class_docstr: Registry of dataset registries.
  
  Each namespace is associated with one or more registers. Those registers can
  be any type of register, e.g. code on Github or datasets stored somewhere.
  
  Attributes:
    namespace_config: config where to find the datasets of a namespace.
    registers_per_namespace: per namespace a list of registers it consists of.
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docstr: Returns all available registers for a given namespace, if any.
  
  Args:
    name: str, the namespace's name.
  
  Raises:
    DatasetNotFound error if the namespace is not found.
docstr_tok: ["Returns","all","available","registers","for","a","given","namespace",",","if","any",".","Args",":","name",":","str",",","the","namespace","'s","name",".","Raises",":","DatasetNotFound","error","if","the","namespace","is","not","found","."]
code: def _get_registers(
      self, name: naming.DatasetName
  ) -> List[register_base.BaseRegister]:
      """Returns all available registers for a given namespace, if any.
  
      Args:
        name: str, the namespace's name.
  
      Raises:
        DatasetNotFound error if the namespace is not found.
      """
      if not self.has_namespace(name.namespace):
          error_msg = f"\nNamespace {name.namespace} not found. "
          error_msg += (
              "Note that the namespace should be one of: "
              f"{sorted(self.registers_per_namespace.keys())}.\n"
          )
          close_matches = difflib.get_close_matches(
              name.namespace, self.registers_per_namespace, n=1
          )
          if close_matches:
              error_msg += f"Did you mean: {name.namespace} -> {close_matches[0]} ?\n"
          raise registered.DatasetNotFoundError(error_msg)
      return self.registers_per_namespace[name.namespace]
  
imports: import dataclasses
  import difflib
  import functools
  import os
  from typing import Any, Iterable, List, Mapping, Type
  from absl import logging
  from etils import epath
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import github_api
  from tensorflow_datasets.core import naming
  from tensorflow_datasets.core import registered
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.community import register_base
  from tensorflow_datasets.core.community import register_package
  from tensorflow_datasets.core.community import register_path
  from tensorflow_datasets.core.utils import gcs_utils
  import toml
label_desc: Use image node_id 8 for calling the DatasetRegistry obj's underlying member method code with example usage: obj._get_registers(name) and returns: self