Implement trigonometric ops for direct execution. (#1289)

* Implement trigonometric ops for direct execution.

* Rename files.

src/ngraph/runtime/cpu/cpu_builder.cpp

@@ -79,10 +79,15 @@
 #include "ngraph/runtime/cpu/cpu_kernels.hpp"
 #include "ngraph/runtime/cpu/cpu_op_annotations.hpp"
 #include "ngraph/runtime/cpu/kernel/abs.hpp"
+#include "ngraph/runtime/cpu/kernel/acos.hpp"
 #include "ngraph/runtime/cpu/kernel/add.hpp"
 #include "ngraph/runtime/cpu/kernel/and.hpp"
+#include "ngraph/runtime/cpu/kernel/asin.hpp"
+#include "ngraph/runtime/cpu/kernel/atan.hpp"
 #include "ngraph/runtime/cpu/kernel/broadcast.hpp"
 #include "ngraph/runtime/cpu/kernel/ceil.hpp"
+#include "ngraph/runtime/cpu/kernel/cos.hpp"
+#include "ngraph/runtime/cpu/kernel/cosh.hpp"
 #include "ngraph/runtime/cpu/kernel/cwise_pow.hpp"
 #include "ngraph/runtime/cpu/kernel/divide.hpp"
 #include "ngraph/runtime/cpu/kernel/equal.hpp"
@@ -103,8 +108,12 @@
 #include "ngraph/runtime/cpu/kernel/relu.hpp"
 #include "ngraph/runtime/cpu/kernel/result.hpp"
 #include "ngraph/runtime/cpu/kernel/sign.hpp"
+#include "ngraph/runtime/cpu/kernel/sin.hpp"
+#include "ngraph/runtime/cpu/kernel/sinh.hpp"
 #include "ngraph/runtime/cpu/kernel/sqrt.hpp"
 #include "ngraph/runtime/cpu/kernel/subtract.hpp"
+#include "ngraph/runtime/cpu/kernel/tan.hpp"
+#include "ngraph/runtime/cpu/kernel/tanh.hpp"
 #include "ngraph/runtime/cpu/op/convert_layout.hpp"
 #include "ngraph/type/element_type.hpp"
 #include "ngraph/util.hpp"
@@ -242,12 +251,42 @@ namespace ngraph
                 BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::abs);
             }
 
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Acos)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::acos);
+            }
+
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Asin)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::asin);
+            }
+
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Atan)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::atan);
+            }
+
             template <>
             void Builder::BUILDER_DECL(ngraph::op::Ceiling)
             {
                 BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::ceil);
             }
 
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Cos)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::cos);
+            }
+
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Cosh)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::cosh);
+            }
+
             template <>
             void Builder::BUILDER_DECL(ngraph::op::Floor)
             {
@@ -302,6 +341,30 @@ namespace ngraph
                 BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::sign);
             }
 
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Sin)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::sin);
+            }
+
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Sinh)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::sinh);
+            }
+
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Tan)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::tan);
+            }
+
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Tanh)
+            {
+                BUILD_UNARY_ELEMWISE_FUNCTOR(runtime::cpu::kernel::tanh);
+            }
+
             template <>
             void Builder::BUILDER_DECL(ngraph::op::Constant)
             {
@@ -342,7 +405,12 @@ namespace ngraph
             REGISTER_OP_BUILDER(Divide);
             REGISTER_OP_BUILDER(Power);
             REGISTER_OP_BUILDER(Abs);
+            REGISTER_OP_BUILDER(Acos);
+            REGISTER_OP_BUILDER(Asin);
+            REGISTER_OP_BUILDER(Atan);
             REGISTER_OP_BUILDER(Ceiling);
+            REGISTER_OP_BUILDER(Cos);
+            REGISTER_OP_BUILDER(Cosh)
             REGISTER_OP_BUILDER(Floor);
             REGISTER_OP_BUILDER(Negative);
             REGISTER_OP_BUILDER(Relu);
@@ -350,6 +418,10 @@ namespace ngraph
             REGISTER_OP_BUILDER(Log);
             REGISTER_OP_BUILDER(Sqrt);
             REGISTER_OP_BUILDER(Sign);
+            REGISTER_OP_BUILDER(Sin);
+            REGISTER_OP_BUILDER(Sinh);
+            REGISTER_OP_BUILDER(Tan);
+            REGISTER_OP_BUILDER(Tanh);
 
             REGISTER_OP_BUILDER(Not);
             REGISTER_OP_BUILDER(Equal);

src/ngraph/runtime/cpu/kernel/acos.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void acos(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) =
+                        in0.unaryExpr(Eigen::internal::scalar_acos_op<ElementType>());
+                }
+            }
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/asin.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void asin(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) =
+                        in0.unaryExpr(Eigen::internal::scalar_asin_op<ElementType>());
+                }
+            }
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/atan.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void atan(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) =
+                        in0.unaryExpr(Eigen::internal::scalar_atan_op<ElementType>());
+                }
+            }
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/cos.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void cos(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) =
+                        in0.unaryExpr(Eigen::internal::scalar_cos_op<ElementType>());
+                }
+            }
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/cosh.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void cosh(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) =
+                        in0.unaryExpr(Eigen::internal::scalar_cosh_op<ElementType>());
+                }
+            }
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/sin.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void sin(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) =
+                        in0.unaryExpr(Eigen::internal::scalar_sin_op<ElementType>());
+                }
+            }
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/sinh.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void sinh(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) =
+                        in0.unaryExpr(Eigen::internal::scalar_sinh_op<ElementType>());
+                }
+            }
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/tan.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void tan(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) =
+                        in0.unaryExpr(Eigen::internal::scalar_tan_op<ElementType>());
+                }
+            }
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/tanh.hpp

+/*******************************************************************************
+* Copyright 2018 Intel Corporation
+*
+* 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.
+*******************************************************************************/
+
+#pragma once
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void tanh(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) = in0.tanh();
+                }
+            }
+        }
+    }
+}