code: def test_adapt_dict_of_np_arrays_as_x() -> None:
      adapted = keras._adapt_data_from_fit_args(
          x={"k1": np.arange(0, 100), "k2": np.arange(100, 200)},
          y=np.arange(200, 300),
          sample_weight=None,
          batch_size=16,
      )
      assert isinstance(adapted, Sequence)
      assert len(adapted) == 7
      batch_x, batch_y = adapted[3]
      assert np.array_equal(batch_x["k1"], np.arange(48, 64))
      assert np.array_equal(batch_x["k2"], np.arange(148, 164))
      assert np.array_equal(batch_y, np.arange(248, 264))
  
imports: from typing import Tuple
  import numpy
  import pytest
  from tensorflow.keras.utils import Sequence
  import determined
  from determined import keras
  from determined.common import check
  from tests.experiment import tf_utils
label_desc: Use image node_id 7 for calling a global function with example usage: test_adapt_dict_of_np_arrays_as_x() without return types