


'''simple docstring'''



# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


_lowercase      :      Any            =					logging.get_logger(__name__)

_lowercase      :      Dict[Optional[str], Type[Formatter]]            =					{}
_lowercase      :      Dict[Optional[str], str]            =					{}
_lowercase      :      Dict[Optional[str], Exception]            =					{}


def 				lowerCamelCase__				(	A       :      type				,       A       :      Optional[str]				,       A       :      Optional[List[str]] = None				,       ):




						'''simple docstring'''






						UpperCAmelCase					    =     aliases if aliases is not None else []
						if format_type in _FORMAT_TYPES:
												logger.warning(
												    f"""Overwriting format type '{format_type}' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})"""					)
						UpperCAmelCase					    =     formatter_cls
						for alias in set(aliases + [format_type]					):
												if alias in _FORMAT_TYPES_ALIASES:
																		logger.warning(
																		    f"""Overwriting format type alias '{alias}' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})"""					)
												UpperCAmelCase					    =     format_type


def 				lowerCamelCase__				(	A       :      Exception				,       A       :      Optional[str]				,       A       :      Optional[List[str]] = None					):




						'''simple docstring'''






						UpperCAmelCase					    =     aliases if aliases is not None else []
						for alias in set(aliases + [format_type]					):
												UpperCAmelCase					    =     unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=["""python"""])
_register_formatter(ArrowFormatter, """arrow""", aliases=["""pa""", """pyarrow"""])
_register_formatter(NumpyFormatter, """numpy""", aliases=["""np"""])
_register_formatter(PandasFormatter, """pandas""", aliases=["""pd"""])
_register_formatter(CustomFormatter, """custom""")

if config.TORCH_AVAILABLE:
	from .torch_formatter import TorchFormatter

	_register_formatter(TorchFormatter, """torch""", aliases=["""pt""", """pytorch"""])
else:
	_lowercase      :      List[str]            =					ValueError("""PyTorch needs to be installed to be able to return PyTorch tensors.""")
	_register_unavailable_formatter(_torch_error, """torch""", aliases=["""pt""", """pytorch"""])

if config.TF_AVAILABLE:
	from .tf_formatter import TFFormatter

	_register_formatter(TFFormatter, """tensorflow""", aliases=["""tf"""])
else:
	_lowercase      :      List[Any]            =					ValueError("""Tensorflow needs to be installed to be able to return Tensorflow tensors.""")
	_register_unavailable_formatter(_tf_error, """tensorflow""", aliases=["""tf"""])

if config.JAX_AVAILABLE:
	from .jax_formatter import JaxFormatter

	_register_formatter(JaxFormatter, """jax""", aliases=[])
else:
	_lowercase      :      List[str]            =					ValueError("""JAX needs to be installed to be able to return JAX arrays.""")
	_register_unavailable_formatter(_jax_error, """jax""", aliases=[])


def 				lowerCamelCase__				(	A       :      Optional[str]					):




						'''simple docstring'''






						if format_type in _FORMAT_TYPES_ALIASES:
												return _FORMAT_TYPES_ALIASES[format_type]
						else:
												return format_type




def 				lowerCamelCase__				(	A       :      Optional[str]				,       **A       :      int					):




						'''simple docstring'''






						UpperCAmelCase					    =     get_format_type_from_alias(A					)
						if format_type in _FORMAT_TYPES:
												return _FORMAT_TYPES[format_type](**A					)
						if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
												raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
						else:
												raise ValueError(
												    f"""Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None					)}, but got '{format_type}'"""					)









'''simple docstring'''



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


_lowercase      :      int            =					logging.get_logger(__name__)

_lowercase      :      Optional[Any]            =					{"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}






class 	UpperCamelCase__(       lowerCAmelCase	):
				__magic_name__    :				Union[str, Any]  		=	"openai-gpt"
				__magic_name__    :				Optional[int]  		=	{
				    "max_position_embeddings": "n_positions",
				    "hidden_size": "n_embd",
				    "num_attention_heads": "n_head",
				    "num_hidden_layers": "n_layer",
				}




				def __init__(		self      :			Optional[int]				,   lowerCAmelCase      :			Optional[Any]=40478				,   lowerCAmelCase      :			str=512				,   lowerCAmelCase      :			List[Any]=768				,   lowerCAmelCase      :			Tuple=12				,   lowerCAmelCase      :			int=12				,   lowerCAmelCase      :			List[str]="gelu"				,   lowerCAmelCase      :			List[str]=0.1				,   lowerCAmelCase      :			List[Any]=0.1				,   lowerCAmelCase      :			Dict=0.1				,   lowerCAmelCase      :			Tuple=1E-5				,   lowerCAmelCase      :			Tuple=0.02				,   lowerCAmelCase      :			Optional[int]="cls_index"				,   lowerCAmelCase      :			Dict=True				,   lowerCAmelCase      :			Optional[int]=None				,   lowerCAmelCase      :			Dict=True				,   lowerCAmelCase      :			int=0.1				,   **lowerCAmelCase      :			Optional[int]				,   )->					str:

										"""simple docstring"""




										UpperCAmelCase					    =     vocab_size
										UpperCAmelCase					    =     n_positions
										UpperCAmelCase					    =     n_embd
										UpperCAmelCase					    =     n_layer
										UpperCAmelCase					    =     n_head
										UpperCAmelCase					    =     afn
										UpperCAmelCase					    =     resid_pdrop
										UpperCAmelCase					    =     embd_pdrop
										UpperCAmelCase					    =     attn_pdrop
										UpperCAmelCase					    =     layer_norm_epsilon
										UpperCAmelCase					    =     initializer_range
										UpperCAmelCase					    =     summary_type
										UpperCAmelCase					    =     summary_use_proj
										UpperCAmelCase					    =     summary_activation
										UpperCAmelCase					    =     summary_first_dropout
										UpperCAmelCase					    =     summary_proj_to_labels
										super().__init__(**lowerCAmelCase				)





