stage_names=self.stage_names		)










import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def  UpperCamelCase						(       _A			:				List[Any]			,							_A			:				List[str]=7    )->       Optional[Any]:





						"""simple docstring"""





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

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

						A__							=       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}"""

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

						return result["workflow_runs"]
def  UpperCamelCase						(       _A			:				str    )->       Dict:





						"""simple docstring"""





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

						return workflow_run_id
def  UpperCamelCase						(       _A			:				int			,							_A			:				List[str]			,							_A			:				str    )->       Any:





						"""simple docstring"""





						A__							=       get_last_daily_ci_runs(_A    )
						if workflow_run_id is not None:
												A__							=       get_artifacts_links(worflow_run_id=_A			,							token=_A    )
												for artifact_name in artifact_names:
																		if artifact_name in artifacts_links:
																								A__							=       artifacts_links[artifact_name]
																								download_artifact(
																								    artifact_name=_A			,							artifact_url=_A			,							output_dir=_A			,							token=_A    )
def  UpperCamelCase						(       _A			:				Optional[Any]			,							_A			:				Any			,							_A			:				List[Any]    )->       Optional[int]:





						"""simple docstring"""





						get_last_daily_ci_artifacts(_A			,							_A			,							_A    )

						A__							=       {}
						for artifact_name in artifact_names:
												A__							=       os.path.join(_A			,							f"""{artifact_name}.zip"""    )
												if os.path.isfile(_A    ):
																		A__							=       {}
																		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:
																																										A__							=       f.read().decode("UTF-8"    )

						return results





