"""simple docstring"""


import collections
import inspect
import unittest
from typing import Dict, List, Tuple

from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.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, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
 import torch
 from torch import nn

 from transformers import MaskFormerSwinBackbone
 from transformers.models.maskformer import MaskFormerSwinModel






class    a__    :


   def __init__(     self,				_UpperCAmelCase,				_UpperCAmelCase=13,				_UpperCAmelCase=32,				_UpperCAmelCase=2,				_UpperCAmelCase=3,				_UpperCAmelCase=16,				_UpperCAmelCase=[1, 2, 1],				_UpperCAmelCase=[2, 2, 4],				_UpperCAmelCase=2,				_UpperCAmelCase=2.0,				_UpperCAmelCase=True,				_UpperCAmelCase=0.0,				_UpperCAmelCase=0.0,				_UpperCAmelCase=0.1,				_UpperCAmelCase="gelu",				_UpperCAmelCase=False,				_UpperCAmelCase=True,				_UpperCAmelCase=0.02,				_UpperCAmelCase=1E-5,				_UpperCAmelCase=True,				_UpperCAmelCase=None,				_UpperCAmelCase=True,				_UpperCAmelCase=10,				_UpperCAmelCase=8,				_UpperCAmelCase=["stage1", "stage2", "stage3"],				_UpperCAmelCase=[1, 2, 3],				):
        '''simple docstring'''



        lowercase__				 =							parent
        lowercase__				 =							batch_size
        lowercase__				 =							image_size
        lowercase__				 =							patch_size
        lowercase__				 =							num_channels
        lowercase__				 =							embed_dim
        lowercase__				 =							depths
        lowercase__				 =							num_heads
        lowercase__				 =							window_size
        lowercase__				 =							mlp_ratio
        lowercase__				 =							qkv_bias
        lowercase__				 =							hidden_dropout_prob
        lowercase__				 =							attention_probs_dropout_prob
        lowercase__				 =							drop_path_rate
        lowercase__				 =							hidden_act
        lowercase__				 =							use_absolute_embeddings
        lowercase__				 =							patch_norm
        lowercase__				 =							layer_norm_eps
        lowercase__				 =							initializer_range
        lowercase__				 =							is_training
        lowercase__				 =							scope
        lowercase__				 =							use_labels
        lowercase__				 =							type_sequence_label_size
        lowercase__				 =							encoder_stride
        lowercase__				 =							out_features
        lowercase__				 =							out_indices


   def 	snake_case__	(     self  ):
        '''simple docstring'''



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

        lowercase__				 =							None
        if self.use_labels:
             lowercase__				 =							ids_tensor([self.batch_size],				self.type_sequence_label_size  )

        lowercase__				 =							self.get_config()

        return config, pixel_values, labels


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        return MaskFormerSwinConfig(
            image_size=self.image_size,				patch_size=self.patch_size,				num_channels=self.num_channels,				embed_dim=self.embed_dim,				depths=self.depths,				num_heads=self.num_heads,				window_size=self.window_size,				mlp_ratio=self.mlp_ratio,				qkv_bias=self.qkv_bias,				hidden_dropout_prob=self.hidden_dropout_prob,				attention_probs_dropout_prob=self.attention_probs_dropout_prob,				drop_path_rate=self.drop_path_rate,				hidden_act=self.hidden_act,				use_absolute_embeddings=self.use_absolute_embeddings,				path_norm=self.patch_norm,				layer_norm_eps=self.layer_norm_eps,				initializer_range=self.initializer_range,				encoder_stride=self.encoder_stride,				out_features=self.out_features,				out_indices=self.out_indices,				)


   def 	snake_case__	(     self,				_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase  ):
        '''simple docstring'''



        lowercase__				 =							MaskFormerSwinModel(config=_UpperCAmelCase  )
        model.to(_UpperCAmelCase  )
        model.eval()
        lowercase__				 =							model(_UpperCAmelCase  )

        lowercase__				 =							((config.image_size // config.patch_size) ** 2) // (4 ** (len(config.depths  ) - 1))
        lowercase__				 =							int(config.embed_dim * 2 ** (len(config.depths  ) - 1)  )

        self.parent.assertEqual(result.last_hidden_state.shape,				(self.batch_size, expected_seq_len, expected_dim)  )


   def 	snake_case__	(     self,				_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase  ):
        '''simple docstring'''



        lowercase__				 =							MaskFormerSwinBackbone(config=_UpperCAmelCase  )
        model.to(_UpperCAmelCase  )
        model.eval()
        lowercase__				 =							model(_UpperCAmelCase  )

        # verify feature maps
        self.parent.assertEqual(len(result.feature_maps  ),				len(config.out_features  )  )
        self.parent.assertListEqual(list(result.feature_maps[0].shape  ),				[13, 16, 16, 16]  )

        # verify channels
        self.parent.assertEqual(len(model.channels  ),				len(config.out_features  )  )
        self.parent.assertListEqual(model.channels,				[16, 32, 64]  )

        # verify ValueError
        with self.parent.assertRaises(_UpperCAmelCase  ):
             lowercase__				 =							["stem"]
             lowercase__				 =							MaskFormerSwinBackbone(config=_UpperCAmelCase  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



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






@require_torch
class    a__    (   _a					,					_a					,					unittest.TestCase	):
   snake_case_							=      (
       (
           MaskFormerSwinModel,
           MaskFormerSwinBackbone,
       )
       if is_torch_available()
       else ()
   )
   snake_case_							=      {"feature-extraction": MaskFormerSwinModel} if is_torch_available() else {}
   snake_case_							=      False
   snake_case_							=      False
   snake_case_							=      False
   snake_case_							=      False
   snake_case_							=      False


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							MaskFormerSwinModelTester(self  )
        lowercase__				 =							ConfigTester(self,				config_class=_UpperCAmelCase,				embed_dim=37  )


   @require_torch_multi_gpu
   @unittest.skip(
       reason=(
           "`MaskFormerSwinModel` outputs `hidden_states_spatial_dimensions` which doesn't work well with"
           " `nn.DataParallel`"
       )  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self  ):
        '''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 	snake_case__	(     self  ):
        '''simple docstring'''



        return


   def 	snake_case__	(     self  ):
        '''simple docstring'''



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


   def 	snake_case__	(     self  ):
        '''simple docstring'''



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


   @unittest.skip("Swin does not use inputs_embeds"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   @unittest.skip("Swin does not support feedforward chunking"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self  ):
        '''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  )
             self.assertIsInstance(model.get_input_embeddings(),				(nn.Module)  )
             lowercase__				 =							model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(_UpperCAmelCase,				nn.Linear  )  )


   def 	snake_case__	(     self  ):
        '''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.forward  )
             # signature.parameters is an OrderedDict => so arg_names order is deterministic
             lowercase__				 =							[*signature.parameters.keys()]

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


   @unittest.skip(reason="MaskFormerSwin is only used as backbone and doesn't support output_attentions"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   @unittest.skip(reason="MaskFormerSwin is only used as an internal backbone"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self,				_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase  ):
        '''simple docstring'''



        lowercase__				 =							model_class(_UpperCAmelCase  )
        model.to(_UpperCAmelCase  )
        model.eval()

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

        lowercase__				 =							outputs.hidden_states

        lowercase__				 =							getattr(
            self.model_tester,				"expected_num_hidden_layers",				len(self.model_tester.depths  ) + 1  )
        self.assertEqual(len(_UpperCAmelCase  ),				_UpperCAmelCase  )

        # Swin has a different seq_length
        lowercase__				 =							(
            config.patch_size
            if isinstance(config.patch_size,				collections.abc.Iterable  )
            else (config.patch_size, config.patch_size)
        )

        lowercase__				 =							(image_size[1] // patch_size[1]) * (image_size[0] // patch_size[0])

        self.assertListEqual(
            list(hidden_states[0].shape[-2:]  ),				[num_patches, self.model_tester.embed_dim],				)


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__ ,						lowercase__				 =							self.model_tester.prepare_config_and_inputs_for_common()

        lowercase__				 =							(
            self.model_tester.image_size
            if isinstance(self.model_tester.image_size,				collections.abc.Iterable  )
            else (self.model_tester.image_size, self.model_tester.image_size)
        )

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

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

             self.check_hidden_states_output(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__ ,						lowercase__				 =							self.model_tester.prepare_config_and_inputs_for_common()
        lowercase__				 =							3

        lowercase__				 =							(
            self.model_tester.image_size
            if isinstance(self.model_tester.image_size,				collections.abc.Iterable  )
            else (self.model_tester.image_size, self.model_tester.image_size)
        )
        lowercase__				 =							(
            config.patch_size
            if isinstance(config.patch_size,				collections.abc.Iterable  )
            else (config.patch_size, config.patch_size)
        )

        lowercase__				 =							image_size[0] + patch_size[0] - (image_size[0] % patch_size[0])
        lowercase__				 =							image_size[1] + patch_size[1] - (image_size[1] % patch_size[1])

        for model_class in self.all_model_classes:
             lowercase__				 =							True
             self.check_hidden_states_output(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase,				(padded_height, padded_width)  )

             # check that output_hidden_states also work using config
             del inputs_dict["output_hidden_states"]
             lowercase__				 =							True
             self.check_hidden_states_output(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase,				(padded_height, padded_width)  )


   @unittest.skip(reason="MaskFormerSwin doesn't have pretrained checkpoints"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   @unittest.skip(reason="This will be fixed once MaskFormerSwin is replaced by native Swin"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   @unittest.skip(reason="This will be fixed once MaskFormerSwin is replaced by native Swin"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__ ,						lowercase__				 =							self.model_tester.prepare_config_and_inputs_for_common()

        def set_nan_tensor_to_zero(_UpperCAmelCase  ):
             lowercase__				 =							0
             return t

        def check_equivalence(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase={}  ):
             with torch.no_grad():
                  lowercase__				 =							model(**_UpperCAmelCase,				return_dict=_UpperCAmelCase,				**_UpperCAmelCase  )
                  lowercase__				 =							model(**_UpperCAmelCase,				return_dict=_UpperCAmelCase,				**_UpperCAmelCase  ).to_tuple()

                  def recursive_check(_UpperCAmelCase,				_UpperCAmelCase  ):
                       if isinstance(_UpperCAmelCase,				(List, Tuple)  ):
                            for tuple_iterable_value, dict_iterable_value in zip(_UpperCAmelCase,				_UpperCAmelCase  ):
                                 recursive_check(_UpperCAmelCase,				_UpperCAmelCase  )
                       elif isinstance(_UpperCAmelCase,				_UpperCAmelCase  ):
                            for tuple_iterable_value, dict_iterable_value in zip(
                                tuple_object.values(),				dict_object.values()  ):
                                 recursive_check(_UpperCAmelCase,				_UpperCAmelCase  )
                       elif tuple_object is None:
                            return
                       else:
                            self.assertTrue(
                                torch.allclose(
                                    set_nan_tensor_to_zero(_UpperCAmelCase  ),				set_nan_tensor_to_zero(_UpperCAmelCase  ),				atol=1E-5  ),				msg=(
                                    "Tuple and dict output are not equal. Difference:"
                                    F''' {torch.max(torch.abs(tuple_object - dict_object  )  )}. Tuple has `nan`:'''
                                    F''' {torch.isnan(_UpperCAmelCase  ).any()} and `inf`: {torch.isinf(_UpperCAmelCase  )}. Dict has'''
                                    F''' `nan`: {torch.isnan(_UpperCAmelCase  ).any()} and `inf`: {torch.isinf(_UpperCAmelCase  )}.'''
                                ),				)

                  recursive_check(_UpperCAmelCase,				_UpperCAmelCase  )

        for model_class in self.all_model_classes:
             lowercase__				 =							model_class(_UpperCAmelCase  )
             model.to(_UpperCAmelCase  )
             model.eval()

             lowercase__				 =							self._prepare_for_class(_UpperCAmelCase,				_UpperCAmelCase  )
             lowercase__				 =							self._prepare_for_class(_UpperCAmelCase,				_UpperCAmelCase  )
             check_equivalence(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase  )

             lowercase__				 =							self._prepare_for_class(_UpperCAmelCase,				_UpperCAmelCase,				return_labels=_UpperCAmelCase  )
             lowercase__				 =							self._prepare_for_class(_UpperCAmelCase,				_UpperCAmelCase,				return_labels=_UpperCAmelCase  )
             check_equivalence(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase  )

             lowercase__				 =							self._prepare_for_class(_UpperCAmelCase,				_UpperCAmelCase  )
             lowercase__				 =							self._prepare_for_class(_UpperCAmelCase,				_UpperCAmelCase  )
             check_equivalence(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase,				{"output_hidden_states": True}  )

             lowercase__				 =							self._prepare_for_class(_UpperCAmelCase,				_UpperCAmelCase,				return_labels=_UpperCAmelCase  )
             lowercase__				 =							self._prepare_for_class(_UpperCAmelCase,				_UpperCAmelCase,				return_labels=_UpperCAmelCase  )
             check_equivalence(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase,				{"output_hidden_states": True}  )






@require_torch
class    a__    (   unittest.TestCase					,					_a	):
   snake_case_							=      (MaskFormerSwinBackbone,) if is_torch_available() else ()
   snake_case_							=      MaskFormerSwinConfig


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							MaskFormerSwinModelTester(self  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__ ,						lowercase__				 =							self.model_tester.prepare_config_and_inputs_for_common()
        lowercase__				 =							inputs_dict["pixel_values"].shape[0]

        for backbone_class in self.all_model_classes:
             lowercase__				 =							backbone_class(_UpperCAmelCase  )
             backbone.to(_UpperCAmelCase  )
             backbone.eval()

             lowercase__				 =							backbone(**_UpperCAmelCase  )

             # Test default outputs and verify feature maps
             self.assertIsInstance(outputs.feature_maps,				_UpperCAmelCase  )
             self.assertTrue(len(outputs.feature_maps  ) == len(backbone.channels  )  )
             for feature_map, n_channels in zip(outputs.feature_maps,				backbone.channels  ):
                  self.assertTrue(feature_map.shape[:2],				(batch_size, n_channels)  )
             self.assertIsNone(outputs.hidden_states  )
             self.assertIsNone(outputs.attentions  )

             # Test output_hidden_states=True
             lowercase__				 =							backbone(**_UpperCAmelCase,				output_hidden_states=_UpperCAmelCase  )
             self.assertIsNotNone(outputs.hidden_states  )
             self.assertTrue(len(outputs.hidden_states  ),				len(backbone.stage_names  )  )
             # We skip the stem layer
             for hidden_states, n_channels in zip(outputs.hidden_states[1:],				backbone.channels  ):
                  for hidden_state in hidden_states:
                       # Hidden states are in the format (batch_size, (height * width), n_channels)
                       lowercase__ ,						lowercase__ ,						lowercase__				 =							hidden_state.shape
                       self.assertTrue((h_batch_size, h_n_channels),				(batch_size, n_channels)  )

            # Test output_attentions=True
             if self.has_attentions:
                  lowercase__				 =							backbone(**_UpperCAmelCase,				output_attentions=_UpperCAmelCase  )
                  self.assertIsNotNone(outputs.attentions  )





"""simple docstring"""


lowerCAmelCase_:					Union[str, Any]     =					[
    9_9_9,
    8_0_0,
    7_9_9,
    6_0_0,
    5_9_9,
    5_0_0,
    4_0_0,
    3_9_9,
    3_7_7,
    3_5_5,
    3_3_3,
    3_1_1,
    2_8_8,
    2_6_6,
    2_4_4,
    2_2_2,
    2_0_0,
    1_9_9,
    1_7_7,
    1_5_5,
    1_3_3,
    1_1_1,
    8_8,
    6_6,
    4_4,
    2_2,
    0,
]

lowerCAmelCase_:					List[str]     =					[
    9_9_9,
    9_7_6,
    9_5_2,
    9_2_8,
    9_0_5,
    8_8_2,
    8_5_8,
    8_5_7,
    8_1_0,
    7_6_2,
    7_1_5,
    7_1_4,
    5_7_2,
    4_2_9,
    4_2_8,
    2_8_6,
    2_8_5,
    2_3_8,
    1_9_0,
    1_4_3,
    1_4_2,
    1_1_8,
    9_5,
    7_1,
    4_7,
    2_4,
    0,
]

lowerCAmelCase_:					List[str]     =					[
    9_9_9,
    9_8_8,
    9_7_7,
    9_6_6,
    9_5_5,
    9_4_4,
    9_3_3,
    9_2_2,
    9_1_1,
    9_0_0,
    8_9_9,
    8_7_9,
    8_5_9,
    8_4_0,
    8_2_0,
    8_0_0,
    7_9_9,
    7_6_6,
    7_3_3,
    7_0_0,
    6_9_9,
    6_5_0,
    6_0_0,
    5_9_9,
    5_0_0,
    4_9_9,
    4_0_0,
    3_9_9,
    3_5_0,
    3_0_0,
    2_9_9,
    2_6_6,
    2_3_3,
    2_0_0,
    1_9_9,
    1_7_9,
    1_5_9,
    1_4_0,
    1_2_0,
    1_0_0,
    9_9,
    8_8,
    7_7,
    6_6,
    5_5,
    4_4,
    3_3,
    2_2,
    1_1,
    0,
]

lowerCAmelCase_:					Dict     =					[
    9_9_9,
    9_9_5,
    9_9_2,
    9_8_9,
    9_8_5,
    9_8_1,
    9_7_8,
    9_7_5,
    9_7_1,
    9_6_7,
    9_6_4,
    9_6_1,
    9_5_7,
    9_5_6,
    9_5_1,
    9_4_7,
    9_4_2,
    9_3_7,
    9_3_3,
    9_2_8,
    9_2_3,
    9_1_9,
    9_1_4,
    9_1_3,
    9_0_8,
    9_0_3,
    8_9_7,
    8_9_2,
    8_8_7,
    8_8_1,
    8_7_6,
    8_7_1,
    8_7_0,
    8_6_4,
    8_5_8,
    8_5_2,
    8_4_6,
    8_4_0,
    8_3_4,
    8_2_8,
    8_2_7,
    8_2_0,
    8_1_3,
    8_0_6,
    7_9_9,
    7_9_2,
    7_8_5,
    7_8_4,
    7_7_7,
    7_7_0,
    7_6_3,
    7_5_6,
    7_4_9,
    7_4_2,
    7_4_1,
    7_3_3,
    7_2_4,
    7_1_6,
    7_0_7,
    6_9_9,
    6_9_8,
    6_8_8,
    6_7_7,
    6_6_6,
    6_5_6,
    6_5_5,
    6_4_5,
    6_3_4,
    6_2_3,
    6_1_3,
    6_1_2,
    5_9_8,
    5_8_4,
    5_7_0,
    5_6_9,
    5_5_5,
    5_4_1,
    5_2_7,
    5_2_6,
    5_0_5,
    4_8_4,
    4_8_3,
    4_6_2,
    4_4_0,
    4_3_9,
    3_9_6,
    3_9_5,
    3_5_2,
    3_5_1,
    3_0_8,
    3_0_7,
    2_6_4,
    2_6_3,
    2_2_0,
    2_1_9,
    1_7_6,
    1_3_2,
    8_8,
    4_4,
    0,
]

lowerCAmelCase_:					Optional[int]     =					[
    9_9_9,
    9_9_7,
    9_9_5,
    9_9_2,
    9_9_0,
    9_8_8,
    9_8_6,
    9_8_4,
    9_8_1,
    9_7_9,
    9_7_7,
    9_7_5,
    9_7_2,
    9_7_0,
    9_6_8,
    9_6_6,
    9_6_4,
    9_6_1,
    9_5_9,
    9_5_7,
    9_5_6,
    9_5_4,
    9_5_1,
    9_4_9,
    9_4_6,
    9_4_4,
    9_4_1,
    9_3_9,
    9_3_6,
    9_3_4,
    9_3_1,
    9_2_9,
    9_2_6,
    9_2_4,
    9_2_1,
    9_1_9,
    9_1_6,
    9_1_4,
    9_1_3,
    9_1_0,
    9_0_7,
    9_0_5,
    9_0_2,
    8_9_9,
    8_9_6,
    8_9_3,
    8_9_1,
    8_8_8,
    8_8_5,
    8_8_2,
    8_7_9,
    8_7_7,
    8_7_4,
    8_7_1,
    8_7_0,
    8_6_7,
    8_6_4,
    8_6_1,
    8_5_8,
    8_5_5,
    8_5_2,
    8_4_9,
    8_4_6,
    8_4_3,
    8_4_0,
    8_3_7,
    8_3_4,
    8_3_1,
    8_2_8,
    8_2_7,
    8_2_4,
    8_2_1,
    8_1_7,
    8_1_4,
    8_1_1,
    8_0_8,
    8_0_4,
    8_0_1,
    7_9_8,
    7_9_5,
    7_9_1,
    7_8_8,
    7_8_5,
    7_8_4,
    7_8_0,
    7_7_7,
    7_7_4,
    7_7_0,
    7_6_6,
    7_6_3,
    7_6_0,
    7_5_6,
    7_5_2,
    7_4_9,
    7_4_6,
    7_4_2,
    7_4_1,
    7_3_7,
    7_3_3,
    7_3_0,
    7_2_6,
    7_2_2,
    7_1_8,
    7_1_4,
    7_1_0,
    7_0_7,
    7_0_3,
    6_9_9,
    6_9_8,
    6_9_4,
    6_9_0,
    6_8_5,
    6_8_1,
    6_7_7,
    6_7_3,
    6_6_9,
    6_6_4,
    6_6_0,
    6_5_6,
    6_5_5,
    6_5_0,
    6_4_6,
    6_4_1,
    6_3_6,
    6_3_2,
    6_2_7,
    6_2_2,
    6_1_8,
    6_1_3,
    6_1_2,
    6_0_7,
    6_0_2,
    5_9_6,
    5_9_1,
    5_8_6,
    5_8_0,
    5_7_5,
    5_7_0,
    5_6_9,
    5_6_3,
    5_5_7,
    5_5_1,
    5_4_5,
    5_3_9,
    5_3_3,
    5_2_7,
    5_2_6,
    5_1_9,
    5_1_2,
    5_0_5,
    4_9_8,
    4_9_1,
    4_8_4,
    4_8_3,
    4_7_4,
    4_6_6,
    4_5_7,
    4_4_9,
    4_4_0,
    4_3_9,
    4_2_8,
    4_1_8,
    4_0_7,
    3_9_6,
    3_9_5,
    3_8_1,
    3_6_6,
    3_5_2,
    3_5_1,
    3_3_0,
    3_0_8,
    3_0_7,
    2_8_6,
    2_6_4,
    2_6_3,
    2_4_2,
    2_2_0,
    2_1_9,
    1_7_6,
    1_7_5,
    1_3_2,
    1_3_1,
    8_8,
    4_4,
    0,
]

lowerCAmelCase_:					Tuple     =					[
    9_9_9,
    9_9_1,
    9_8_2,
    9_7_4,
    9_6_6,
    9_5_8,
    9_5_0,
    9_4_1,
    9_3_3,
    9_2_5,
    9_1_6,
    9_0_8,
    9_0_0,
    8_9_9,
    8_7_4,
    8_5_0,
    8_2_5,
    8_0_0,
    7_9_9,
    7_0_0,
    6_0_0,
    5_0_0,
    4_0_0,
    3_0_0,
    2_0_0,
    1_0_0,
    0,
]

lowerCAmelCase_:					str     =					[
    9_9_9,
    9_9_2,
    9_8_5,
    9_7_8,
    9_7_1,
    9_6_4,
    9_5_7,
    9_4_9,
    9_4_2,
    9_3_5,
    9_2_8,
    9_2_1,
    9_1_4,
    9_0_7,
    9_0_0,
    8_9_9,
    8_7_9,
    8_5_9,
    8_4_0,
    8_2_0,
    8_0_0,
    7_9_9,
    7_6_6,
    7_3_3,
    7_0_0,
    6_9_9,
    6_5_0,
    6_0_0,
    5_9_9,
    5_0_0,
    4_9_9,
    4_0_0,
    3_9_9,
    3_0_0,
    2_9_9,
    2_0_0,
    1_9_9,
    1_0_0,
    9_9,
    0,
]

lowerCAmelCase_:					int     =					[
    9_9_9,
    9_9_6,
    9_9_2,
    9_8_9,
    9_8_5,
    9_8_2,
    9_7_9,
    9_7_5,
    9_7_2,
    9_6_8,
    9_6_5,
    9_6_1,
    9_5_8,
    9_5_5,
    9_5_1,
    9_4_8,
    9_4_4,
    9_4_1,
    9_3_8,
    9_3_4,
    9_3_1,
    9_2_7,
    9_2_4,
    9_2_0,
    9_1_7,
    9_1_4,
    9_1_0,
    9_0_7,
    9_0_3,
    9_0_0,
    8_9_9,
    8_9_1,
    8_8_4,
    8_7_6,
    8_6_9,
    8_6_1,
    8_5_3,
    8_4_6,
    8_3_8,
    8_3_0,
    8_2_3,
    8_1_5,
    8_0_8,
    8_0_0,
    7_9_9,
    7_8_8,
    7_7_7,
    7_6_6,
    7_5_5,
    7_4_4,
    7_3_3,
    7_2_2,
    7_1_1,
    7_0_0,
    6_9_9,
    6_8_8,
    6_7_7,
    6_6_6,
    6_5_5,
    6_4_4,
    6_3_3,
    6_2_2,
    6_1_1,
    6_0_0,
    5_9_9,
    5_8_5,
    5_7_1,
    5_5_7,
    5_4_2,
    5_2_8,
    5_1_4,
    5_0_0,
    4_9_9,
    4_8_5,
    4_7_1,
    4_5_7,
    4_4_2,
    4_2_8,
    4_1_4,
    4_0_0,
    3_9_9,
    3_7_9,
    3_5_9,
    3_4_0,
    3_2_0,
    3_0_0,
    2_9_9,
    2_7_9,
    2_5_9,
    2_4_0,
    2_2_0,
    2_0_0,
    1_9_9,
    1_6_6,
    1_3_3,
    1_0_0,
    9_9,
    6_6,
    3_3,
    0,
]




