Add a small test to cover the mlir generated Tanh GPU kernel.

This test is a first step towards being able to ensure that we don't
accidentally break the kernel generation.

PiperOrigin-RevId: 317269120
Change-Id: Iad6bdd7ab7e9fb819a478c947ba6294a191f1099

tensorflow/core/kernels/BUILD

@@ -4168,6 +4168,25 @@ tf_kernel_library(
     ]),
 )
 
+tf_cuda_cc_test(
+    name = "mlir_generated_op_gpu_tanh_test",
+    size = "small",
+    srcs = if_mlir_generated_gpu_kernels_enabled(["mlir_generated_op_gpu_tanh_test.cc"]),
+    tags = tf_cuda_tests_tags() + ["no_rocm"],
+    deps = [
+        ":cwise_op",
+        ":ops_testutil",
+        "//tensorflow/core:framework",
+        "//tensorflow/core:framework_internal",
+        "//tensorflow/core:tensorflow",
+        "//tensorflow/core:test",
+        "//tensorflow/core:test_main",
+        "//tensorflow/core:testlib",
+        "//tensorflow/core/common_runtime:device",
+        "//tensorflow/core/common_runtime:device_factory",
+    ],
+)
+
 tf_kernel_library(
     name = "nextafter_op",
     prefix = "nextafter_op",

tensorflow/core/kernels/mlir_generated_op_gpu_tanh_test.cc

@@ -0,0 +1,85 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <cmath>
+#include <memory>
+#include <vector>
+
+#include "tensorflow/core/common_runtime/device.h"
+#include "tensorflow/core/common_runtime/device_factory.h"
+#include "tensorflow/core/framework/fake_input.h"
+#include "tensorflow/core/framework/node_def_builder.h"
+#include "tensorflow/core/framework/tensor.h"
+#include "tensorflow/core/kernels/ops_testutil.h"
+#include "tensorflow/core/lib/core/status_test_util.h"
+#include "tensorflow/core/platform/test.h"
+
+namespace tensorflow {
+namespace {
+
+class MlirGeneratedOpGpuTanhTest : public OpsTestBase {
+ protected:
+  void SetUp() override {
+    std::unique_ptr<tensorflow::Device> device_gpu(
+        tensorflow::DeviceFactory::NewDevice("GPU", {},
+                                             "/job:a/replica:0/task:0"));
+    SetDevice(tensorflow::DEVICE_GPU, std::move(device_gpu));
+  }
+  template <typename T, typename RT = T>
+  void RunTanhOp(std::initializer_list<T> input) {
+    TensorShape shape({2, 7});
+    TF_ASSERT_OK(NodeDefBuilder("tanh_op", "Tanh")
+                     .Input(FakeInput(DataTypeToEnum<T>::v()))
+                     .Attr("T", DataTypeToEnum<T>::v())
+                     .Finalize(node_def()));
+
+    TF_ASSERT_OK(InitOp());
+    AddInputFromArray<T>(shape, input);
+    TF_ASSERT_OK(RunOpKernel());
+
+    Tensor expected_tensor(allocator(), DataTypeToEnum<T>::value, shape);
+    std::vector<T> expected;
+    expected.reserve(input.size());
+    for (const T& inp : input) {
+      expected.push_back(static_cast<T>(std::tanh(static_cast<RT>(inp))));
+    }
+    test::FillValues<T>(&expected_tensor, expected);
+    test::ExpectClose(expected_tensor, *GetOutput(0));
+  }
+};
+
+TEST_F(MlirGeneratedOpGpuTanhTest, TanhFloat) {
+  RunTanhOp<float>({-18.0f, -9.0f, -1e-6f, -0.0f, 0.0f, 1e-6, 0.1f, 0.2f, 0.3f,
+                    0.5f, 0.7f, 0.9f, 9.0f, 18.0f});
+}
+
+TEST_F(MlirGeneratedOpGpuTanhTest, TanhDouble) {
+  RunTanhOp<double>({-18.0, -9.0, -1e-6, -0.0, 0.0, 1e-6, 0.1, 0.2, 0.3, 0.5,
+                     0.7, 0.9, 9.0, 18.0});
+}
+
+TEST_F(MlirGeneratedOpGpuTanhTest, TanhHalf) {
+  RunTanhOp<Eigen::half, float>(
+      {static_cast<Eigen::half>(-18.0), static_cast<Eigen::half>(-9.0),
+       static_cast<Eigen::half>(-1e-6), static_cast<Eigen::half>(-0.0),
+       static_cast<Eigen::half>(0.0), static_cast<Eigen::half>(1e-6),
+       static_cast<Eigen::half>(0.1), static_cast<Eigen::half>(0.2),
+       static_cast<Eigen::half>(0.3), static_cast<Eigen::half>(0.5),
+       static_cast<Eigen::half>(0.7), static_cast<Eigen::half>(0.9),
+       static_cast<Eigen::half>(9.0), static_cast<Eigen::half>(18.0)});
+}
+
+}  // namespace
+}  // end namespace tensorflow