Moved test out of run_all_in_graph_and_eager_mode in softshrink. (ten…

…sorflow#1405)

* Moved test out of run_all_in_graph_and_eager_mode in softshrink.

See tensorflow#1328

* Small fix.

tensorflow_addons/activations/softshrink_test.py

@@ -16,7 +16,6 @@
 import sys
 
 import pytest
-from absl.testing import parameterized
 
 import numpy as np
 import tensorflow as tf
@@ -48,21 +47,6 @@ def test_softshrink(dtype):
     )
 
 
-@test_utils.run_all_in_graph_and_eager_modes
-class SoftshrinkTest(tf.test.TestCase, parameterized.TestCase):
-    @parameterized.named_parameters(("float32", np.float32), ("float64", np.float64))
-    def test_theoretical_gradients(self, dtype):
-        # Only test theoretical gradients for float32 and float64
-        # because of the instability of float16 while computing jacobian
-
-        # Softshrink is not continuous at `lower` and `upper`.
-        # Avoid these two points to make gradients smooth.
-        x = tf.constant([-2.0, -1.5, 0.0, 1.5, 2.0], dtype=dtype)
-
-        theoretical, numerical = tf.test.compute_gradient(softshrink, [x])
-        self.assertAllCloseAccordingToType(theoretical, numerical, atol=1e-4)
-
-
 @pytest.mark.parametrize("dtype", [np.float16, np.float32])
 def test_same_as_py_func(dtype):
     np.random.seed(1234)
@@ -89,5 +73,18 @@ def verify_funcs_are_equivalent(dtype):
     test_utils.assert_allclose_according_to_type(grad_native, grad_py)
 
 
+@pytest.mark.parametrize("dtype", [np.float32, np.float64])
+def test_theoretical_gradients(dtype):
+    # Only test theoretical gradients for float32 and float64
+    # because of the instability of float16 while computing jacobian
+
+    # Softshrink is not continuous at `lower` and `upper`.
+    # Avoid these two points to make gradients smooth.
+    x = tf.constant([-2.0, -1.5, 0.0, 1.5, 2.0], dtype=dtype)
+
+    theoretical, numerical = tf.test.compute_gradient(softshrink, [x])
+    test_utils.assert_allclose_according_to_type(theoretical, numerical, atol=1e-4)
+
+
 if __name__ == "__main__":
     sys.exit(pytest.main([__file__]))