message: Increase the dataset size so that out of range error is not encountered when running with 2gpu
diff: @@ -52,8 +52,8 @@ class DatasetCreatorModelFitTest(test_base.DatasetCreatorModelFitTestBase):
  self.assertEqual(model.optimizer.iterations, 100)
  def testModelFitWithNumpyData(self, strategy):
  - x = np.random.rand(10, 10)
  - y = np.random.rand(10, 1)
  + x = np.random.rand(100, 10)
  + y = np.random.rand(100, 1)
  model = self._model_fit(
  strategy,
  x=x,
  @@ -64,8 +64,8 @@ class DatasetCreatorModelFitTest(test_base.DatasetCreatorModelFitTestBase):
  self.assertEqual(model.optimizer.iterations, 100)
  def testModelFitWithTensorData(self, strategy):
  - x = random_ops.random_uniform((10, 10))
  - y = random_ops.random_uniform((10,))
  + x = random_ops.random_uniform((100, 10))
  + y = random_ops.random_uniform((100,))
  model = self._model_fit(
  strategy,
  x=x,
  @@ -100,8 +100,8 @@ class DatasetCreatorModelFitTest(test_base.DatasetCreatorModelFitTestBase):
  self.assertGreaterEqual(self._accuracy_metric.result(), 0.0)
  def testModelEvaluateWithNumpyData(self, strategy):
  - x = np.random.rand(10, 10)
  - y = np.random.rand(10, 1)
  + x = np.random.rand(100, 10)
  + y = np.random.rand(100, 1)
  self._model_evaluate(
  strategy,
  x=x,
  @@ -111,8 +111,8 @@ class DatasetCreatorModelFitTest(test_base.DatasetCreatorModelFitTestBase):
  self.assertGreaterEqual(self._accuracy_metric.result(), 0.0)
  def testModelEvaluateWithTensorData(self, strategy):
  - x = random_ops.random_uniform((10, 10))
  - y = random_ops.random_uniform((10,))
  + x = random_ops.random_uniform((100, 10))
  + y = random_ops.random_uniform((100,))
  self._model_evaluate(
  strategy,
  x=x,
  