class_docstr: Generic exception thrown to surface failure information about external-facing operations.
  The error message associated with this exception may be exposed to clients in HTTP responses
  for debugging purposes. If the error text is sensitive, raise a generic `Exception` object
  instead.
class_docstr_tok: ["Generic","exception","thrown","to","surface","failure","information","about","external-facing","operations",".","The","error","message","associated","with","this","exception","may","be","exposed","to","clients","in","HTTP","responses","for","debugging","purposes",".","If","the","error","text","is","sensitive",",","raise","a","generic","`","Exception","`","object","instead","."]
docstr: Args:
      message: The message or exception describing the error that occurred. This will be
          included in the exception's serialized JSON representation.
      error_code: An appropriate error code for the error that occurred; it will be
          included in the exception's serialized JSON representation. This should
          be one of the codes listed in the `mlflow.protos.databricks_pb2` proto.
      kwargs: Additional key-value pairs to include in the serialized JSON representation
          of the MlflowException.
docstr_tok: ["Args",":","message",":","The","message","or","exception","describing","the","error","that","occurred",".","This","will","be","included","in","the","exception","'s","serialized","JSON","representation",".","error_code",":","An","appropriate","error","code","for","the","error","that","occurred",";","it","will","be","included","in","the","exception","'s","serialized","JSON","representation",".","This","should","be","one","of","the","codes","listed","in","the","`","mlflow.protos.databricks_pb2","`","proto",".","kwargs",":","Additional","key-value","pairs","to","include","in","the","serialized","JSON","representation","of","the","MlflowException","."]
code: def __init__(self, message, error_code=INTERNAL_ERROR, **kwargs):
      """
      Args:
          message: The message or exception describing the error that occurred. This will be
              included in the exception's serialized JSON representation.
          error_code: An appropriate error code for the error that occurred; it will be
              included in the exception's serialized JSON representation. This should
              be one of the codes listed in the `mlflow.protos.databricks_pb2` proto.
          kwargs: Additional key-value pairs to include in the serialized JSON representation
              of the MlflowException.
      """
      try:
          self.error_code = ErrorCode.Name(error_code)
      except (ValueError, TypeError):
          self.error_code = ErrorCode.Name(INTERNAL_ERROR)
      message = str(message)
      self.message = message
      self.json_kwargs = kwargs
      super().__init__(message)
  
imports: import json
  from mlflow.protos.databricks_pb2 import ABORTED, ALREADY_EXISTS, BAD_REQUEST, CANCELLED, CUSTOMER_UNAUTHORIZED, DATA_LOSS, DEADLINE_EXCEEDED, ENDPOINT_NOT_FOUND, INTERNAL_ERROR, INVALID_PARAMETER_VALUE, INVALID_STATE, NOT_FOUND, NOT_IMPLEMENTED, PERMISSION_DENIED, REQUEST_LIMIT_EXCEEDED, RESOURCE_ALREADY_EXISTS, RESOURCE_CONFLICT, RESOURCE_DOES_NOT_EXIST, RESOURCE_EXHAUSTED, TEMPORARILY_UNAVAILABLE, UNAUTHENTICATED, ErrorCode
label_desc: Use image node_id 1 to create a new MlflowException object from inherited base classes: Exception with example: obj = MlflowException(message, error_code)