code: def make_array(self, array_type, shape, dtype="float32"):
      if array_type == "np":
          return np.ones(shape, dtype=dtype)
      elif array_type == "tf":
          return tf.ones(shape, dtype=dtype)
      elif array_type == "backend":
          if backend.backend() == "jax":
              import jax
  
              return jax.numpy.ones(shape, dtype=dtype)
          elif backend.backend() == "torch":
              import torch
  
              return torch.tensor(np.ones(shape, dtype=dtype))
          else:
              return tf.ones(shape, dtype=dtype)
      elif array_type == "pandas":
          return pandas.DataFrame(np.ones(shape, dtype=dtype))
  
file_path: keras/keras/trainers/data_adapters/array_data_adapter_test.py
imports: import numpy
  import pandas
  import pytest
  import tensorflow
  from absl.testing import parameterized
  from keras import backend
  from keras import testing
  from keras.trainers.data_adapters import array_data_adapter
label_desc: Use image node_id 1 for calling the TestArrayDataAdapter obj's underlying member method code with example usage: obj.make_array(array_type, shape, dtype) and returns: np, tf, jax, pandas, torch, tf