




import inspect
import os
import unittest
from pathlib import Path

import torch

import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command






class  __magic_name__						(  unittest.TestCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							List[Any]	      =					inspect.getfile(accelerate.test_utils)
				SCREAMING_SNAKE_CASE__					:							List[Any]	      =					os.path.sep.join(mod_file.split(os.path.sep)[:-1] + ["scripts", "test_cli.py"])

				SCREAMING_SNAKE_CASE__					:							Any	      =					["accelerate", "launch"]
				SCREAMING_SNAKE_CASE__					:							Tuple	      =					Path.home() / ".cache/huggingface/accelerate"
				SCREAMING_SNAKE_CASE__					:							int	      =					"default_config.yaml"
				SCREAMING_SNAKE_CASE__					:							Any	      =					config_folder / config_file
				SCREAMING_SNAKE_CASE__					:							Union[str, Any]	      =					config_folder / "_default_config.yaml"

				SCREAMING_SNAKE_CASE__					:							Optional[Any]	      =					Path("tests/test_configs")


				@classmethod
				def     _A							(							cls:   Tuple		):
											if cls.config_path.is_file():
																		cls.config_path.rename(cls.changed_path		)


				@classmethod
				def     _A							(							cls:   Union[str, Any]		):
											if cls.changed_path.is_file():
																		cls.changed_path.rename(cls.config_path		)


				def     _A							(							self:   Optional[Any]		):
											SCREAMING_SNAKE_CASE_   	=    self.base_cmd
											if torch.cuda.is_available() and (torch.cuda.device_count() > 1):
																		cmd += ["--multi_gpu"]
											execute_subprocess_async(cmd + [self.test_file_path]		,					env=os.environ.copy()		)


				def     _A							(							self:   List[str]		):
											for config in sorted(self.test_config_path.glob('''**/*.yaml'''		)		):
																		with self.subTest(config_file=A__		):
																									execute_subprocess_async(
																									    self.base_cmd + ['''--config_file''', str(A__		), self.test_file_path]		,					env=os.environ.copy()		)





				def     _A							(							self:   str		):
											execute_subprocess_async(['''accelerate''', '''test''']		,					env=os.environ.copy()		)






class  __magic_name__						(  unittest.TestCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							Dict	      =					"test-tpu"
				SCREAMING_SNAKE_CASE__					:							int	      =					"us-central1-a"
				SCREAMING_SNAKE_CASE__					:							List[Any]	      =					"ls"
				SCREAMING_SNAKE_CASE__					:							Optional[int]	      =					["accelerate", "tpu-config"]
				SCREAMING_SNAKE_CASE__					:							Tuple	      =					"cd /usr/share"
				SCREAMING_SNAKE_CASE__					:							str	      =					"tests/test_samples/test_command_file.sh"
				SCREAMING_SNAKE_CASE__					:							str	      =					"Running gcloud compute tpus tpu-vm ssh"


				def     _A							(							self:   List[Any]		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd
											    + ['''--command''', self.command, '''--tpu_zone''', self.tpu_zone, '''--tpu_name''', self.tpu_name, '''--debug''']		,					return_stdout=A__		,					)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"		,					A__		,					)


				def     _A							(							self:   Any		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd
											    + [
											        '''--config_file''',
											        '''tests/test_configs/0_12_0.yaml''',
											        '''--command''',
											        self.command,
											        '''--tpu_zone''',
											        self.tpu_zone,
											        '''--tpu_name''',
											        self.tpu_name,
											        '''--debug''',
											    ]		,					return_stdout=A__		,					)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"		,					A__		,					)


				def     _A							(							self:   Optional[Any]		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd + ['''--config_file''', '''tests/test_configs/latest.yaml''', '''--debug''']		,					return_stdout=A__		)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"		,					A__		,					)


				def     _A							(							self:   Optional[Any]		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd + ['''--config_file''', '''tests/test_configs/latest.yaml''', '''--command''', self.command, '''--debug''']		,					return_stdout=A__		,					)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"		,					A__		,					)


				def     _A							(							self:   Optional[int]		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd
											    + [
											        '''--config_file''',
											        '''tests/test_configs/latest.yaml''',
											        '''--command''',
											        self.command,
											        '''--command''',
											        '''echo "Hello World"''',
											        '''--debug''',
											    ]		,					return_stdout=A__		,					)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls; echo \"Hello World\" --worker all"		,					A__		,					)


				def     _A							(							self:   Optional[int]		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd
											    + ['''--config_file''', '''tests/test_configs/latest.yaml''', '''--command_file''', self.command_file, '''--debug''']		,					return_stdout=A__		,					)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"		,					A__		,					)


				def     _A							(							self:   int		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd
											    + [
											        '''--config_file''',
											        '''tests/test_configs/0_12_0.yaml''',
											        '''--command_file''',
											        self.command_file,
											        '''--tpu_zone''',
											        self.tpu_zone,
											        '''--tpu_name''',
											        self.tpu_name,
											        '''--debug''',
											    ]		,					return_stdout=A__		,					)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"		,					A__		,					)


				def     _A							(							self:   Union[str, Any]		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd + ['''--config_file''', '''tests/test_configs/latest.yaml''', '''--install_accelerate''', '''--debug''']		,					return_stdout=A__		,					)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate -U; echo \"hello world\"; echo \"this is a second command\" --worker all"		,					A__		,					)





				def     _A							(							self:   Optional[Any]		):
											SCREAMING_SNAKE_CASE_   	=    run_command(
											    self.cmd
											    + [
											        '''--config_file''',
											        '''tests/test_configs/latest.yaml''',
											        '''--install_accelerate''',
											        '''--accelerate_version''',
											        '''12.0.0''',
											        '''--debug''',
											    ]		,					return_stdout=A__		,					)
											self.assertIn(
											    f"{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate==12.0.0; echo \"hello world\"; echo \"this is a second command\" --worker all"		,					A__		,					)








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  __magic_name__						:
				'''simple docstring'''







				def __init__(							self:   Optional[int]		,					_lowerCamelCase:   Tuple		,					_lowerCamelCase:   Any=None		,					_lowerCamelCase:   Any=None		,					_lowerCamelCase:   Tuple=None		,					_lowerCamelCase:   Optional[Any]="resnet50"		,					_lowerCamelCase:   Any=3		,					_lowerCamelCase:   Optional[int]=32		,					_lowerCamelCase:   List[Any]=3		,					_lowerCamelCase:   int=True		,					_lowerCamelCase:   Any=True		,					):
											SCREAMING_SNAKE_CASE_   	=    parent
											SCREAMING_SNAKE_CASE_   	=    out_indices if out_indices is not None else [4]
											SCREAMING_SNAKE_CASE_   	=    stage_names
											SCREAMING_SNAKE_CASE_   	=    out_features
											SCREAMING_SNAKE_CASE_   	=    backbone
											SCREAMING_SNAKE_CASE_   	=    batch_size
											SCREAMING_SNAKE_CASE_   	=    image_size
											SCREAMING_SNAKE_CASE_   	=    num_channels
											SCREAMING_SNAKE_CASE_   	=    use_pretrained_backbone
											SCREAMING_SNAKE_CASE_   	=    is_training


				def     _A							(							self:   Optional[Any]		):
											SCREAMING_SNAKE_CASE_   	=    floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]		)
											SCREAMING_SNAKE_CASE_   	=    self.get_config()

											return config, pixel_values


				def     _A							(							self:   List[Any]		):
											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     _A							(							self:   str		,					_lowerCamelCase:   str		,					_lowerCamelCase:   Optional[Any]		):
											SCREAMING_SNAKE_CASE_   	=    TimmBackbone(config=_lowerCamelCase		)
											model.to(_lowerCamelCase		)
											model.eval()
											with torch.no_grad():
																		SCREAMING_SNAKE_CASE_   	=    model(_lowerCamelCase		)
											self.parent.assertEqual(
											    result.feature_map[-1].shape		,					(self.batch_size, model.channels[-1], 14, 14)		,					)





				def     _A							(							self:   Optional[Any]		):
											SCREAMING_SNAKE_CASE_   	=    self.prepare_config_and_inputs()
											SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_   	=    config_and_inputs
											SCREAMING_SNAKE_CASE_   	=    {'''pixel_values''': pixel_values}
											return config, inputs_dict






@require_torch
@require_timm
class  __magic_name__						(  __UpperCAmelCase    ,  __UpperCAmelCase    ,  __UpperCAmelCase    ,  unittest.TestCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							List[str]	      =					(TimmBackbone,) if is_torch_available() else ()
				SCREAMING_SNAKE_CASE__					:							List[str]	      =					{"feature-extraction": TimmBackbone} if is_torch_available() else {}
				SCREAMING_SNAKE_CASE__					:							Tuple	      =					False
				SCREAMING_SNAKE_CASE__					:							Optional[int]	      =					False
				SCREAMING_SNAKE_CASE__					:							Any	      =					False
				SCREAMING_SNAKE_CASE__					:							Any	      =					False


				def     _A							(							self:   int		):
											SCREAMING_SNAKE_CASE_   	=    TimmBackboneModelTester(self		)
											SCREAMING_SNAKE_CASE_   	=    ConfigTester(self		,					config_class=_lowerCamelCase		,					has_text_modality=_lowerCamelCase		)


				def     _A							(							self:   str		):
											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     _A							(							self:   List[Any]		):
											SCREAMING_SNAKE_CASE_   	=    '''resnet18'''
											SCREAMING_SNAKE_CASE_   	=    '''microsoft/resnet-18'''

											SCREAMING_SNAKE_CASE_   	=    AutoBackbone.from_pretrained(_lowerCamelCase		,					use_timm_backbone=_lowerCamelCase		)
											SCREAMING_SNAKE_CASE_   	=    AutoBackbone.from_pretrained(_lowerCamelCase		)

											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]		)

											SCREAMING_SNAKE_CASE_   	=    AutoBackbone.from_pretrained(_lowerCamelCase		,					use_timm_backbone=_lowerCamelCase		,					out_indices=[1, 2, 3]		)
											SCREAMING_SNAKE_CASE_   	=    AutoBackbone.from_pretrained(_lowerCamelCase		,					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     _A							(							self:   Optional[Any]		):
											pass


				@unittest.skip('''TimmBackbone doesn\'t have num_hidden_layers attribute'''		)
				def     _A							(							self:   Any		):
											pass


				@unittest.skip('''TimmBackbone initialization is managed on the timm side'''		)
				def     _A							(							self:   Dict		):
											pass


				@unittest.skip('''TimmBackbone models doesn\'t have inputs_embeds'''		)
				def     _A							(							self:   Optional[Any]		):
											pass


				@unittest.skip('''TimmBackbone models doesn\'t have inputs_embeds'''		)
				def     _A							(							self:   List[Any]		):
											pass


				@unittest.skip('''TimmBackbone model cannot be created without specifying a backbone checkpoint'''		)
				def     _A							(							self:   Tuple		):
											pass


				@unittest.skip('''Only checkpoints on timm can be loaded into TimmBackbone'''		)
				def     _A							(							self:   List[str]		):
											pass


				@unittest.skip('''model weights aren\'t tied in TimmBackbone.'''		)
				def     _A							(							self:   Any		):
											pass


				@unittest.skip('''model weights aren\'t tied in TimmBackbone.'''		)
				def     _A							(							self:   Tuple		):
											pass


				@unittest.skip('''Only checkpoints on timm can be loaded into TimmBackbone'''		)
				def     _A							(							self:   Optional[int]		):
											pass


				@unittest.skip('''Only checkpoints on timm can be loaded into TimmBackbone'''		)
				def     _A							(							self:   Union[str, Any]		):
											pass


				@unittest.skip('''TimmBackbone doesn\'t have hidden size info in its configuration.'''		)
				def     _A							(							self:   Any		):
											pass


				@unittest.skip('''TimmBackbone doesn\'t support output_attentions.'''		)
				def     _A							(							self:   Tuple		):
											pass


				@unittest.skip('''Safetensors is not supported by timm.'''		)
				def     _A							(							self:   Optional[int]		):
											pass


				@unittest.skip('''Will be fixed soon by reducing the size of the model used for common tests.'''		)
				def     _A							(							self:   str		):
											pass


				def     _A							(							self:   Dict		):
											SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_   	=    self.model_tester.prepare_config_and_inputs_for_common()

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

																		SCREAMING_SNAKE_CASE_   	=    ['''pixel_values''']
																		self.assertListEqual(arg_names[:1]		,					_lowerCamelCase		)


				def     _A							(							self:   Dict		):
											SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_   	=    self.model_tester.prepare_config_and_inputs_for_common()
											SCREAMING_SNAKE_CASE_   	=    True
											SCREAMING_SNAKE_CASE_   	=    self.has_attentions

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

											SCREAMING_SNAKE_CASE_   	=    self._prepare_for_class(_lowerCamelCase		,					_lowerCamelCase		)
											SCREAMING_SNAKE_CASE_   	=    model(**_lowerCamelCase		)
											SCREAMING_SNAKE_CASE_   	=    outputs[0][-1]

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

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

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

											self.assertIsNotNone(hidden_states.grad		)

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





				def     _A							(							self:   List[str]		):
											SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_   	=    self.model_tester.prepare_config_and_inputs_for_common()

											for model_class in self.all_model_classes:
																		SCREAMING_SNAKE_CASE_   	=    model_class(_lowerCamelCase		)
																		model.to(_lowerCamelCase		)
																		model.eval()
																		SCREAMING_SNAKE_CASE_   	=    model(**_lowerCamelCase		)

																		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
																		SCREAMING_SNAKE_CASE_   	=    copy.deepcopy(_lowerCamelCase		)
																		SCREAMING_SNAKE_CASE_   	=    None
																		SCREAMING_SNAKE_CASE_   	=    model_class(_lowerCamelCase		)
																		model.to(_lowerCamelCase		)
																		model.eval()
																		SCREAMING_SNAKE_CASE_   	=    model(**_lowerCamelCase		)

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

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


