





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


lowercase_					     =	logging.get_logger(__name__)

lowercase_					     =	{
    """shi-labs/dinat-mini-in1k-224""": """https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json""",
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}
class        SCREAMING_SNAKE_CASE     (UpperCAmelCase    ,			UpperCAmelCase   ):
   _UpperCamelCase					:	int				      = 'dinat'

   _UpperCamelCase					:	Any				      = {
       'num_attention_heads': 'num_heads',
       'num_hidden_layers': 'num_layers',
   }


   def __init__(					self    :       List[str]    ,  a    :       Optional[int]=4    ,  a    :       Tuple=3    ,  a    :       List[str]=64    ,  a    :       Optional[Any]=[3, 4, 6, 5]    ,  a    :       Tuple=[2, 4, 8, 16]    ,  a    :       Union[str, Any]=7    ,  a    :       Optional[Any]=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]    ,  a    :       int=3.0    ,  a    :       Union[str, Any]=True    ,  a    :       Any=0.0    ,  a    :       Optional[Any]=0.0    ,  a    :       int=0.1    ,  a    :       Dict="gelu"    ,  a    :       List[str]=0.02    ,  a    :       List[str]=1E-5    ,  a    :       Any=0.0    ,  a    :       Optional[int]=None    ,  a    :       Optional[Any]=None    ,  **a    :       Union[str, Any]    ,  )->     Optional[int]:





     """simple docstring"""







     super().__init__(**a )

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









import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE=7	)       ->     List[Any]:
  lowercase__			    =						None
  if token is not None:
    lowercase__			    =						{'Accept': 'application/vnd.github+json', 'Authorization': F"""Bearer {token}"""}

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

  lowercase__			    =						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}"""

  lowercase__			    =						requests.get(_SCREAMING_SNAKE_CASE	,		headers=_SCREAMING_SNAKE_CASE	).json()

  return result["workflow_runs"]




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	)       ->     Union[str, Any]:
  lowercase__			    =						get_daily_ci_runs(_SCREAMING_SNAKE_CASE	)
  lowercase__			    =						None
  for workflow_run in workflow_runs:
    if workflow_run["status"] == "completed":
      lowercase__			    =						workflow_run['id']
      break

  return workflow_run_id




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     Tuple:
  lowercase__			    =						get_last_daily_ci_runs(_SCREAMING_SNAKE_CASE	)
  if workflow_run_id is not None:
    lowercase__			    =						get_artifacts_links(worflow_run_id=_SCREAMING_SNAKE_CASE	,		token=_SCREAMING_SNAKE_CASE	)
    for artifact_name in artifact_names:
      if artifact_name in artifacts_links:
        lowercase__			    =						artifacts_links[artifact_name]
        download_artifact(
            artifact_name=_SCREAMING_SNAKE_CASE	,		artifact_url=_SCREAMING_SNAKE_CASE	,		output_dir=_SCREAMING_SNAKE_CASE	,		token=_SCREAMING_SNAKE_CASE	)




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     Dict:
  get_last_daily_ci_artifacts(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)

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

  return results


