CLN: remove tf_test_util and keras.test_util (#81)

* CLN: remove tf_test_util and keras.test_util

Author: facaiy

tensorflow_addons/activations/BUILD

@@ -17,7 +17,7 @@ py_library(
 
 py_test(
     name = "sparsemax_py_test",
-    size = "small",
+    size = "medium",
     srcs = [
         "python/sparsemax_test.py",
     ],

tensorflow_addons/activations/README.md

@@ -19,7 +19,9 @@ must:
 #### Testing Requirements
  * Simple unittests that demonstrate the layer is behaving as expected.
  * When applicable, run all unittests with TensorFlow's
-  `@run_all_in_graph_and_eager_modes` decorator.
+   `@run_in_graph_and_eager_modes` (for test method)
+   or `run_all_in_graph_and_eager_modes` (for TestCase subclass)
+   decorator.
  * Add a `py_test` to this sub-package's BUILD file.
 
 #### Documentation Requirements

tensorflow_addons/custom_ops/README.md

@@ -20,7 +20,9 @@ must:
  * Simple unittests that demonstrate the custom op is behaving as
     expected.
  * When applicable, run all unittests with TensorFlow's
-  `@run_all_in_graph_and_eager_modes` decorator.
+   `@run_in_graph_and_eager_modes` (for test method)
+   or `run_all_in_graph_and_eager_modes` (for TestCase subclass)
+   decorator.
  * Add a `py_test` to the custom-op's BUILD file.
 
 #### Documentation Requirements

tensorflow_addons/custom_ops/image/BUILD

@@ -30,14 +30,15 @@ py_library(
     ]),
     data = [
         ":python/_image_ops.so",
+        "//tensorflow_addons/utils:utils_py",
     ],
     srcs_version = "PY2AND3",
 )
 
 # TODO: use cuda_py_test later.
 py_test(
     name = "transform_ops_test",
-    size = "small",
+    size = "medium",
     srcs = [
         "python/transform_test.py",
     ],

tensorflow_addons/custom_ops/image/python/transform.py

@@ -121,6 +121,7 @@ def transform(images,
             return output
 
 
+@tf.function
 def compose_transforms(*transforms):
     """Composes the transforms tensors.
 
@@ -144,6 +145,7 @@ def compose_transforms(*transforms):
         return matrices_to_flat_transforms(composed)
 
 
+@tf.function
 def flat_transforms_to_matrices(transforms):
     """Converts projective transforms to affine matrices.
 
@@ -176,6 +178,7 @@ def flat_transforms_to_matrices(transforms):
             tf.constant([-1, 3, 3]))
 
 
+@tf.function
 def matrices_to_flat_transforms(transform_matrices):
     """Converts affine matrices to projective transforms.
 
@@ -208,6 +211,7 @@ def matrices_to_flat_transforms(transform_matrices):
         return transforms[:, :8]
 
 
+@tf.function
 def angles_to_projective_transforms(angles,
                                     image_height,
                                     image_width,

tensorflow_addons/custom_ops/image/python/transform_test.py

@@ -21,9 +21,9 @@
 import numpy as np
 import tensorflow as tf
 
-from tensorflow.python.framework import test_util as tf_test_util
 from tensorflow.python.ops import gradient_checker
 from tensorflow_addons.custom_ops.image.python import transform as transform_ops
+from tensorflow_addons.utils.python import test_utils
 
 _DTYPES = set([
     tf.dtypes.uint8, tf.dtypes.int32, tf.dtypes.int64, tf.dtypes.float16,
@@ -32,7 +32,7 @@
 
 
 class ImageOpsTest(tf.test.TestCase):
-    @tf_test_util.run_all_in_graph_and_eager_modes
+    @test_utils.run_in_graph_and_eager_modes
     def test_compose(self):
         for dtype in _DTYPES:
             image = tf.constant(
@@ -51,7 +51,7 @@ def test_compose(self):
                 [[0, 0, 0, 0], [0, 1, 0, 1], [0, 1, 0, 1], [0, 1, 1, 1]],
                 image_transformed)
 
-    @tf_test_util.run_all_in_graph_and_eager_modes
+    @test_utils.run_in_graph_and_eager_modes
     def test_extreme_projective_transform(self):
         for dtype in _DTYPES:
             image = tf.constant(
@@ -64,7 +64,6 @@ def test_extreme_projective_transform(self):
                 [[1, 0, 0, 0], [0, 0, 0, 0], [1, 0, 0, 0], [0, 0, 0, 0]],
                 image_transformed)
 
-    @tf_test_util.run_all_in_graph_and_eager_modes
     def test_transform_static_output_shape(self):
         image = tf.constant([[1., 2.], [3., 4.]])
         result = transform_ops.transform(
@@ -118,7 +117,7 @@ def _test_grad_different_shape(self, input_shape, output_shape):
             self.assertLess(left_err, 1e-10)
 
     # TODO: switch to TF2 later.
-    @tf_test_util.run_deprecated_v1
+    @test_utils.run_deprecated_v1
     def test_grad(self):
         self._test_grad([16, 16])
         self._test_grad([4, 12, 12])
@@ -127,16 +126,15 @@ def test_grad(self):
         self._test_grad_different_shape([4, 12, 3], [8, 24, 3])
         self._test_grad_different_shape([3, 4, 12, 3], [3, 8, 24, 3])
 
-    @tf_test_util.run_all_in_graph_and_eager_modes
+    @test_utils.run_in_graph_and_eager_modes
     def test_transform_data_types(self):
         for dtype in _DTYPES:
             image = tf.constant([[1, 2], [3, 4]], dtype=dtype)
-            with self.test_session(use_gpu=True):
-                self.assertAllEqual(
-                    np.array([[4, 4], [4, 4]]).astype(dtype.as_numpy_dtype()),
-                    transform_ops.transform(image, [1] * 8))
+            self.assertAllEqual(
+                np.array([[4, 4], [4, 4]]).astype(dtype.as_numpy_dtype()),
+                transform_ops.transform(image, [1] * 8))
 
-    @tf_test_util.run_all_in_graph_and_eager_modes
+    @test_utils.run_in_graph_and_eager_modes
     def test_transform_eager(self):
         image = tf.constant([[1., 2.], [3., 4.]])
         self.assertAllEqual(

tensorflow_addons/custom_ops/text/BUILD

@@ -27,6 +27,7 @@ py_library(
     ]),
     data = [
         ":python/_skip_gram_ops.so",
+        "//tensorflow_addons/utils:utils_py",
     ],
     srcs_version = "PY2AND3",
 )

tensorflow_addons/custom_ops/text/python/skip_gram_ops_test.py

@@ -22,12 +22,12 @@
 import os
 import tensorflow as tf
 
-from tensorflow.python.framework import test_util as tf_test_util
 from tensorflow.python.framework import random_seed
 from tensorflow.python.ops import lookup_ops
 from tensorflow.python.platform import test
 from tensorflow_addons.custom_ops import text
 from tensorflow_addons.custom_ops.text.python import skip_gram_ops
+from tensorflow_addons.utils.python import test_utils
 
 
 class SkipGramOpsTest(tf.test.TestCase):
@@ -232,7 +232,7 @@ def test_skip_gram_sample_non_string_input(self):
         self.assertAllEqual(expected_tokens, tokens)
         self.assertAllEqual(expected_labels, labels)
 
-    @tf_test_util.run_deprecated_v1
+    @test_utils.run_deprecated_v1
     def test_skip_gram_sample_errors_v1(self):
         """Tests various errors raised by skip_gram_sample()."""
         # input_tensor must be of rank 1.

tensorflow_addons/layers/README.md

@@ -20,8 +20,10 @@ must:
 #### Testing Requirements
  * Simple unittests that demonstrate the layer is behaving as expected.
  * When applicable, run all unittests with TensorFlow's
-  `@run_all_in_graph_and_eager_modes` decorator.
- * Run `keras.testing_utils.layer_test` on the layer.
+   `@run_in_graph_and_eager_modes` (for test method)
+   or `run_all_in_graph_and_eager_modes` (for TestCase subclass)
+   decorator.
+ * Run `layer_test` on the layer.
  * Add a `py_test` to this sub-package's BUILD file.
 
 #### Documentation Requirements

tensorflow_addons/layers/python/maxout_test.py

@@ -21,25 +21,26 @@
 import numpy as np
 import tensorflow as tf
 
-from tensorflow.python.keras import testing_utils as keras_test_util
 from tensorflow_addons.layers.python.maxout import Maxout
+from tensorflow_addons.utils.python import test_utils
 
 
+@test_utils.run_all_in_graph_and_eager_modes
 class MaxOutTest(tf.test.TestCase):
     def test_simple(self):
-        keras_test_util.layer_test(
+        test_utils.layer_test(
             Maxout, kwargs={'num_units': 3}, input_shape=(5, 4, 2, 18))
 
     def test_nchw(self):
-        keras_test_util.layer_test(
+        test_utils.layer_test(
             Maxout,
             kwargs={
                 'num_units': 4,
                 'axis': 1
             },
             input_shape=(2, 20, 3, 6))
 
-        keras_test_util.layer_test(
+        test_utils.layer_test(
             Maxout,
             kwargs={
                 'num_units': 4,
@@ -49,21 +50,21 @@ def test_nchw(self):
 
     def test_unknown(self):
         inputs = np.random.random((5, 4, 2, 18)).astype('float32')
-        keras_test_util.layer_test(
+        test_utils.layer_test(
             Maxout,
             kwargs={'num_units': 3},
             input_shape=(5, 4, 2, None),
             input_data=inputs)
 
-        keras_test_util.layer_test(
+        test_utils.layer_test(
             Maxout,
             kwargs={'num_units': 3},
             input_shape=(None, None, None, None),
             input_data=inputs)
 
     def test_invalid_shape(self):
         with self.assertRaisesRegexp(ValueError, r'number of features'):
-            keras_test_util.layer_test(
+            test_utils.layer_test(
                 Maxout, kwargs={'num_units': 3}, input_shape=(5, 4, 2, 7))