class_docstr: Adapter for array-like objects, e.g. TF/JAX Tensors, NumPy arrays.
class_docstr_tok: ["Adapter","for","array-like","objects",",","e.g",".","TF\/JAX","Tensors",",","NumPy","arrays","."]
code: def get_numpy_iterator(self):
      inputs = self._inputs
      if self._shuffle:
          inputs = data_adapter_utils.sync_shuffle(
              inputs, num_samples=self._num_samples
          )
      for i in range(self._size):
          start, stop = i * self._batch_size, (i + 1) * self._batch_size
          yield tree.map_structure(lambda x: x[start:stop], inputs)
  
file_path: keras/keras/trainers/data_adapters/array_data_adapter.py
imports: import math
  import numpy
  import tree
  from keras import backend
  from keras.trainers.data_adapters import data_adapter_utils
  from keras.trainers.data_adapters.data_adapter import DataAdapter
  from keras.utils.nest import lists_to_tuples
label_desc: Use image node_id 2 for calling the ArrayDataAdapter obj's underlying member method code with example usage: obj.get_numpy_iterator() without return types