code: def convert_all(
      inputs: Union[Dict[str, DATA_TYPE], Sequence[DATA_TYPE]],
      types: Union[Dict[str, str], Sequence[str], str],
      dtypes: Union[Dict[str, DTYPE], Sequence[DTYPE], DTYPE] = None,
  ):
      """
      Convert all input tf.Tensor/np.ndarray to specified format.
  
      Usage:
      ```
      x = np.random.random((10, 10))
      y = np.random.random((10, 10))
      x, y = convert_all([x, y], types="tf", dtypes=tf.float32)
  
      x = np.random.random((10, 10))
      y = np.random.random((10, 10))
      x, y = convert_all({"x":x, "y": y}, types="tf", dtypes={"x": tf.float32, "y": tf.bfloat16})
  
      x = np.random.random((10, 10))
      y = tf.random.normal((10, 10))
      x, y = convert_all([x, y], types=["tf", "numpy"], dtypes=[tf.float32, np.float32])
      ```
  
      :param input_: A list/dict of tf.Tensor/np.ndarray to convert.
      :param type_: (A list/dict of) target type, "tf" means tf.Tensor, "numpy" means np.ndarray.
      :param dtype_: (A list/dict of) target dtype.
      :return The convert result.
      """
      if isinstance(inputs, Sequence):
          return _convert_list(inputs, types, dtypes)  # type: ignore
      else:
          return _convert_dict(inputs, types, dtypes)
  
file_path: BigDL/python/nano/src/bigdl/nano/utils/tf/data.py
imports: from typing import Union, Optional, Sequence, Dict
  import numpy
  import tensorflow
  from bigdl.nano.utils.common import invalidInputError
label_desc: Use image node_id 1 for calling a global function with example usage: convert_all(inputs, types, dtypes) and returns: _convert_list, _convert_dict