import copy
import inspect
import unittest

from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
    require_torch,
    require_vision,
    slow,
    torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available

from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
    import torch
    from torch import nn

    from transformers import SwiftFormerForImageClassification, SwiftFormerModel
    from transformers.models.swiftformer.modeling_swiftformer import SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST


if is_vision_available():
    from PIL import Image

    from transformers import ViTImageProcessor
class     a_			:






 '''simple docstring'''






 def __init__(      self :  Optional[Any]      ,   lowercase__ :  Tuple      ,   lowercase__ :  Optional[Any]=13      ,   lowercase__ :  List[Any]=3      ,   lowercase__ :  Optional[Any]=True      ,   lowercase__ :  str=True      ,   lowercase__ :  Optional[int]=0.1      ,   lowercase__ :  Optional[int]=0.1      ,   lowercase__ :  Optional[Any]=224      ,   lowercase__ :  Tuple=1_000      ,   lowercase__ :  Optional[int]=[3, 3, 6, 4]      ,   lowercase__ :  List[Any]=[48, 56, 112, 220]      ,   ):







        '''simple docstring'''



        lowerCAmelCase__					     = parent
        lowerCAmelCase__					     = batch_size
        lowerCAmelCase__					     = num_channels
        lowerCAmelCase__					     = is_training
        lowerCAmelCase__					     = use_labels
        lowerCAmelCase__					     = hidden_dropout_prob
        lowerCAmelCase__					     = attention_probs_dropout_prob
        lowerCAmelCase__					     = num_labels
        lowerCAmelCase__					     = image_size
        lowerCAmelCase__					     = layer_depths
        lowerCAmelCase__					     = embed_dims




 def 		__snake_case						(      self :  Optional[Any]):







        '''simple docstring'''



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

        lowerCAmelCase__					     = None
        if self.use_labels:
               lowerCAmelCase__					     = ids_tensor([self.batch_size]      ,   self.num_labels)

        lowerCAmelCase__					     = self.get_config()

        return config, pixel_values, labels




 def 		__snake_case						(      self :  List[Any]):







        '''simple docstring'''



        return SwiftFormerConfig(
            depths=self.layer_depths      ,   embed_dims=self.embed_dims      ,   mlp_ratio=4      ,   downsamples=[True, True, True, True]      ,   hidden_act='gelu'      ,   num_labels=self.num_labels      ,   down_patch_size=3      ,   down_stride=2      ,   down_pad=1      ,   drop_rate=0.0      ,   drop_path_rate=0.0      ,   use_layer_scale=lowercase__      ,   layer_scale_init_value=1e-5      ,   )




 def 		__snake_case						(      self :  str      ,   lowercase__ :  Tuple      ,   lowercase__ :  str      ,   lowercase__ :  List[str]):







        '''simple docstring'''



        lowerCAmelCase__					     = SwiftFormerModel(config=lowercase__)
        model.to(lowercase__)
        model.eval()
        lowerCAmelCase__					     = model(lowercase__)
        self.parent.assertEqual(result.last_hidden_state.shape      ,   (self.batch_size, self.embed_dims[-1], 7, 7))




 def 		__snake_case						(      self :  Dict      ,   lowercase__ :  Optional[int]      ,   lowercase__ :  Dict      ,   lowercase__ :  Tuple):







        '''simple docstring'''



        lowerCAmelCase__					     = self.num_labels
        lowerCAmelCase__					     = SwiftFormerForImageClassification(lowercase__)
        model.to(lowercase__)
        model.eval()
        lowerCAmelCase__					     = model(lowercase__      ,   labels=lowercase__)
        self.parent.assertEqual(result.logits.shape      ,   (self.batch_size, self.num_labels))

        lowerCAmelCase__					     = SwiftFormerForImageClassification(lowercase__)
        model.to(lowercase__)
        model.eval()

        lowerCAmelCase__					     = floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size])
        lowerCAmelCase__					     = model(lowercase__)
        self.parent.assertEqual(result.logits.shape      ,   (self.batch_size, self.num_labels))




 def 		__snake_case						(      self :  List[str]):







        '''simple docstring'''



        ((lowerCAmelCase__)     , (lowerCAmelCase__)     , (lowerCAmelCase__))					     = self.prepare_config_and_inputs()
        lowerCAmelCase__					     = {'pixel_values': pixel_values}
        return config, inputs_dict






@require_torch
class     a_			(						SCREAMING_SNAKE_CASE	,					SCREAMING_SNAKE_CASE	,					unittest.TestCase						):






 '''simple docstring'''






 UpperCAmelCase_     			= (SwiftFormerModel, SwiftFormerForImageClassification) if is_torch_available() else ()
 UpperCAmelCase_     			= (
     {'feature-extraction': SwiftFormerModel, 'image-classification': SwiftFormerForImageClassification}
     if is_torch_available()
     else {}
 )

 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False




 def 		__snake_case						(      self :  Any):







        '''simple docstring'''



        lowerCAmelCase__					     = SwiftFormerModelTester(self)
        lowerCAmelCase__					     = ConfigTester(
            self      ,   config_class=lowercase__      ,   has_text_modality=lowercase__      ,   hidden_size=37      ,   num_attention_heads=12      ,   num_hidden_layers=12      ,   )




 def 		__snake_case						(      self :  Dict):







        '''simple docstring'''



        self.config_tester.run_common_tests()




 @unittest.skip(reason='SwiftFormer does not use inputs_embeds')
 def 		__snake_case						(      self :  Union[str, Any]):







        '''simple docstring'''



        pass




 def 		__snake_case						(      self :  Tuple):







        '''simple docstring'''



        lowerCAmelCase__     , lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs_for_common()

        for model_class in self.all_model_classes:
               lowerCAmelCase__					     = model_class(lowercase__)
               lowerCAmelCase__					     = model.get_output_embeddings()
               self.assertTrue(x is None or isinstance(lowercase__      ,   nn.Linear))




 def 		__snake_case						(      self :  Any):







        '''simple docstring'''



        lowerCAmelCase__     , lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs_for_common()

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

               lowerCAmelCase__					     = ['pixel_values']
               self.assertListEqual(arg_names[:1]      ,   lowercase__)




 def 		__snake_case						(      self :  List[str]):







        '''simple docstring'''



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




 def 		__snake_case						(      self :  int):







        '''simple docstring'''



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




 @slow
 def 		__snake_case						(      self :  Tuple):







        '''simple docstring'''



        for model_name in SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
               lowerCAmelCase__					     = SwiftFormerModel.from_pretrained(lowercase__)
               self.assertIsNotNone(lowercase__)




 @unittest.skip(reason='SwiftFormer does not output attentions')
 def 		__snake_case						(      self :  Union[str, Any]):







        '''simple docstring'''



        pass




 def 		__snake_case						(      self :  Dict):







        '''simple docstring'''



        def check_hidden_states_output(lowercase__ :  Dict      ,   lowercase__ :  List[str]      ,   lowercase__ :  str):
               lowerCAmelCase__					     = model_class(lowercase__)
               model.to(lowercase__)
               model.eval()

               with torch.no_grad():
                      lowerCAmelCase__					     = model(**self._prepare_for_class(lowercase__      ,   lowercase__))

               lowerCAmelCase__					     = outputs.hidden_states

               lowerCAmelCase__					     = 8
               self.assertEqual(len(lowercase__)      ,   lowercase__)  # TODO

               # SwiftFormer's feature maps are of shape (batch_size, embed_dims, height, width)
               # with the width and height being successively divided by 2, after every 2 blocks
               for i in range(len(lowercase__)):
                      self.assertEqual(
                          hidden_states[i].shape      ,   torch.Size(
                              [
                                  self.model_tester.batch_size,
                                  self.model_tester.embed_dims[i // 2],
                                  (self.model_tester.image_size // 4) // 2 ** (i // 2),
                                  (self.model_tester.image_size // 4) // 2 ** (i // 2),
                              ])      ,   )

        lowerCAmelCase__     , lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs_for_common()

        for model_class in self.all_model_classes:
               lowerCAmelCase__					     = True
               check_hidden_states_output(lowercase__      ,   lowercase__      ,   lowercase__)

               # check that output_hidden_states also work using config
               del inputs_dict["output_hidden_states"]
               lowerCAmelCase__					     = True

               check_hidden_states_output(lowercase__      ,   lowercase__      ,   lowercase__)




 def 		__snake_case						(      self :  Dict):







        '''simple docstring'''



        def _config_zero_init(lowercase__ :  Dict):
               lowerCAmelCase__					     = copy.deepcopy(lowercase__)
               for key in configs_no_init.__dict__.keys():
                      if "_range" in key or "_std" in key or "initializer_factor" in key or "layer_scale" in key:
                             setattr(lowercase__      ,   lowercase__      ,   1e-10)
                      if isinstance(getattr(lowercase__      ,   lowercase__      ,   lowercase__)      ,   lowercase__):
                             lowerCAmelCase__					     = _config_zero_init(getattr(lowercase__      ,   lowercase__))
                             setattr(lowercase__      ,   lowercase__      ,   lowercase__)
               return configs_no_init

        lowerCAmelCase__     , lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs_for_common()

        lowerCAmelCase__					     = _config_zero_init(lowercase__)
        for model_class in self.all_model_classes:
               lowerCAmelCase__					     = model_class(config=lowercase__)
               for name, param in model.named_parameters():
                      if param.requires_grad:
                             self.assertIn(
                                 ((param.data.mean() * 1e9) / 1e9).round().item()      ,   [0.0, 1.0]      ,   msg=F"""Parameter {name} of model {model_class} seems not properly initialized"""      ,   )




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







        '''simple docstring'''



        pass






def 				__lowerCamelCase		(						):
       lowerCAmelCase__					     = Image.open('./tests/fixtures/tests_samples/COCO/000000039769.png'     )
       return image



@require_torch
@require_vision
class     a_			(						unittest.TestCase						):






 '''simple docstring'''






 @cached_property
 def 		__snake_case						(      self :  Any):







        '''simple docstring'''



        return ViTImageProcessor.from_pretrained('MBZUAI/swiftformer-xs') if is_vision_available() else None




 @slow
 def 		__snake_case						(      self :  Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = SwiftFormerForImageClassification.from_pretrained('MBZUAI/swiftformer-xs').to(lowercase__)

        lowerCAmelCase__					     = self.default_image_processor
        lowerCAmelCase__					     = prepare_img()
        lowerCAmelCase__					     = image_processor(images=lowercase__      ,   return_tensors='pt').to(lowercase__)

        # forward pass
        with torch.no_grad():
               lowerCAmelCase__					     = model(**lowercase__)

        # verify the logits
        lowerCAmelCase__					     = torch.Size((1, 1_000))
        self.assertEqual(outputs.logits.shape      ,   lowercase__)

        lowerCAmelCase__					     = torch.tensor([[-2.1703e00, 2.1107e00, -2.0811e00]]).to(lowercase__)
        self.assertTrue(torch.allclose(outputs.logits[0, :3]      ,   lowercase__      ,   atol=1e-4))

from __future__ import annotations

lowerCAmelCase__     						=			tuple[int, int, int]
lowerCAmelCase__     						=			tuple[str, str, str]


# used alphabet --------------------------
# from string.ascii_uppercase
lowerCAmelCase__     						=			'ABCDEFGHIJKLMNOPQRSTUVWXYZ'

# -------------------------- default selection --------------------------
# rotors --------------------------
lowerCAmelCase__     						=			'EGZWVONAHDCLFQMSIPJBYUKXTR'
lowerCAmelCase__     						=			'FOBHMDKEXQNRAULPGSJVTYICZW'
lowerCAmelCase__     						=			'ZJXESIUQLHAVRMDOYGTNFWPBKC'
# reflector --------------------------
lowerCAmelCase__     						=			{
    'A': 'N',
    'N': 'A',
    'B': 'O',
    'O': 'B',
    'C': 'P',
    'P': 'C',
    'D': 'Q',
    'Q': 'D',
    'E': 'R',
    'R': 'E',
    'F': 'S',
    'S': 'F',
    'G': 'T',
    'T': 'G',
    'H': 'U',
    'U': 'H',
    'I': 'V',
    'V': 'I',
    'J': 'W',
    'W': 'J',
    'K': 'X',
    'X': 'K',
    'L': 'Y',
    'Y': 'L',
    'M': 'Z',
    'Z': 'M',
}

# -------------------------- extra rotors --------------------------
lowerCAmelCase__     						=			'RMDJXFUWGISLHVTCQNKYPBEZOA'
lowerCAmelCase__     						=			'SGLCPQWZHKXAREONTFBVIYJUDM'
lowerCAmelCase__     						=			'HVSICLTYKQUBXDWAJZOMFGPREN'
lowerCAmelCase__     						=			'RZWQHFMVDBKICJLNTUXAGYPSOE'
lowerCAmelCase__     						=			'LFKIJODBEGAMQPXVUHYSTCZRWN'
lowerCAmelCase__     						=			'KOAEGVDHXPQZMLFTYWJNBRCIUS'






def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ,  lowerCAmelCase__     ):
       # Checks if there are 3 unique rotors

       if (unique_rotsel := len(set(lowerCAmelCase__     )     )) < 3:
              lowerCAmelCase__					     = F"""Please use 3 unique rotors (not {unique_rotsel})"""
              raise Exception(lowerCAmelCase__     )

       # Checks if rotor positions are valid
       lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = rotpos
       if not 0 < rotorposa <= len(lowerCAmelCase__     ):
              lowerCAmelCase__					     = F"""First rotor position is not within range of 1..26 ({rotorposa}"""
              raise ValueError(lowerCAmelCase__     )
       if not 0 < rotorposa <= len(lowerCAmelCase__     ):
              lowerCAmelCase__					     = F"""Second rotor position is not within range of 1..26 ({rotorposa})"""
              raise ValueError(lowerCAmelCase__     )
       if not 0 < rotorposa <= len(lowerCAmelCase__     ):
              lowerCAmelCase__					     = F"""Third rotor position is not within range of 1..26 ({rotorposa})"""
              raise ValueError(lowerCAmelCase__     )

       # Validates string and returns dict
       lowerCAmelCase__					     = _plugboard(lowerCAmelCase__     )

       return rotpos, rotsel, pbdict






def 				__lowerCamelCase		(						lowerCAmelCase__     ):

       # tests the input string if it
       # a) is type string
       # b) has even length (so pairs can be made)
       if not isinstance(lowerCAmelCase__     ,  lowerCAmelCase__     ):
              lowerCAmelCase__					     = F"""Plugboard setting isn't type string ({type(lowerCAmelCase__     )})"""
              raise TypeError(lowerCAmelCase__     )
       elif len(lowerCAmelCase__     ) % 2 != 0:
              lowerCAmelCase__					     = F"""Odd number of symbols ({len(lowerCAmelCase__     )})"""
              raise Exception(lowerCAmelCase__     )
       elif pbstring == "":
              return {}

       pbstring.replace(' '     ,  ''     )

       # Checks if all characters are unique
       lowerCAmelCase__					     = set()
       for i in pbstring:
              if i not in abc:
                     lowerCAmelCase__					     = F"""'{i}' not in list of symbols"""
                     raise Exception(lowerCAmelCase__     )
              elif i in tmppbl:
                     lowerCAmelCase__					     = F"""Duplicate symbol ({i})"""
                     raise Exception(lowerCAmelCase__     )
              else:
                     tmppbl.add(lowerCAmelCase__     )
       del tmppbl

       # Created the dictionary
       lowerCAmelCase__					     = {}
       for j in range(0     ,  len(lowerCAmelCase__     ) - 1     ,  2     ):
              lowerCAmelCase__					     = pbstring[j + 1]
              lowerCAmelCase__					     = pbstring[j]

       return pb






def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ,  lowerCAmelCase__ = (rotora, rotora, rotora)     ,  lowerCAmelCase__ = ""     ,  ):
       lowerCAmelCase__					     = text.upper()
       lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = _validator(
           lowerCAmelCase__     ,  lowerCAmelCase__     ,  plugb.upper()     )

       lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = rotor_position
       lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = rotor_selection
       rotorposa -= 1
       rotorposa -= 1
       rotorposa -= 1

       lowerCAmelCase__					     = []

       # encryption/decryption process --------------------------
       for symbol in text:
              if symbol in abc:
                     # 1st plugboard --------------------------
                     if symbol in plugboard:
                            lowerCAmelCase__					     = plugboard[symbol]

                     # rotor ra --------------------------
                     lowerCAmelCase__					     = abc.index(lowerCAmelCase__     ) + rotorposa
                     lowerCAmelCase__					     = rotora[index % len(lowerCAmelCase__     )]

                     # rotor rb --------------------------
                     lowerCAmelCase__					     = abc.index(lowerCAmelCase__     ) + rotorposa
                     lowerCAmelCase__					     = rotora[index % len(lowerCAmelCase__     )]

                     # rotor rc --------------------------
                     lowerCAmelCase__					     = abc.index(lowerCAmelCase__     ) + rotorposa
                     lowerCAmelCase__					     = rotora[index % len(lowerCAmelCase__     )]

                     # reflector --------------------------
                     # this is the reason you don't need another machine to decipher

                     lowerCAmelCase__					     = reflector[symbol]

                     # 2nd rotors
                     lowerCAmelCase__					     = abc[rotora.index(lowerCAmelCase__     ) - rotorposa]
                     lowerCAmelCase__					     = abc[rotora.index(lowerCAmelCase__     ) - rotorposa]
                     lowerCAmelCase__					     = abc[rotora.index(lowerCAmelCase__     ) - rotorposa]

                     # 2nd plugboard
                     if symbol in plugboard:
                            lowerCAmelCase__					     = plugboard[symbol]

                     # moves/resets rotor positions
                     rotorposa += 1
                     if rotorposa >= len(lowerCAmelCase__     ):
                            lowerCAmelCase__					     = 0
                            rotorposa += 1
                     if rotorposa >= len(lowerCAmelCase__     ):
                            lowerCAmelCase__					     = 0
                            rotorposa += 1
                     if rotorposa >= len(lowerCAmelCase__     ):
                            lowerCAmelCase__					     = 0

        # else:
        #    pass
        #    Error could be also raised
        #    raise ValueError(
        #       'Invalid symbol('+repr(symbol)+')')
              result.append(lowerCAmelCase__     )

       return "".join(lowerCAmelCase__     )


if __name__ == "__main__":
    lowerCAmelCase__     						=			'This is my Python script that emulates the Enigma machine from WWII.'
    lowerCAmelCase__     						=			(1, 1, 1)
    lowerCAmelCase__     						=			'pictures'
    lowerCAmelCase__     						=			(rotora, rotora, rotora)
    lowerCAmelCase__     						=			enigma(message, rotor_pos, rotor_sel, pb)

    print('Encrypted message:', en)
    print('Decrypted message:', enigma(en, rotor_pos, rotor_sel, pb))
