
"""simple docstring"""




import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union
class SCREAMING_SNAKE_CASE       (      enum.Enum					):






	'''simple docstring'''







	snake_case__							:		Optional[Any]         =		'timm'
	snake_case__							:		Optional[Any]         =		'transformers'

def __snake_case (      UpperCamelCase						,					UpperCamelCase						,					UpperCamelCase    )       ->    Union[str, Any]:


		"""simple docstring"""





		if stage_names is None:
				raise ValueError('''Stage_names must be set for transformers backbones'''    )

		if out_features is not None:
				if not isinstance(UpperCamelCase						,					(list,)    ):
						raise ValueError(f"out_features must be a list {type(UpperCamelCase    )}"    )
				if any(feat not in stage_names for feat in out_features    ):
						raise ValueError(f"out_features must be a subset of stage_names: {stage_names} got {out_features}"    )

		if out_indices is not None:
				if not isinstance(UpperCamelCase						,					(list, tuple)    ):
						raise ValueError(f"out_indices must be a list or tuple, got {type(UpperCamelCase    )}"    )
				if any(idx >= len(UpperCamelCase    ) for idx in out_indices    ):
						raise ValueError('''out_indices must be valid indices for stage_names {stage_names}, got {out_indices}'''    )

		if out_features is not None and out_indices is not None:
				if len(UpperCamelCase    ) != len(UpperCamelCase    ):
						raise ValueError('''out_features and out_indices should have the same length if both are set'''    )
				if out_features != [stage_names[idx] for idx in out_indices]:
						raise ValueError('''out_features and out_indices should correspond to the same stages if both are set'''    )

def __snake_case (      UpperCamelCase						,					UpperCamelCase						,					UpperCamelCase						,					)       ->    int:


		"""simple docstring"""





		if out_indices is None and out_features is None:
				a__   		=     [len(UpperCamelCase    ) - 1]
				a__   		=     [stage_names[-1]]
		elif out_indices is None and out_features is not None:
				a__   		=     [stage_names.index(UpperCamelCase    ) for layer in out_features]
		elif out_features is None and out_indices is not None:
				a__   		=     [stage_names[idx] for idx in out_indices]
		return out_features, out_indices

def __snake_case (      UpperCamelCase						,					UpperCamelCase						,					UpperCamelCase						,					)       ->    Tuple[List[str], List[int]]:


		"""simple docstring"""





		verify_out_features_out_indices(out_features=UpperCamelCase						,					out_indices=UpperCamelCase						,					stage_names=UpperCamelCase    )
		a__		,	a__   		=     _align_output_features_output_indices(
		    out_features=UpperCamelCase						,					out_indices=UpperCamelCase						,					stage_names=UpperCamelCase    )
		# Verify that the aligned out_features and out_indices are valid
		verify_out_features_out_indices(out_features=UpperCamelCase						,					out_indices=UpperCamelCase						,					stage_names=UpperCamelCase    )
		return output_features, output_indices
class SCREAMING_SNAKE_CASE       :






	'''simple docstring'''







	snake_case__							:		Optional[BackboneType]         =		None


	def    _UpperCamelCase							(  self :Any       ,    __magic_name__ :Any			)			->   None:

			'''simple docstring'''






			if getattr(self       ,    '''_backbone'''       ,    __magic_name__			) is None:
					raise ValueError('''self._backbone must be set before calling _init_timm_backbone'''			)

			# These will diagree with the defaults for the transformers models e.g. for resnet50
			# the transformer model has out_features = ['stem', 'stage1', 'stage2', 'stage3', 'stage4']
			# the timm model has out_features = ['act', 'layer1', 'layer2', 'layer3', 'layer4']
			a__   		=     [stage['''module'''] for stage in self._backbone.feature_info.info]
			a__   		=     [stage['''num_chs'''] for stage in self._backbone.feature_info.info]
			a__   		=     self._backbone.feature_info.out_indices
			a__   		=     self._backbone.feature_info.module_name()

			# We verify the out indices and out features are valid
			verify_out_features_out_indices(
			    out_features=__magic_name__       ,    out_indices=__magic_name__       ,    stage_names=self.stage_names			)
			a__		,	a__   		=     out_features, out_indices


	def    _UpperCamelCase							(  self :str       ,    __magic_name__ :str			)			->   None:

			'''simple docstring'''






			a__   		=     getattr(__magic_name__       ,    '''stage_names'''			)
			a__   		=     getattr(__magic_name__       ,    '''out_features'''       ,    __magic_name__			)
			a__   		=     getattr(__magic_name__       ,    '''out_indices'''       ,    __magic_name__			)

			a__   		=     stage_names
			a__		,	a__   		=     get_aligned_output_features_output_indices(
			    out_features=__magic_name__       ,    out_indices=__magic_name__       ,    stage_names=__magic_name__			)
			# Number of channels for each stage. This is set in the transformer backbone model init
			a__   		=     None


	def    _UpperCamelCase							(  self :List[Any]       ,    __magic_name__ :List[Any]			)			->   None:

			'''simple docstring'''






			a__   		=     config

			a__   		=     getattr(__magic_name__       ,    '''use_timm_backbone'''       ,    __magic_name__			)
			a__   		=     BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

			if self.backbone_type == BackboneType.TIMM:
					self._init_timm_backbone(__magic_name__			)
			elif self.backbone_type == BackboneType.TRANSFORMERS:
					self._init_transformers_backbone(__magic_name__			)
			else:
					raise ValueError(F"backbone_type {self.backbone_type} not supported."			)


	@property
	def    _UpperCamelCase							(  self :Tuple			)			->   List[Any]:

			'''simple docstring'''






			return self._out_features


	@out_features.setter
	def    _UpperCamelCase							(  self :List[Any]       ,    __magic_name__ :List[str]			)			->   List[str]:

			'''simple docstring'''






			a__		,	a__   		=     get_aligned_output_features_output_indices(
			    out_features=__magic_name__       ,    out_indices=__magic_name__       ,    stage_names=self.stage_names			)


	@property
	def    _UpperCamelCase							(  self :int			)			->   Dict:

			'''simple docstring'''






			return self._out_indices


	@out_indices.setter
	def    _UpperCamelCase							(  self :Optional[int]       ,    __magic_name__ :Union[Tuple[int], List[int]]			)			->   Optional[Any]:

			'''simple docstring'''






			a__		,	a__   		=     get_aligned_output_features_output_indices(
			    out_features=__magic_name__       ,    out_indices=__magic_name__       ,    stage_names=self.stage_names			)


	@property
	def    _UpperCamelCase							(  self :Any			)			->   int:

			'''simple docstring'''






			return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names			)}


	@property
	def    _UpperCamelCase							(  self :Any			)			->   List[str]:

			'''simple docstring'''






			return [self.out_feature_channels[name] for name in self.out_features]


	def    _UpperCamelCase							(  self :Tuple       ,    *__magic_name__ :Optional[Any]       ,    **__magic_name__ :Dict			)			->   List[str]:

			'''simple docstring'''






			a__   		=     dict(inspect.signature(self.forward			).parameters			)
			a__   		=     {k: v for k, v in kwargs.items() if k in signature}
			return self(*__magic_name__       ,    **__magic_name__			)


	def    _UpperCamelCase							(  self :Optional[int]       ,    __magic_name__ :Tuple       ,    __magic_name__ :Optional[bool] = None       ,    __magic_name__ :Optional[bool] = None       ,    __magic_name__ :Optional[bool] = None       ,    )			->   Optional[int]:

			'''simple docstring'''






			raise NotImplementedError('''This method should be implemented by the derived class.'''			)






	def    _UpperCamelCase							(  self :Optional[int]			)			->   Optional[Any]:

			'''simple docstring'''






			a__   		=     super().to_dict()
			a__   		=     output.pop('''_out_features'''			)
			a__   		=     output.pop('''_out_indices'''			)
			return output

class SCREAMING_SNAKE_CASE       :






	'''simple docstring'''







	@property
	def    _UpperCamelCase							(  self :Any			)			->   List[str]:

			'''simple docstring'''






			return self._out_features


	@out_features.setter
	def    _UpperCamelCase							(  self :Tuple       ,    __magic_name__ :List[str]			)			->   Any:

			'''simple docstring'''






			a__		,	a__   		=     get_aligned_output_features_output_indices(
			    out_features=__magic_name__       ,    out_indices=__magic_name__       ,    stage_names=self.stage_names			)


	@property
	def    _UpperCamelCase							(  self :Dict			)			->   List[str]:

			'''simple docstring'''






			return self._out_indices


	@out_indices.setter
	def    _UpperCamelCase							(  self :Optional[Any]       ,    __magic_name__ :Union[Tuple[int], List[int]]			)			->   Union[str, Any]:

			'''simple docstring'''






			a__		,	a__   		=     get_aligned_output_features_output_indices(
			    out_features=__magic_name__       ,    out_indices=__magic_name__       ,    stage_names=self.stage_names			)






	def    _UpperCamelCase							(  self :int			)			->   List[Any]:

			'''simple docstring'''






			a__   		=     super().to_dict()
			a__   		=     output.pop('''_out_features'''			)
			a__   		=     output.pop('''_out_indices'''			)
			return output






"""simple docstring"""




import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

__lowerCAmelCase							:  Dict 				=		logging.getLogger()

def __snake_case (      )       ->    Optional[int]:


		"""simple docstring"""





		a__   		=     argparse.ArgumentParser()
		parser.add_argument('''-f'''    )
		a__   		=     parser.parse_args()
		return args.f




class SCREAMING_SNAKE_CASE       (      lowerCAmelCase					):






	'''simple docstring'''







	def    _UpperCamelCase							(  self :Tuple			)			->   Union[str, Any]:

			'''simple docstring'''






			a__   		=     logging.StreamHandler(sys.stdout			)
			logger.addHandler(__magic_name__			)

			a__   		=     self.get_auto_remove_tmp_dir()
			a__   		=     F"\n            run_glue_with_pabee.py\n            --model_type albert\n            --model_name_or_path albert-base-v2\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --task_name mrpc\n            --do_train\n            --do_eval\n            --per_gpu_train_batch_size=2\n            --per_gpu_eval_batch_size=1\n            --learning_rate=2e-5\n            --max_steps=50\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            ".split()

			with patch.object(__magic_name__       ,    '''argv'''       ,    __magic_name__			):
					a__   		=     run_glue_with_pabee.main()
					for value in result.values():
							self.assertGreaterEqual(__magic_name__       ,    0.75			)




