
'''simple docstring'''


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


__lowercase							:      List[Any]		 =   logging.get_logger(__name__)

__lowercase							:      int		 =   {
    "transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}

class 		__lowercase (     _lowercase			):
			lowerCamelCase	:						Optional[int]							=	'''transfo-xl'''
			lowerCamelCase	:						Optional[Any]							=	['''mems''']
			lowerCamelCase	:						Optional[Any]							=	{
			    '''n_token''': '''vocab_size''',
			    '''hidden_size''': '''d_model''',
			    '''num_attention_heads''': '''n_head''',
			    '''num_hidden_layers''': '''n_layer''',
			}

			def __init__(self	,      A=2_6_7_7_3_5	,      A=[2_0_0_0_0, 4_0_0_0_0, 2_0_0_0_0_0]	,      A=1_0_2_4	,      A=1_0_2_4	,      A=1_6	,      A=6_4	,      A=4_0_9_6	,      A=4	,      A=False	,      A=1_8	,      A=1_6_0_0	,      A=1_0_0_0	,      A=True	,      A=True	,      A=0	,      A=-1	,      A=True	,      A=0.1	,      A=0.0	,      A=True	,      A="normal"	,      A=0.01	,      A=0.01	,      A=0.02	,      A=1E-5	,      A=0	,      **A	,      ):
								lowerCamelCase_    :					int   =						vocab_size
								lowerCamelCase_    :					Union[str, Any]   =						[]
								self.cutoffs.extend(_snake_case					)
								if proj_share_all_but_first:
													lowerCamelCase_    :					Optional[Any]   =						[False] + [True] * len(self.cutoffs					)
								else:
													lowerCamelCase_    :					int   =						[False] + [False] * len(self.cutoffs					)
								lowerCamelCase_    :					Union[str, Any]   =						d_model
								lowerCamelCase_    :					Tuple   =						d_embed
								lowerCamelCase_    :					int   =						d_head
								lowerCamelCase_    :					List[str]   =						d_inner
								lowerCamelCase_    :					int   =						div_val
								lowerCamelCase_    :					Optional[int]   =						pre_lnorm
								lowerCamelCase_    :					int   =						n_layer
								lowerCamelCase_    :					Any   =						n_head
								lowerCamelCase_    :					Tuple   =						mem_len
								lowerCamelCase_    :					Optional[Any]   =						same_length
								lowerCamelCase_    :					Optional[int]   =						attn_type
								lowerCamelCase_    :					Optional[int]   =						clamp_len
								lowerCamelCase_    :					Optional[int]   =						sample_softmax
								lowerCamelCase_    :					Union[str, Any]   =						adaptive
								lowerCamelCase_    :					int   =						dropout
								lowerCamelCase_    :					Optional[int]   =						dropatt
								lowerCamelCase_    :					Tuple   =						untie_r
								lowerCamelCase_    :					Any   =						init
								lowerCamelCase_    :					Dict   =						init_range
								lowerCamelCase_    :					Optional[int]   =						proj_init_std
								lowerCamelCase_    :					Union[str, Any]   =						init_std
								lowerCamelCase_    :					Tuple   =						layer_norm_epsilon
								super().__init__(eos_token_id=_snake_case	,      **_snake_case					)

			@property
			def 				UpperCAmelCase__       (self					):
								logger.info(F"""The model {self.model_type} is one of the few models that has no sequence length limit."""					)
								return -1






			@max_position_embeddings.setter
			def 				UpperCAmelCase__       (self	,      A					):
								raise NotImplementedError(
								    F"""The model {self.model_type} is one of the few models that has no sequence length limit."""					)








snake_case_ : Dict    		=       {
    "Pillow": "Pillow",
    "accelerate": "accelerate>=0.11.0",
    "compel": "compel==0.1.8",
    "black": "black~=23.1",
    "datasets": "datasets",
    "filelock": "filelock",
    "flax": "flax>=0.4.1",
    "hf-doc-builder": "hf-doc-builder>=0.3.0",
    "huggingface-hub": "huggingface-hub>=0.13.2",
    "requests-mock": "requests-mock==1.10.0",
    "importlib_metadata": "importlib_metadata",
    "invisible-watermark": "invisible-watermark",
    "isort": "isort>=5.5.4",
    "jax": "jax>=0.2.8,!=0.3.2",
    "jaxlib": "jaxlib>=0.1.65",
    "Jinja2": "Jinja2",
    "k-diffusion": "k-diffusion>=0.0.12",
    "torchsde": "torchsde",
    "note_seq": "note_seq",
    "librosa": "librosa",
    "numpy": "numpy",
    "omegaconf": "omegaconf",
    "parameterized": "parameterized",
    "protobuf": "protobuf>=3.20.3,<4",
    "pytest": "pytest",
    "pytest-timeout": "pytest-timeout",
    "pytest-xdist": "pytest-xdist",
    "ruff": "ruff>=0.0.241",
    "safetensors": "safetensors",
    "sentencepiece": "sentencepiece>=0.1.91,!=0.1.92",
    "scipy": "scipy",
    "onnx": "onnx",
    "regex": "regex!=2019.12.17",
    "requests": "requests",
    "tensorboard": "tensorboard",
    "torch": "torch>=1.4",
    "torchvision": "torchvision",
    "transformers": "transformers>=4.25.1",
    "urllib3": "urllib3<=2.0.0",
}






