message: Fix partial batch TPU predict test with numpy inputs.
diff: @@ -727,14 +727,14 @@ class TestDistributionStrategyWithNumpyArrays(test.TestCase,
  cpu_model = get_model()
  cpu_model.compile(optimizer, loss)
  - inputs = np.zeros((10, 3), dtype=np.float32)
  + inputs = np.random.random((10, 3)).astype(np.float32)
  # As sample size is 10, we batch by 4 so that the last batch is
  # a partial batch. Also `predict()` using numpy array as inputs without
  # distribution strategy uses entire sample as a single batch. As so,
  # we remove parameters `batch_size` and `steps`.
  - predict_ground_truth = cpu_model.predict(inputs)
  cpu_model.set_weights(model_with_ds_strategy.get_weights())
  + predict_ground_truth = cpu_model.predict(inputs)
  self.assertAllClose(
  model_with_ds_strategy.predict(inputs, batch_size=4, steps=3),
  predict_ground_truth,
  @@ -1180,7 +1180,7 @@ class TestDistributionStrategyWithDatasets(test.TestCase,
  cpu_model = get_model()
  cpu_model.compile(optimizer, loss)
  - inputs = np.zeros((10, 3), dtype=np.float32)
  + inputs = np.random.random((10, 3)).astype(np.float32)
  dataset = dataset_ops.Dataset.from_tensor_slices((inputs))
  # As sample size is 10, we batch by 4 so that the last batch is
  