'''simple docstring'''




import inspect
import unittest

from transformers import RegNetConfig, 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.regnet.modeling_flax_regnet import FlaxRegNetForImageClassification, FlaxRegNetModel

if is_vision_available():
						from PIL import Image

						from transformers import AutoImageProcessor





class 					__magic_name__		(					unittest.TestCase):







			def __init__(			self       :						Dict       ,    lowercase_       :						List[Any]       ,    lowercase_       :						List[str]=3       ,    lowercase_       :						Any=32       ,    lowercase_       :						Dict=3       ,    lowercase_       :						Optional[int]=10       ,    lowercase_       :						Dict=[10, 20, 30, 40]       ,    lowercase_       :						List[str]=[1, 1, 2, 1]       ,    lowercase_       :						int=True       ,    lowercase_       :						str=True       ,    lowercase_       :						List[str]="relu"       ,    lowercase_       :						Optional[int]=3       ,    lowercase_       :						List[Any]=None       ,    ):
										lowercase_      :    List[Any]       		= parent
										lowercase_      :    List[Any]       		= batch_size
										lowercase_      :    List[Any]       		= image_size
										lowercase_      :    Any       		= num_channels
										lowercase_      :    List[Any]       		= embeddings_size
										lowercase_      :    Union[str, Any]       		= hidden_sizes
										lowercase_      :    str       		= depths
										lowercase_      :    Union[str, Any]       		= is_training
										lowercase_      :    List[Any]       		= use_labels
										lowercase_      :    str       		= hidden_act
										lowercase_      :    Tuple       		= num_labels
										lowercase_      :    Optional[int]       		= scope
										lowercase_      :    Tuple       		= len(__A					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[int]					):
										lowercase_      :    Union[str, Any]       		= floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]					)

										lowercase_      :    Any       		= self.get_config()

										return config, pixel_values







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[int]					):
										return RegNetConfig(
										    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 			SCREAMING_SNAKE_CASE_  (			self       :						str       ,    lowercase_       :						int       ,    lowercase_       :						str					):
										lowercase_      :    Optional[int]       		= FlaxRegNetModel(config=__A					)
										lowercase_      :    str       		= model(__A					)

										# 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 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]       ,    lowercase_       :						Dict       ,    lowercase_       :						Any					):
										lowercase_      :    Optional[Any]       		= self.num_labels
										lowercase_      :    List[str]       		= FlaxRegNetForImageClassification(config=__A					)
										lowercase_      :    Dict       		= model(__A					)
										self.parent.assertEqual(result.logits.shape       ,    (self.batch_size, self.num_labels)					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						List[str]					):
										lowercase_      :    Any       		= self.prepare_config_and_inputs()
										lowercase_		,		lowercase_      :    Union[str, Any]       		= config_and_inputs
										lowercase_      :    Optional[Any]       		= {"""pixel_values""": pixel_values}
										return config, inputs_dict





@require_flax
class 					__magic_name__		(					UpperCamelCase__,  unittest.TestCase):
			UpperCamelCase__       = (FlaxRegNetModel, FlaxRegNetForImageClassification) if is_flax_available() else ()

			UpperCamelCase__       = False
			UpperCamelCase__       = False
			UpperCamelCase__       = False







			def 			SCREAMING_SNAKE_CASE_  (			self       :						int					):
										lowercase_      :    Union[str, Any]       		= FlaxRegNetModelTester(self					)
										lowercase_      :    List[str]       		= ConfigTester(self       ,    config_class=__A       ,    has_text_modality=__A					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						List[str]					):
										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 			SCREAMING_SNAKE_CASE_  (			self       :						List[str]					):
										return







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[int]					):
										lowercase_      :    int       		= self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_model(*__A					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]					):
										lowercase_      :    Optional[int]       		= self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_for_image_classification(*__A					)







			@unittest.skip(reason="""RegNet does not use inputs_embeds"""					)
			def 			SCREAMING_SNAKE_CASE_  (			self       :						int					):
										pass







			@unittest.skip(reason="""RegNet does not support input and output embeddings"""					)
			def 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple					):
										pass







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]					):
										lowercase_		,		lowercase_      :    Union[str, Any]       		= self.model_tester.prepare_config_and_inputs_for_common()

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

																	lowercase_      :    List[str]       		= ["""pixel_values"""]
																	self.assertListEqual(arg_names[:1]       ,    __A					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Union[str, Any]					):



										def check_hidden_states_output(lowercase_       :						Optional[int]       ,    lowercase_       :						str       ,    lowercase_       :						Optional[Any]					):
																	lowercase_      :    Optional[int]       		= model_class(__A					)

																	lowercase_      :    Optional[int]       		= model(**self._prepare_for_class(__A       ,    __A					)					)

																	lowercase_      :    List[str]       		= outputs.encoder_hidden_states if config.is_encoder_decoder else outputs.hidden_states

																	lowercase_      :    List[str]       		= self.model_tester.num_stages
																	self.assertEqual(len(__A					)       ,    expected_num_stages + 1					)

										lowercase_		,		lowercase_      :    Dict       		= self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
																	lowercase_      :    Dict       		= True
																	check_hidden_states_output(__A       ,    __A       ,    __A					)

																	# check that output_hidden_states also work using config
																	del inputs_dict["output_hidden_states"]
																	lowercase_      :    Dict       		= True

																	check_hidden_states_output(__A       ,    __A       ,    __A					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Any					):
										lowercase_		,		lowercase_      :    int       		= self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
																	with self.subTest(model_class.__name__					):
																								lowercase_      :    Any       		= self._prepare_for_class(__A       ,    __A					)
																								lowercase_      :    Union[str, Any]       		= model_class(__A					)

																								@jax.jit
																								def model_jitted(lowercase_       :						Dict       ,    **lowercase_       :						Any					):
																															return model(pixel_values=__A       ,    **__A					)

																								with self.subTest("""JIT Enabled"""					):
																															lowercase_      :    Optional[Any]       		= model_jitted(**__A					).to_tuple()

																								with self.subTest("""JIT Disabled"""					):
																															with jax.disable_jit():
																																						lowercase_      :    Union[str, Any]       		= model_jitted(**__A					).to_tuple()

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




def 							lowerCamelCase			(   ):
							lowercase_      :    List[Any]       		= Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""				)
							return image





@require_flax
class 					__magic_name__		(					unittest.TestCase):







			@cached_property
			def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]					):
										return AutoImageProcessor.from_pretrained("""facebook/regnet-y-040"""					) if is_vision_available() else None







			@slow
			def 			SCREAMING_SNAKE_CASE_  (			self       :						Any					):
										lowercase_      :    List[str]       		= FlaxRegNetForImageClassification.from_pretrained("""facebook/regnet-y-040"""					)

										lowercase_      :    Union[str, Any]       		= self.default_image_processor
										lowercase_      :    str       		= prepare_img()
										lowercase_      :    int       		= image_processor(images=__A       ,    return_tensors="""np"""					)

										lowercase_      :    List[str]       		= model(**__A					)

										# verify the logits
										lowercase_      :    Optional[Any]       		= (1, 1000)
										self.assertEqual(outputs.logits.shape       ,    __A					)

										lowercase_      :    List[str]       		= jnp.array([-0.41_80, -1.50_51, -3.48_36]					)

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






'''simple docstring'''




_lowercase		:				int	       =		"ABCDEFGHIJKLMNOPQRSTUVWXYZ"




def 							lowerCamelCase			(   )    ->   None:
							lowercase_      :    List[Any]       		= input("""Enter message: """				)
							lowercase_      :    str       		= input("""Enter key [alphanumeric]: """				)
							lowercase_      :    List[Any]       		= input("""Encrypt/Decrypt [e/d]: """				)

							if mode.lower().startswith("""e"""				):
														lowercase_      :    List[str]       		= """encrypt"""
														lowercase_      :    Optional[int]       		= encrypt_message(UpperCAmelCase__   ,   UpperCAmelCase__				)
							elif mode.lower().startswith("""d"""				):
														lowercase_      :    Any       		= """decrypt"""
														lowercase_      :    Optional[Any]       		= decrypt_message(UpperCAmelCase__   ,   UpperCAmelCase__				)

							print(F'''\n{mode.title()}ed message:'''				)
							print(UpperCAmelCase__				)




def 							lowerCamelCase			(   UpperCAmelCase__ :      str   ,   UpperCAmelCase__ :      str				)    ->   str:
							return translate_message(UpperCAmelCase__   ,   UpperCAmelCase__   ,   """encrypt"""				)




def 							lowerCamelCase			(   UpperCAmelCase__ :      str   ,   UpperCAmelCase__ :      str				)    ->   str:
							return translate_message(UpperCAmelCase__   ,   UpperCAmelCase__   ,   """decrypt"""				)




def 							lowerCamelCase			(   UpperCAmelCase__ :      str   ,   UpperCAmelCase__ :      str   ,   UpperCAmelCase__ :      str				)    ->   str:
							lowercase_      :    Union[str, Any]       		= []
							lowercase_      :    List[Any]       		= 0
							lowercase_      :    str       		= key.upper()

							for symbol in message:
														lowercase_      :    Tuple       		= LETTERS.find(symbol.upper()				)
														if num != -1:
																					if mode == "encrypt":
																												num += LETTERS.find(key[key_index]				)
																					elif mode == "decrypt":
																												num -= LETTERS.find(key[key_index]				)

																					num %= len(UpperCAmelCase__				)

																					if symbol.isupper():
																												translated.append(LETTERS[num]				)
																					elif symbol.islower():
																												translated.append(LETTERS[num].lower()				)

																					key_index += 1
																					if key_index == len(UpperCAmelCase__				):
																												lowercase_      :    Any       		= 0
														else:
																					translated.append(UpperCAmelCase__				)
							return "".join(UpperCAmelCase__				)


if __name__ == "__main__":
						main()





