



import copy
import inspect
import unittest

from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available

from ...test_backbone_common import BackboneTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor


if is_torch_available():
	import torch

	from transformers import TimmBackbone, TimmBackboneConfig

from ...test_pipeline_mixin import PipelineTesterMixin


class       _lowercase   :
				'''simple docstring'''







				def __init__( self     , snake_case__     , snake_case__=None     , snake_case__=None     , snake_case__=None     , snake_case__="resnet50"     , snake_case__=3     , snake_case__=32     , snake_case__=3     , snake_case__=True     , snake_case__=True     , ):

									'''simple docstring'''


									UpperCamelCase_		  =   parent
									UpperCamelCase_		  =   out_indices if out_indices is not None else [4]
									UpperCamelCase_		  =   stage_names
									UpperCamelCase_		  =   out_features
									UpperCamelCase_		  =   backbone
									UpperCamelCase_		  =   batch_size
									UpperCamelCase_		  =   image_size
									UpperCamelCase_		  =   num_channels
									UpperCamelCase_		  =   use_pretrained_backbone
									UpperCamelCase_		  =   is_training

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]    )
									UpperCamelCase_		  =   self.get_config()

									return config, pixel_values

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									return TimmBackboneConfig(
									    image_size=self.image_size     , num_channels=self.num_channels     , out_features=self.out_features     , out_indices=self.out_indices     , stage_names=self.stage_names     , use_pretrained_backbone=self.use_pretrained_backbone     , backbone=self.backbone     , )

				def       _lowerCamelCase					( self     , snake_case__     , snake_case__    ):

									'''simple docstring'''


									UpperCamelCase_		  =   TimmBackbone(config=snake_case__    )
									model.to(snake_case__    )
									model.eval()
									with torch.no_grad():
														UpperCamelCase_		  =   model(snake_case__    )
									self.parent.assertEqual(
									    result.feature_map[-1].shape     , (self.batch_size, model.channels[-1], 14, 14)     , )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   self.prepare_config_and_inputs()
									UpperCamelCase_  ,    UpperCamelCase_		  =   config_and_inputs
									UpperCamelCase_		  =   {"pixel_values": pixel_values}
									return config, inputs_dict




@require_torch
@require_timm
class       _lowercase   (a_      ,   a_      ,   a_      ,   unittest.TestCase      ):
				'''simple docstring'''







				lowercase__   						=						(TimmBackbone,) if is_torch_available() else ()
				lowercase__   						=						{"""feature-extraction""": TimmBackbone} if is_torch_available() else {}
				lowercase__   						=						False
				lowercase__   						=						False
				lowercase__   						=						False
				lowercase__   						=						False

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   TimmBackboneModelTester(self    )
									UpperCamelCase_		  =   ConfigTester(self     , config_class=snake_case__     , has_text_modality=snake_case__    )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									self.config_tester.create_and_test_config_to_json_string()
									self.config_tester.create_and_test_config_to_json_file()
									self.config_tester.create_and_test_config_from_and_save_pretrained()
									self.config_tester.create_and_test_config_with_num_labels()
									self.config_tester.check_config_can_be_init_without_params()
									self.config_tester.check_config_arguments_init()

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_		  =   "resnet18"
									UpperCamelCase_		  =   "microsoft/resnet-18"

									UpperCamelCase_		  =   AutoBackbone.from_pretrained(snake_case__     , use_timm_backbone=snake_case__    )
									UpperCamelCase_		  =   AutoBackbone.from_pretrained(snake_case__    )

									self.assertEqual(len(timm_model.out_features    )     , len(transformers_model.out_features    )    )
									self.assertEqual(len(timm_model.stage_names    )     , len(transformers_model.stage_names    )    )
									self.assertEqual(timm_model.channels     , transformers_model.channels    )
									# Out indices are set to the last layer by default. For timm models, we don't know
									# the number of layers in advance, so we set it to (-1,), whereas for transformers
									# models, we set it to [len(stage_names) - 1] (kept for backward compatibility).
									self.assertEqual(timm_model.out_indices     , (-1,)    )
									self.assertEqual(transformers_model.out_indices     , [len(timm_model.stage_names    ) - 1]    )

									UpperCamelCase_		  =   AutoBackbone.from_pretrained(snake_case__     , use_timm_backbone=snake_case__     , out_indices=[1, 2, 3]    )
									UpperCamelCase_		  =   AutoBackbone.from_pretrained(snake_case__     , out_indices=[1, 2, 3]    )

									self.assertEqual(timm_model.out_indices     , transformers_model.out_indices    )
									self.assertEqual(len(timm_model.out_features    )     , len(transformers_model.out_features    )    )
									self.assertEqual(timm_model.channels     , transformers_model.channels    )

				@unittest.skip("TimmBackbone doesn't support feed forward chunking"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("TimmBackbone doesn't have num_hidden_layers attribute"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("TimmBackbone initialization is managed on the timm side"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("TimmBackbone models doesn't have inputs_embeds"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("TimmBackbone models doesn't have inputs_embeds"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("TimmBackbone model cannot be created without specifying a backbone checkpoint"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("Only checkpoints on timm can be loaded into TimmBackbone"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("model weights aren't tied in TimmBackbone."    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("model weights aren't tied in TimmBackbone."    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("Only checkpoints on timm can be loaded into TimmBackbone"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("Only checkpoints on timm can be loaded into TimmBackbone"    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("TimmBackbone doesn't have hidden size info in its configuration."    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("TimmBackbone doesn't support output_attentions."    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("Safetensors is not supported by timm."    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				@unittest.skip("Will be fixed soon by reducing the size of the model used for common tests."    )
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									pass

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_  ,    UpperCamelCase_		  =   self.model_tester.prepare_config_and_inputs_for_common()

									for model_class in self.all_model_classes:
														UpperCamelCase_		  =   model_class(snake_case__    )
														UpperCamelCase_		  =   inspect.signature(model.forward    )
														# signature.parameters is an OrderedDict => so arg_names order is deterministic
														UpperCamelCase_		  =   [*signature.parameters.keys()]

														UpperCamelCase_		  =   ["pixel_values"]
														self.assertListEqual(arg_names[:1]     , snake_case__    )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_  ,    UpperCamelCase_		  =   self.model_tester.prepare_config_and_inputs_for_common()
									UpperCamelCase_		  =   True
									UpperCamelCase_		  =   self.has_attentions

									# no need to test all models as different heads yield the same functionality
									UpperCamelCase_		  =   self.all_model_classes[0]
									UpperCamelCase_		  =   model_class(snake_case__    )
									model.to(snake_case__    )

									UpperCamelCase_		  =   self._prepare_for_class(snake_case__     , snake_case__    )
									UpperCamelCase_		  =   model(**snake_case__    )
									UpperCamelCase_		  =   outputs[0][-1]

									# Encoder-/Decoder-only models
									UpperCamelCase_		  =   outputs.hidden_states[0]
									hidden_states.retain_grad()

									if self.has_attentions:
														UpperCamelCase_		  =   outputs.attentions[0]
														attentions.retain_grad()

									output.flatten()[0].backward(retain_graph=snake_case__    )

									self.assertIsNotNone(hidden_states.grad    )

									if self.has_attentions:
														self.assertIsNotNone(attentions.grad    )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									UpperCamelCase_  ,    UpperCamelCase_		  =   self.model_tester.prepare_config_and_inputs_for_common()

									for model_class in self.all_model_classes:
														UpperCamelCase_		  =   model_class(snake_case__    )
														model.to(snake_case__    )
														model.eval()
														UpperCamelCase_		  =   model(**snake_case__    )

														self.assertEqual(len(result.feature_maps    )     , len(config.out_indices    )    )
														self.assertEqual(len(model.channels    )     , len(config.out_indices    )    )

														# Check output of last stage is taken if out_features=None, out_indices=None
														UpperCamelCase_		  =   copy.deepcopy(snake_case__    )
														UpperCamelCase_		  =   None
														UpperCamelCase_		  =   model_class(snake_case__    )
														model.to(snake_case__    )
														model.eval()
														UpperCamelCase_		  =   model(**snake_case__    )

														self.assertEqual(len(result.feature_maps    )     , 1    )
														self.assertEqual(len(model.channels    )     , 1    )

														# Check backbone can be initialized with fresh weights
														UpperCamelCase_		  =   copy.deepcopy(snake_case__    )
														UpperCamelCase_		  =   False
														UpperCamelCase_		  =   model_class(snake_case__    )
														model.to(snake_case__    )
														model.eval()
														UpperCamelCase_		  =   model(**snake_case__    )





import functools
import logging
import os
import sys
import threading
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

import huggingface_hub.utils as hf_hub_utils
from tqdm import auto as tqdm_lib


UpperCAmelCase   :							int							 =threading.Lock()
UpperCAmelCase   :							Optional[logging.Handler]							 =None

UpperCAmelCase   :							List[Any]							 ={
    """debug""": logging.DEBUG,
    """info""": logging.INFO,
    """warning""": logging.WARNING,
    """error""": logging.ERROR,
    """critical""": logging.CRITICAL,
}

UpperCAmelCase   :							Any							 =logging.WARNING

UpperCAmelCase   :							List[Any]							 =True



def    _lowerCAmelCase    ():
					UpperCamelCase_		  =   os.getenv("TRANSFORMERS_VERBOSITY"   ,	_lowerCAmelCase)
					if env_level_str:
										if env_level_str in log_levels:
															return log_levels[env_level_str]
										else:
															logging.getLogger().warning(
															    f"""Unknown option TRANSFORMERS_VERBOSITY={env_level_str}, """
															    f"""has to be one of: { ', '.join(log_levels.keys()) }""")
					return _default_log_level



def    _lowerCAmelCase    ():
					return __name__.split(".")[0]



def    _lowerCAmelCase    ():
					return logging.getLogger(_get_library_name())



def    _lowerCAmelCase    ():
					global _default_handler

					with _lock:
										if _default_handler:
															# This library has already configured the library root logger.
															return
										UpperCamelCase_		  =   logging.StreamHandler()  # Set sys.stderr as stream.
										UpperCamelCase_		  =   sys.stderr.flush

										# Apply our default configuration to the library root logger.
										UpperCamelCase_		  =   _get_library_root_logger()
										library_root_logger.addHandler(_default_handler)
										library_root_logger.setLevel(_get_default_logging_level())
										UpperCamelCase_		  =   False



def    _lowerCAmelCase    ():
					global _default_handler

					with _lock:
										if not _default_handler:
															return

										UpperCamelCase_		  =   _get_library_root_logger()
										library_root_logger.removeHandler(_default_handler)
										library_root_logger.setLevel(logging.NOTSET)
										UpperCamelCase_		  =   None



def    _lowerCAmelCase    ():
					return log_levels



def    _lowerCAmelCase    (_lowerCAmelCase = None):

					if name is None:
										UpperCamelCase_		  =   _get_library_name()

					_configure_library_root_logger()
					return logging.getLogger(_lowerCAmelCase)



def    _lowerCAmelCase    ():
					_configure_library_root_logger()
					return _get_library_root_logger().getEffectiveLevel()



def    _lowerCAmelCase    (_lowerCAmelCase):
					_configure_library_root_logger()
					_get_library_root_logger().setLevel(_lowerCAmelCase)



def    _lowerCAmelCase    ():
					return set_verbosity(_lowerCAmelCase)



def    _lowerCAmelCase    ():
					return set_verbosity(_lowerCAmelCase)



def    _lowerCAmelCase    ():
					return set_verbosity(_lowerCAmelCase)



def    _lowerCAmelCase    ():
					return set_verbosity(_lowerCAmelCase)



def    _lowerCAmelCase    ():
					_configure_library_root_logger()

					assert _default_handler is not None
					_get_library_root_logger().removeHandler(_default_handler)



def    _lowerCAmelCase    ():
					_configure_library_root_logger()

					assert _default_handler is not None
					_get_library_root_logger().addHandler(_default_handler)



def    _lowerCAmelCase    (_lowerCAmelCase):
					_configure_library_root_logger()

					assert handler is not None
					_get_library_root_logger().addHandler(_lowerCAmelCase)



def    _lowerCAmelCase    (_lowerCAmelCase):
					_configure_library_root_logger()

					assert handler is not None and handler not in _get_library_root_logger().handlers
					_get_library_root_logger().removeHandler(_lowerCAmelCase)



def    _lowerCAmelCase    ():
					_configure_library_root_logger()
					UpperCamelCase_		  =   False



def    _lowerCAmelCase    ():
					_configure_library_root_logger()
					UpperCamelCase_		  =   True



def    _lowerCAmelCase    ():
					UpperCamelCase_		  =   _get_library_root_logger().handlers

					for handler in handlers:
										UpperCamelCase_		  =   logging.Formatter("[%(levelname)s|%(filename)s:%(lineno)s] %(asctime)s >> %(message)s")
										handler.setFormatter(_lowerCAmelCase)



def    _lowerCAmelCase    ():
					UpperCamelCase_		  =   _get_library_root_logger().handlers

					for handler in handlers:
										handler.setFormatter(_lowerCAmelCase)



def    _lowerCAmelCase    (self   ,	*_lowerCAmelCase   ,	**_lowerCAmelCase):
					UpperCamelCase_		  =   os.getenv("TRANSFORMERS_NO_ADVISORY_WARNINGS"   ,	_lowerCAmelCase)
					if no_advisory_warnings:
										return
					self.warning(*_lowerCAmelCase   ,	**_lowerCAmelCase)


UpperCAmelCase   :							Dict							 =warning_advice



@functools.lru_cache(_lowerCAmelCase)
def    _lowerCAmelCase    (self   ,	*_lowerCAmelCase   ,	**_lowerCAmelCase):
					self.warning(*_lowerCAmelCase   ,	**_lowerCAmelCase)


UpperCAmelCase   :							Optional[Any]							 =warning_once


class       _lowercase   :
				'''simple docstring'''







				def __init__( self     , *snake_case__     , **snake_case__    ):  # pylint: disable=unused-argument

									'''simple docstring'''


									UpperCamelCase_		  =   args[0] if args else None

				def __iter__( self    ):

									'''simple docstring'''


									return iter(self._iterator    )

				def __getattr__( self     , snake_case__    ):

									'''simple docstring'''


									def empty_fn(*snake_case__     , **snake_case__    ):  # pylint: disable=unused-argument
														return

									return empty_fn

				def __enter__( self    ):

									'''simple docstring'''


									return self

				def __exit__( self     , snake_case__     , snake_case__     , snake_case__    ):

									'''simple docstring'''


									return




class       _lowercase   :
				'''simple docstring'''







				def __call__( self     , *snake_case__     , **snake_case__    ):

									'''simple docstring'''


									if _tqdm_active:
														return tqdm_lib.tqdm(*snake_case__     , **snake_case__    )
									else:
														return EmptyTqdm(*snake_case__     , **snake_case__    )

				def       _lowerCamelCase					( self     , *snake_case__     , **snake_case__    ):

									'''simple docstring'''


									UpperCamelCase_		  =   None
									if _tqdm_active:
														return tqdm_lib.tqdm.set_lock(*snake_case__     , **snake_case__    )

				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									if _tqdm_active:
														return tqdm_lib.tqdm.get_lock()




UpperCAmelCase   :							Tuple							 =_tqdm_cls()



def    _lowerCAmelCase    ():
					global _tqdm_active
					return bool(_tqdm_active)



def    _lowerCAmelCase    ():
					global _tqdm_active
					UpperCamelCase_		  =   True
					hf_hub_utils.enable_progress_bars()






def    _lowerCAmelCase    ():
					global _tqdm_active
					UpperCamelCase_		  =   False
					hf_hub_utils.disable_progress_bars()
