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.
class_docstr_tok: ["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","."]
docstr: Loads the builder class for the given dataset.
docstr_tok: ["Loads","the","builder","class","for","the","given","dataset","."]
code: def builder(
      self,
      name: naming.DatasetName,
      **builder_kwargs: Any,
  ) -> dataset_builder.DatasetBuilder:
      """Loads the builder class for the given dataset."""
      registers = self._get_registers(name)
  
      # Typically there's only 1, so add special case so that more informative
      # exceptions are raised.
      if len(registers) == 1:
          return registers[0].builder(name, **builder_kwargs)
  
      if len(registers) > 1:
          raise ValueError(
              f"Namespace {name.namespace} has multiple registers! "
              f"This should not happen! Registers: {registers}"
          )
  
      raise registered.DatasetNotFoundError(
          f"Namespace {name.namespace} found with {len(registers)} registers, "
          f"but could not load dataset {name.name}."
      )
  
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 10 for calling the DatasetRegistry obj's underlying member method code with example usage: obj.builder(name) and returns: registers