





import inspect
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase_     							= """src/transformers"""


# This is to make sure the transformers module imported is the one in the repo.
UpperCAmelCase_     							= direct_transformers_import(PATH_TO_TRANSFORMERS)

UpperCAmelCase_     							= transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
UpperCAmelCase_     							= re.compile(R'\[(.+?)\]\((https://huggingface\.co/.+?)\)')


UpperCAmelCase_     							= {
    """DecisionTransformerConfig""",
    """EncoderDecoderConfig""",
    """MusicgenConfig""",
    """RagConfig""",
    """SpeechEncoderDecoderConfig""",
    """TimmBackboneConfig""",
    """VisionEncoderDecoderConfig""",
    """VisionTextDualEncoderConfig""",
    """LlamaConfig""",
}




def 		lowerCAmelCase_    (  __UpperCAmelCase:			int      )      ->	List[str]:
    UpperCamelCase__							:				List[str]          =      None

    # source code of `config_class`
    UpperCamelCase__							:				str          =      inspect.getsource(__UpperCAmelCase      )
    UpperCamelCase__							:				Optional[Any]          =      _re_checkpoint.findall(__UpperCAmelCase      )

    # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
    # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
    for ckpt_name, ckpt_link in checkpoints:
        # allow the link to end with `/`
        if ckpt_link.endswith('''/'''      ):
            UpperCamelCase__							:				str          =      ckpt_link[:-1]

        # verify the checkpoint name corresponds to the checkpoint link
        UpperCamelCase__							:				Dict          =      f"https://huggingface.co/{ckpt_name}"
        if ckpt_link == ckpt_link_from_name:
            UpperCamelCase__							:				Dict          =      ckpt_name
            break

    return checkpoint




def 		lowerCAmelCase_    (  )      ->	List[Any]:
    UpperCamelCase__							:				Optional[Any]          =      []

    for config_class in list(CONFIG_MAPPING.values()      ):
        # Skip deprecated models
        if "models.deprecated" in config_class.__module__:
            continue
        UpperCamelCase__							:				str          =      get_checkpoint_from_config_class(__UpperCAmelCase      )

        UpperCamelCase__							:				List[str]          =      config_class.__name__
        if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
            configs_without_checkpoint.append(__UpperCAmelCase      )

    if len(__UpperCAmelCase      ) > 0:
        UpperCamelCase__							:				Optional[int]          =      '''\n'''.join(sorted(__UpperCAmelCase      )      )
        raise ValueError(f"The following configurations don't contain any valid checkpoint:\n{message}"      )


if __name__ == "__main__":
  check_config_docstrings_have_checkpoints()


'''simple docstring'''

from typing import TYPE_CHECKING

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


__a: Dict          =   {
    """configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
    """tokenization_ctrl""": ["""CTRLTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a: int          =   [
      """CTRL_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """CTRLForSequenceClassification""",
      """CTRLLMHeadModel""",
      """CTRLModel""",
      """CTRLPreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a: int          =   [
      """TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFCTRLForSequenceClassification""",
      """TFCTRLLMHeadModel""",
      """TFCTRLModel""",
      """TFCTRLPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
  from .tokenization_ctrl import CTRLTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_ctrl import (
        CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
        CTRLForSequenceClassification,
        CTRLLMHeadModel,
        CTRLModel,
        CTRLPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_ctrl import (
        TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFCTRLForSequenceClassification,
        TFCTRLLMHeadModel,
        TFCTRLModel,
        TFCTRLPreTrainedModel,
    )

else:
  import sys

  __a: Dict          =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

