


import inspect
import unittest

from transformers import ResNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available

from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor


if is_flax_available():
	import jax
	import jax.numpy as jnp

	from transformers.models.resnet.modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel

if is_vision_available():
	from PIL import Image

	from transformers import AutoImageProcessor



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






					def __init__(self					:		Dict   ,      _UpperCAmelCase					:		Union[str, Any]   ,      _UpperCAmelCase					:		List[Any]=3   ,      _UpperCAmelCase					:		int=32   ,      _UpperCAmelCase					:		Union[str, Any]=3   ,      _UpperCAmelCase					:		Optional[Any]=10   ,      _UpperCAmelCase					:		Any=[10, 20, 30, 40]   ,      _UpperCAmelCase					:		str=[1, 1, 2, 1]   ,      _UpperCAmelCase					:		List[Any]=True   ,      _UpperCAmelCase					:		Dict=True   ,      _UpperCAmelCase					:		List[Any]="relu"   ,      _UpperCAmelCase					:		Any=3   ,      _UpperCAmelCase					:		Dict=None   ,      )		->     Optional[Any]:




							"""simple docstring"""


							lowercase__      =	parent
							lowercase__      =	batch_size
							lowercase__      =	image_size
							lowercase__      =	num_channels
							lowercase__      =	embeddings_size
							lowercase__      =	hidden_sizes
							lowercase__      =	depths
							lowercase__      =	is_training
							lowercase__      =	use_labels
							lowercase__      =	hidden_act
							lowercase__      =	num_labels
							lowercase__      =	scope
							lowercase__      =	len(_UpperCAmelCase	)

					def 						lowerCamelCase__  (self					:		Dict	)		->     Tuple:




							"""simple docstring"""


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

							lowercase__      =	self.get_config()

							return config, pixel_values

					def 						lowerCamelCase__  (self					:		List[str]	)		->     List[Any]:




							"""simple docstring"""


							return ResNetConfig(
							    num_channels=self.num_channels   ,      embeddings_size=self.embeddings_size   ,      hidden_sizes=self.hidden_sizes   ,      depths=self.depths   ,      hidden_act=self.hidden_act   ,      num_labels=self.num_labels   ,      image_size=self.image_size   ,      )

					def 						lowerCamelCase__  (self					:		Dict   ,      _UpperCAmelCase					:		str   ,      _UpperCAmelCase					:		List[Any]	)		->     int:




							"""simple docstring"""


							lowercase__      =	FlaxResNetModel(config=_UpperCAmelCase	)
							lowercase__      =	model(_UpperCAmelCase	)

							# Output shape (b, c, h, w)
							self.parent.assertEqual(
							    result.last_hidden_state.shape   ,      (self.batch_size, self.hidden_sizes[-1], self.image_size // 32, self.image_size // 32)   ,      )

					def 						lowerCamelCase__  (self					:		List[str]   ,      _UpperCAmelCase					:		Any   ,      _UpperCAmelCase					:		int	)		->     int:




							"""simple docstring"""


							lowercase__      =	self.num_labels
							lowercase__      =	FlaxResNetForImageClassification(config=_UpperCAmelCase	)
							lowercase__      =	model(_UpperCAmelCase	)
							self.parent.assertEqual(result.logits.shape   ,      (self.batch_size, self.num_labels)	)


					def 						lowerCamelCase__  (self					:		List[str]	)		->     Optional[Any]:




							"""simple docstring"""


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






@require_flax
class 							A					( UpperCAmelCase__				,						unittest.TestCase							):
					'''simple docstring'''






					A__    =				(FlaxResNetModel, FlaxResNetForImageClassification) if is_flax_available() else ()

					A__    =				False
					A__    =				False
					A__    =				False

					def 						lowerCamelCase__  (self					:		Tuple	)		->     None:




							"""simple docstring"""


							lowercase__      =	FlaxResNetModelTester(self	)
							lowercase__      =	ConfigTester(self   ,      config_class=_UpperCAmelCase   ,      has_text_modality=_UpperCAmelCase	)

					def 						lowerCamelCase__  (self					:		Dict	)		->     Dict:




							"""simple docstring"""


							self.create_and_test_config_common_properties()
							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					:		Optional[int]	)		->     Any:




							"""simple docstring"""


							return

					def 						lowerCamelCase__  (self					:		Union[str, Any]	)		->     Optional[int]:




							"""simple docstring"""


							lowercase__      =	self.model_tester.prepare_config_and_inputs()
							self.model_tester.create_and_check_model(*_UpperCAmelCase	)

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




							"""simple docstring"""


							lowercase__      =	self.model_tester.prepare_config_and_inputs()
							self.model_tester.create_and_check_for_image_classification(*_UpperCAmelCase	)

					@unittest.skip(reason="""ResNet does not use inputs_embeds"""	)
					def 						lowerCamelCase__  (self					:		Dict	)		->     Dict:




							"""simple docstring"""


							pass

					@unittest.skip(reason="""ResNet does not support input and output embeddings"""	)
					def 						lowerCamelCase__  (self					:		Dict	)		->     Optional[Any]:




							"""simple docstring"""


							pass

					def 						lowerCamelCase__  (self					:		Union[str, Any]	)		->     Optional[int]:




							"""simple docstring"""


							lowercase__    ,			lowercase__      =	self.model_tester.prepare_config_and_inputs_for_common()

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

									lowercase__      =	["""pixel_values"""]
									self.assertListEqual(arg_names[:1]   ,      _UpperCAmelCase	)

					def 						lowerCamelCase__  (self					:		Dict	)		->     Union[str, Any]:




							"""simple docstring"""


							def check_hidden_states_output(_UpperCAmelCase					:		List[Any]   ,      _UpperCAmelCase					:		Tuple   ,      _UpperCAmelCase					:		List[str]	):
									lowercase__      =	model_class(_UpperCAmelCase	)

									lowercase__      =	model(**self._prepare_for_class(_UpperCAmelCase   ,      _UpperCAmelCase	)	)

									lowercase__      =	outputs.encoder_hidden_states if config.is_encoder_decoder else outputs.hidden_states

									lowercase__      =	self.model_tester.num_stages
									self.assertEqual(len(_UpperCAmelCase	)   ,      expected_num_stages + 1	)

					@unittest.skip(reason="""ResNet does not use feedforward chunking"""	)
					def 						lowerCamelCase__  (self					:		int	)		->     int:




							"""simple docstring"""


							pass


					def 						lowerCamelCase__  (self					:		int	)		->     List[str]:




							"""simple docstring"""


							lowercase__    ,			lowercase__      =	self.model_tester.prepare_config_and_inputs_for_common()

							for model_class in self.all_model_classes:
									with self.subTest(model_class.__name__	):
											lowercase__      =	self._prepare_for_class(_UpperCAmelCase   ,      _UpperCAmelCase	)
											lowercase__      =	model_class(_UpperCAmelCase	)

											@jax.jit
											def model_jitted(_UpperCAmelCase					:		Tuple   ,      **_UpperCAmelCase					:		List[str]	):
													return model(pixel_values=_UpperCAmelCase   ,      **_UpperCAmelCase	)

											with self.subTest("""JIT Enabled"""	):
													lowercase__      =	model_jitted(**_UpperCAmelCase	).to_tuple()

											with self.subTest("""JIT Disabled"""	):
													with jax.disable_jit():
															lowercase__      =	model_jitted(**_UpperCAmelCase	).to_tuple()

											self.assertEqual(len(_UpperCAmelCase	)   ,      len(_UpperCAmelCase	)	)
											for jitted_output, output in zip(_UpperCAmelCase   ,      _UpperCAmelCase	):
													self.assertEqual(jitted_output.shape   ,      output.shape	)






def 				UpperCamelCase      (			)     ->						int:
		"""simple docstring"""




		lowercase__      =	Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""  )
		return image







@require_flax
class 							A					( unittest.TestCase							):
					'''simple docstring'''






					@cached_property
					def 						lowerCamelCase__  (self					:		Dict	)		->     Union[str, Any]:




							"""simple docstring"""


							return AutoImageProcessor.from_pretrained("""microsoft/resnet-50"""	) if is_vision_available() else None


					@slow
					def 						lowerCamelCase__  (self					:		str	)		->     Optional[int]:




							"""simple docstring"""


							lowercase__      =	FlaxResNetForImageClassification.from_pretrained("""microsoft/resnet-50"""	)

							lowercase__      =	self.default_image_processor
							lowercase__      =	prepare_img()
							lowercase__      =	image_processor(images=_UpperCAmelCase   ,      return_tensors="""np"""	)

							lowercase__      =	model(**_UpperCAmelCase	)

							# verify the logits
							lowercase__      =	(1, 1000)
							self.assertEqual(outputs.logits.shape   ,      _UpperCAmelCase	)

							lowercase__      =	jnp.array([-11.1_069, -9.7_877, -8.3_777]	)

							self.assertTrue(jnp.allclose(outputs.logits[0, :3]   ,      _UpperCAmelCase   ,      atol=1E-4	)	)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


A :	int												=     {
    'configuration_rwkv': ['RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RwkvConfig', 'RwkvOnnxConfig'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A :	List[Any]												=     [
	    'RWKV_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'RwkvForCausalLM',
	    'RwkvModel',
	    'RwkvPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_rwkv import (
		    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
		    RwkvForCausalLM,
		    RwkvModel,
		    RwkvPreTrainedModel,
		)
else:
	import sys

	A :	Optional[int]												=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

