






# 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


__UpperCAmelCase								=						logging.get_logger(__name__)

__UpperCAmelCase								=						{}
__UpperCAmelCase								=						{}
__UpperCAmelCase								=						{}




def      lowercase__      (     __snake_case    :							type     ,       __snake_case    :							Optional[str]     ,       __snake_case    :							Optional[List[str]] = None     ,       ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[Any]            =						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_    :      Dict            =						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_    :      int            =						format_type




def      lowercase__      (     __snake_case    :							Exception     ,       __snake_case    :							Optional[str]     ,       __snake_case    :							Optional[List[str]] = None  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Tuple            =						aliases if aliases is not None else []
					for alias in set(aliases + [format_type]  ):
										UpperCAmelCase_    :      Union[str, Any]            =						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:
		__UpperCAmelCase								=						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:
		__UpperCAmelCase								=						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:
		__UpperCAmelCase								=						ValueError('JAX needs to be installed to be able to return JAX arrays.')
		_register_unavailable_formatter(_jax_error, 'jax', aliases=[])




def      lowercase__      (     __snake_case    :							Optional[str]  ):


					'''simple docstring'''


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






def      lowercase__      (     __snake_case    :							Optional[str]     ,       **__snake_case    :							Optional[int]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      List[str]            =						get_format_type_from_alias(__snake_case  )
					if format_type in _FORMAT_TYPES:
										return _FORMAT_TYPES[format_type](**__snake_case  )
					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_		       =  logging.get_logger(__name__)

lowercase_		       =  {
    "vinvino02/glpn-kitti": "https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}






class __A			(  A						):



 '''simple docstring'''







 __lowerCamelCase    :       str          =       'glpn'



 def __init__(self ,   A=3 ,   A=4 ,   A=[2, 2, 2, 2] ,   A=[8, 4, 2, 1] ,   A=[32, 64, 160, 256] ,   A=[7, 3, 3, 3] ,   A=[4, 2, 2, 2] ,   A=[1, 2, 5, 8] ,   A=[4, 4, 4, 4] ,   A="gelu" ,   A=0.0 ,   A=0.0 ,   A=0.02 ,   A=0.1 ,   A=1E-6 ,   A=64 ,   A=10 ,   A=-1 ,   **A ,   )    ->     Any:


      """simple docstring"""



      super().__init__(**A       )

      _a      =  num_channels
      _a      =  num_encoder_blocks
      _a      =  depths
      _a      =  sr_ratios
      _a      =  hidden_sizes
      _a      =  patch_sizes
      _a      =  strides
      _a      =  mlp_ratios
      _a      =  num_attention_heads
      _a      =  hidden_act
      _a      =  hidden_dropout_prob
      _a      =  attention_probs_dropout_prob
      _a      =  initializer_range
      _a      =  drop_path_rate
      _a      =  layer_norm_eps
      _a      =  decoder_hidden_size
      _a      =  max_depth
      _a      =  head_in_index



