




'''simple docstring'''






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


lowercase						:   Union[str, Any]      						=							logging.get_logger(__name__)

lowercase						:   Union[str, Any]      						=							{
    '''facebook/regnet-y-040''': '''https://huggingface.co/facebook/regnet-y-040/blob/main/config.json''',
}

class 	SCREAMING_SNAKE_CASE_		(							lowerCamelCase_					):
 __snake_case						:  List[str]       =   "regnet"
 __snake_case						:  Any       =   ["x", "y"]



 def __init__(	self ,		A=3 ,		A=32 ,		A=[128, 192, 512, 1088] ,		A=[2, 6, 12, 2] ,		A=64 ,		A="y" ,		A="relu" ,		**A ,		):






        '''simple docstring'''




        super().__init__(**A			)
        if layer_type not in self.layer_types:
               raise ValueError(f"""layer_type={layer_type} is not one of {','.join(self.layer_types			)}"""			)
        lowercase	:		Any    =   num_channels
        lowercase	:		List[Any]    =   embedding_size
        lowercase	:		Optional[int]    =   hidden_sizes
        lowercase	:		int    =   depths
        lowercase	:		List[Any]    =   groups_width
        lowercase	:		int    =   layer_type
        lowercase	:		Dict    =   hidden_act
        # always downsample in the first stage
        lowercase	:		str    =   True










'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


lowercase						:   int      						=							{
    '''configuration_xlm_prophetnet''': ['''XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMProphetNetConfig'''],
}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase						:   Any      						=							['''XLMProphetNetTokenizer''']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase						:   Tuple      						=							[
          '''XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''XLMProphetNetDecoder''',
          '''XLMProphetNetEncoder''',
          '''XLMProphetNetForCausalLM''',
          '''XLMProphetNetForConditionalGeneration''',
          '''XLMProphetNetModel''',
          '''XLMProphetNetPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_xlm_prophetnet import (
                XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                XLMProphetNetDecoder,
                XLMProphetNetEncoder,
                XLMProphetNetForCausalLM,
                XLMProphetNetForConditionalGeneration,
                XLMProphetNetModel,
                XLMProphetNetPreTrainedModel,
            )

else:
      import sys

      lowercase						:   Optional[Any]      						=							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




