docstr: Test a dataset that represents the slices from a tuple of tensors.
docstr_tok: ["Test","a","dataset","that","represents","the","slices","from","a","tuple","of","tensors","."]
code: def testFromTensorSlices(self):
      """Test a dataset that represents the slices from a tuple of tensors."""
      components = (
          np.tile(np.array([[1], [2], [3], [4]]), 20),
          np.tile(np.array([[12], [13], [14], [15]]), 22),
          np.array([37.0, 38.0, 39.0, 40.0]),
      )
  
      dataset = dataset_ops.Dataset.from_tensor_slices(components)
      get_next = self.getNext(dataset)
  
      self.assertEqual(
          [c.shape[1:] for c in components],
          [
              shape
              for shape in dataset_ops.get_legacy_output_shapes(dataset)
          ],
      )
  
      for i in range(4):
          results = self.evaluate(get_next())
          for component, result_component in zip(components, results):
              self.assertAllEqual(component[i], result_component)
      with self.assertRaises(errors.OutOfRangeError):
          results = self.evaluate(get_next())
  
imports: import collections
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import random_access
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the FromTensorSlicesTest obj's underlying member method code with example usage: obj.testFromTensorSlices() without return types