



"""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 				lowercase__       :







       '''simple docstring'''


       def __init__(							self      :  Dict		,    _UpperCAmelCase      :  int		,    _UpperCAmelCase      :  List[str]=13		,    _UpperCAmelCase      :  Dict=32		,    _UpperCAmelCase      :  Any=2		,    _UpperCAmelCase      :  Optional[int]=3		,    _UpperCAmelCase      :  Optional[Any]=16		,    _UpperCAmelCase      :  Optional[int]=[1, 2, 1]		,    _UpperCAmelCase      :  int=[2, 2, 4]		,    _UpperCAmelCase      :  Optional[Any]=2		,    _UpperCAmelCase      :  Union[str, Any]=2.0		,    _UpperCAmelCase      :  Any=True		,    _UpperCAmelCase      :  Optional[Any]=0.0		,    _UpperCAmelCase      :  Dict=0.0		,    _UpperCAmelCase      :  Dict=0.1		,    _UpperCAmelCase      :  str="gelu"		,    _UpperCAmelCase      :  List[Any]=False		,    _UpperCAmelCase      :  List[Any]=True		,    _UpperCAmelCase      :  Optional[Any]=0.02		,    _UpperCAmelCase      :  str=1e-5		,    _UpperCAmelCase      :  str=True		,    _UpperCAmelCase      :  Any=None		,    _UpperCAmelCase      :  Tuple=True		,    _UpperCAmelCase      :  Any=10		,    _UpperCAmelCase      :  int=8		,    _UpperCAmelCase      :  Optional[Any]=["stage1", "stage2", "stage3"]		,    _UpperCAmelCase      :  Optional[Any]=[1, 2, 3]		,    )			->						List[Any]:


             '''simple docstring'''




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



       def 					lowercase__    (							self      :  int   )			->						Any:


             '''simple docstring'''




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

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

             UpperCAmelCase_      			=							self.get_config()

             return config, pixel_values, labels



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


             '''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 					lowercase__    (							self      :  List[Any]		,    _UpperCAmelCase      :  Union[str, Any]		,    _UpperCAmelCase      :  str		,    _UpperCAmelCase      :  int   )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							MaskFormerSwinModel(config=_lowercase   )
             model.to(_lowercase   )
             model.eval()
             UpperCAmelCase_      			=							model(_lowercase   )

             UpperCAmelCase_      			=							((config.image_size // config.patch_size) ** 2) // (4 ** (len(config.depths   ) - 1))
             UpperCAmelCase_      			=							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 					lowercase__    (							self      :  int		,    _UpperCAmelCase      :  Optional[Any]		,    _UpperCAmelCase      :  Any		,    _UpperCAmelCase      :  Dict   )			->						Dict:


             '''simple docstring'''




             UpperCAmelCase_      			=							MaskFormerSwinBackbone(config=_lowercase   )
             model.to(_lowercase   )
             model.eval()
             UpperCAmelCase_      			=							model(_lowercase   )

             # 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(_lowercase   ):
                   UpperCAmelCase_      			=							["stem"]
                   UpperCAmelCase_      			=							MaskFormerSwinBackbone(config=_lowercase   )







       def 					lowercase__    (							self      :  Optional[int]   )			->						Any:


             '''simple docstring'''




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



@require_torch
class 				lowercase__       (   _lowerCAmelCase    , _lowerCAmelCase    , unittest.TestCase				):







       '''simple docstring'''


       UpperCamelCase						=					(
           (
               MaskFormerSwinModel,
               MaskFormerSwinBackbone,
           )
           if is_torch_available()
           else ()
       )
       UpperCamelCase						=					{"feature-extraction": MaskFormerSwinModel} if is_torch_available() else {}
       UpperCamelCase						=					False
       UpperCamelCase						=					False
       UpperCamelCase						=					False
       UpperCamelCase						=					False
       UpperCamelCase						=					False



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


             '''simple docstring'''




             UpperCAmelCase_      			=							MaskFormerSwinModelTester(self   )
             UpperCAmelCase_      			=							ConfigTester(self		,    config_class=_lowercase		,    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 					lowercase__    (							self      :  int   )			->						Tuple:


             '''simple docstring'''




             pass



       def 					lowercase__    (							self      :  Dict   )			->						Tuple:


             '''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 					lowercase__    (							self      :  str   )			->						Union[str, Any]:


             '''simple docstring'''




             return



       def 					lowercase__    (							self      :  Optional[Any]   )			->						Any:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_model(*_lowercase   )



       def 					lowercase__    (							self      :  Optional[int]   )			->						Tuple:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_backbone(*_lowercase   )



       @unittest.skip("Swin does not use inputs_embeds"   )
       def 					lowercase__    (							self      :  List[Any]   )			->						Dict:


             '''simple docstring'''




             pass



       @unittest.skip("Swin does not support feedforward chunking"   )
       def 					lowercase__    (							self      :  str   )			->						List[str]:


             '''simple docstring'''




             pass



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


             '''simple docstring'''




             UpperCAmelCase_			,   UpperCAmelCase_      			=							self.model_tester.prepare_config_and_inputs_for_common()

             for model_class in self.all_model_classes:
                   UpperCAmelCase_      			=							model_class(_lowercase   )
                   self.assertIsInstance(model.get_input_embeddings()		,    (nn.Module)   )
                   UpperCAmelCase_      			=							model.get_output_embeddings()
                   self.assertTrue(x is None or isinstance(_lowercase		,    nn.Linear   )   )



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


             '''simple docstring'''




             UpperCAmelCase_			,   UpperCAmelCase_      			=							self.model_tester.prepare_config_and_inputs_for_common()

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

                   UpperCAmelCase_      			=							["pixel_values"]
                   self.assertListEqual(arg_names[:1]		,    _lowercase   )



       @unittest.skip(reason="MaskFormerSwin is only used as backbone and doesn\'t support output_attentions"   )
       def 					lowercase__    (							self      :  Optional[Any]   )			->						str:


             '''simple docstring'''




             pass



       @unittest.skip(reason="MaskFormerSwin is only used as an internal backbone"   )
       def 					lowercase__    (							self      :  Optional[Any]   )			->						Optional[int]:


             '''simple docstring'''




             pass



       def 					lowercase__    (							self      :  List[Any]		,    _UpperCAmelCase      :  Union[str, Any]		,    _UpperCAmelCase      :  List[str]		,    _UpperCAmelCase      :  Dict		,    _UpperCAmelCase      :  Tuple   )			->						Tuple:


             '''simple docstring'''




             UpperCAmelCase_      			=							model_class(_lowercase   )
             model.to(_lowercase   )
             model.eval()

             with torch.no_grad():
                   UpperCAmelCase_      			=							model(**self._prepare_for_class(_lowercase		,    _lowercase   )   )

             UpperCAmelCase_      			=							outputs.hidden_states

             UpperCAmelCase_      			=							getattr(
                 self.model_tester		,    "expected_num_hidden_layers"		,    len(self.model_tester.depths   ) + 1   )
             self.assertEqual(len(_lowercase   )		,    _lowercase   )

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

             UpperCAmelCase_      			=							(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 					lowercase__    (							self      :  str   )			->						Dict:


             '''simple docstring'''




             UpperCAmelCase_			,   UpperCAmelCase_      			=							self.model_tester.prepare_config_and_inputs_for_common()

             UpperCAmelCase_      			=							(
                 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:
                   UpperCAmelCase_      			=							True
                   self.check_hidden_states_output(_lowercase		,    _lowercase		,    _lowercase		,    _lowercase   )

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

                   self.check_hidden_states_output(_lowercase		,    _lowercase		,    _lowercase		,    _lowercase   )



       def 					lowercase__    (							self      :  Optional[Any]   )			->						Tuple:


             '''simple docstring'''




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

             UpperCAmelCase_      			=							(
                 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)
             )
             UpperCAmelCase_      			=							(
                 config.patch_size
                 if isinstance(config.patch_size		,    collections.abc.Iterable   )
                 else (config.patch_size, config.patch_size)
             )

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

             for model_class in self.all_model_classes:
                   UpperCAmelCase_      			=							True
                   self.check_hidden_states_output(_lowercase		,    _lowercase		,    _lowercase		,    (padded_height, padded_width)   )

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



       @unittest.skip(reason="MaskFormerSwin doesn\'t have pretrained checkpoints"   )
       def 					lowercase__    (							self      :  Any   )			->						int:


             '''simple docstring'''




             pass



       @unittest.skip(reason="This will be fixed once MaskFormerSwin is replaced by native Swin"   )
       def 					lowercase__    (							self      :  str   )			->						Optional[int]:


             '''simple docstring'''




             pass



       @unittest.skip(reason="This will be fixed once MaskFormerSwin is replaced by native Swin"   )
       def 					lowercase__    (							self      :  Tuple   )			->						Union[str, Any]:


             '''simple docstring'''




             pass







       def 					lowercase__    (							self      :  Tuple   )			->						Dict:


             '''simple docstring'''




             UpperCAmelCase_			,   UpperCAmelCase_      			=							self.model_tester.prepare_config_and_inputs_for_common()

             def set_nan_tensor_to_zero(_UpperCAmelCase      :  List[str]   ):
                   UpperCAmelCase_      			=							0
                   return t

             def check_equivalence(_UpperCAmelCase      :  List[Any]		,    _UpperCAmelCase      :  Any		,    _UpperCAmelCase      :  str		,    _UpperCAmelCase      :  List[str]={}   ):
                   with torch.no_grad():
                         UpperCAmelCase_      			=							model(**_lowercase		,    return_dict=_lowercase		,    **_lowercase   )
                         UpperCAmelCase_      			=							model(**_lowercase		,    return_dict=_lowercase		,    **_lowercase   ).to_tuple()

                         def recursive_check(_UpperCAmelCase      :  Dict		,    _UpperCAmelCase      :  Optional[Any]   ):
                               if isinstance(_lowercase		,    (List, Tuple)   ):
                                     for tuple_iterable_value, dict_iterable_value in zip(_lowercase		,    _lowercase   ):
                                           recursive_check(_lowercase		,    _lowercase   )
                               elif isinstance(_lowercase		,    _lowercase   ):
                                     for tuple_iterable_value, dict_iterable_value in zip(
                                         tuple_object.values()		,    dict_object.values()   ):
                                           recursive_check(_lowercase		,    _lowercase   )
                               elif tuple_object is None:
                                     return
                               else:
                                     self.assertTrue(
                                         torch.allclose(
                                             set_nan_tensor_to_zero(_lowercase   )		,    set_nan_tensor_to_zero(_lowercase   )		,    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(_lowercase   ).any()} and `inf`: {torch.isinf(_lowercase   )}. Dict has"""
                                             F""" `nan`: {torch.isnan(_lowercase   ).any()} and `inf`: {torch.isinf(_lowercase   )}."""
                                         )		,    )

                         recursive_check(_lowercase		,    _lowercase   )

             for model_class in self.all_model_classes:
                   UpperCAmelCase_      			=							model_class(_lowercase   )
                   model.to(_lowercase   )
                   model.eval()

                   UpperCAmelCase_      			=							self._prepare_for_class(_lowercase		,    _lowercase   )
                   UpperCAmelCase_      			=							self._prepare_for_class(_lowercase		,    _lowercase   )
                   check_equivalence(_lowercase		,    _lowercase		,    _lowercase   )

                   UpperCAmelCase_      			=							self._prepare_for_class(_lowercase		,    _lowercase		,    return_labels=_lowercase   )
                   UpperCAmelCase_      			=							self._prepare_for_class(_lowercase		,    _lowercase		,    return_labels=_lowercase   )
                   check_equivalence(_lowercase		,    _lowercase		,    _lowercase   )

                   UpperCAmelCase_      			=							self._prepare_for_class(_lowercase		,    _lowercase   )
                   UpperCAmelCase_      			=							self._prepare_for_class(_lowercase		,    _lowercase   )
                   check_equivalence(_lowercase		,    _lowercase		,    _lowercase		,    {"output_hidden_states": True}   )

                   UpperCAmelCase_      			=							self._prepare_for_class(_lowercase		,    _lowercase		,    return_labels=_lowercase   )
                   UpperCAmelCase_      			=							self._prepare_for_class(_lowercase		,    _lowercase		,    return_labels=_lowercase   )
                   check_equivalence(_lowercase		,    _lowercase		,    _lowercase		,    {"output_hidden_states": True}   )



@require_torch
class 				lowercase__       (   unittest.TestCase    , _lowerCAmelCase				):







       '''simple docstring'''


       UpperCamelCase						=					(MaskFormerSwinBackbone,) if is_torch_available() else ()
       UpperCamelCase						=					MaskFormerSwinConfig



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


             '''simple docstring'''




             UpperCAmelCase_      			=							MaskFormerSwinModelTester(self   )







       def 					lowercase__    (							self      :  List[Any]   )			->						Dict:


             '''simple docstring'''




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

             for backbone_class in self.all_model_classes:
                   UpperCAmelCase_      			=							backbone_class(_lowercase   )
                   backbone.to(_lowercase   )
                   backbone.eval()

                   UpperCAmelCase_      			=							backbone(**_lowercase   )

                   # Test default outputs and verify feature maps
                   self.assertIsInstance(outputs.feature_maps		,    _lowercase   )
                   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
                   UpperCAmelCase_      			=							backbone(**_lowercase		,    output_hidden_states=_lowercase   )
                   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)
                               UpperCAmelCase_			,   UpperCAmelCase_			,   UpperCAmelCase_      			=							hidden_state.shape
                               self.assertTrue((h_batch_size, h_n_channels)		,    (batch_size, n_channels)   )

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




"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase       	=						logging.get_logger(__name__)

lowerCamelCase       	=						{
    """RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-430m-pile""": """https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-1b5-pile""": """https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-3b-pile""": """https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-7b-pile""": """https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-14b-pile""": """https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json""",
    """RWKV/rwkv-raven-1b5""": """https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json""",
    """RWKV/rwkv-raven-3b""": """https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json""",
    """RWKV/rwkv-raven-7b""": """https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json""",
    """RWKV/rwkv-raven-14b""": """https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json""",
}
class 				lowercase__       (   SCREAMING_SNAKE_CASE				):







       '''simple docstring'''


       UpperCamelCase						=					'''rwkv'''
       UpperCamelCase						=					{'''max_position_embeddings''': '''context_length'''}



       def __init__(							self      :  str		,    _UpperCAmelCase      :  int=50277		,    _UpperCAmelCase      :  Optional[Any]=1024		,    _UpperCAmelCase      :  str=4096		,    _UpperCAmelCase      :  Any=32		,    _UpperCAmelCase      :  Any=None		,    _UpperCAmelCase      :  Optional[int]=None		,    _UpperCAmelCase      :  Tuple=1e-5		,    _UpperCAmelCase      :  str=0		,    _UpperCAmelCase      :  Any=0		,    _UpperCAmelCase      :  Union[str, Any]=6		,    _UpperCAmelCase      :  Dict=False		,    _UpperCAmelCase      :  Any=True		,    **_UpperCAmelCase      :  Optional[Any]		,    )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							vocab_size
             UpperCAmelCase_      			=							context_length
             UpperCAmelCase_      			=							hidden_size
             UpperCAmelCase_      			=							num_hidden_layers
             UpperCAmelCase_      			=							attention_hidden_size if attention_hidden_size is not None else hidden_size
             UpperCAmelCase_      			=							intermediate_size if intermediate_size is not None else 4 * hidden_size
             UpperCAmelCase_      			=							layer_norm_epsilon
             UpperCAmelCase_      			=							rescale_every
             UpperCAmelCase_      			=							use_cache

             UpperCAmelCase_      			=							bos_token_id
             UpperCAmelCase_      			=							eos_token_id

             super().__init__(
                 tie_word_embeddings=_UpperCAmelCase		,    bos_token_id=_UpperCAmelCase		,    eos_token_id=_UpperCAmelCase		,    **_UpperCAmelCase   )




