CPU Direct Execution: Implement ReverseSequence

src/ngraph/runtime/cpu/builder/reverse_sequence.cpp

+/*******************************************************************************
+* 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.
+*******************************************************************************/
+
+#include "ngraph/op/reverse_sequence.hpp"
+#include "ngraph/runtime/cpu/cpu_builder.hpp"
+#include "ngraph/runtime/cpu/kernel/reverse_sequence.hpp"
+
+using namespace std;
+using namespace ngraph;
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::ReverseSequence)
+            {
+                auto rev_seq = static_cast<const ngraph::op::ReverseSequence*>(node);
+
+                auto& functors = external_function->get_functors();
+                auto& tensor_data = external_function->get_tensor_data();
+
+                auto& arg_tensor = tensor_data[args[0].get_name()];
+                auto& seq_len_tensor = tensor_data[args[1].get_name()];
+                auto& out_tensor = tensor_data[out[0].get_name()];
+
+                auto arg_shape = args[0].get_shape();
+
+                auto sequence_axis = rev_seq->get_sequence_axis();
+                auto batch_axis = rev_seq->get_batch_axis();
+
+                std::function<decltype(runtime::cpu::kernel::reverse_sequence<int, int, 4>)> kernel;
+
+                if (args[1].get_element_type() == element::i32)
+                {
+                    SELECT_KERNEL_BY_RANK(kernel,
+                                          args[0].get_element_type(),
+                                          arg_shape.size(),
+                                          runtime::cpu::kernel::reverse_sequence_sli32);
+                }
+                else
+                {
+                    throw ngraph_error("Unsupported sequence length type " +
+                                       args[1].get_element_type().c_type_string() +
+                                       " requires a kernel instantiation to handle this type");
+                }
+
+                auto functor =
+                    [&, kernel, arg_shape, batch_axis, sequence_axis](CPURuntimeContext* ctx) {
+                        kernel(arg_tensor,
+                               out_tensor,
+                               arg_shape,
+                               batch_axis,
+                               sequence_axis,
+                               seq_len_tensor);
+                    };
+                functors.emplace_back(functor);
+            }
+
+            REGISTER_OP_BUILDER(ReverseSequence);
+        }
+    }
+}

src/ngraph/runtime/cpu/kernel/reverse_sequence.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
+
+#include <cstdint>
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+#include "ngraph/shape.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename InputElementType, typename SeqLenType, unsigned int Rank>
+                void reverse_sequence(void* input,
+                                      void* output,
+                                      const Shape& input_shape,
+                                      size_t batch_axis,
+                                      size_t sequence_axis,
+                                      void* sequence_lengths)
+                {
+                    Eigen::array<Eigen::Index, Rank> in_dims;
+
+                    for (int i = 0; i < Rank; i++)
+                    {
+                        in_dims[i] = input_shape[i];
+                    }
+                    Eigen::TensorMap<Eigen::Tensor<InputElementType, Rank, Eigen::RowMajor>> out(
+                        static_cast<InputElementType*>(output), in_dims);
+                    Eigen::TensorMap<Eigen::Tensor<InputElementType, Rank, Eigen::RowMajor>> in(
+                        static_cast<InputElementType*>(input), in_dims);
+
+                    auto slv = static_cast<SeqLenType*>(sequence_lengths);
+
+                    auto generator = [&](const Eigen::array<Eigen::DenseIndex, Rank>& i) {
+                        Eigen::array<Eigen::DenseIndex, Rank> k = i;
+                        if (i[sequence_axis] < slv[i[batch_axis]])
+                        {
+                            k[sequence_axis] = slv[i[batch_axis]] - i[sequence_axis] - 1;
+                        }
+                        return in(k);
+                    };
+
+                    out.device(eigen::global_thread_pool_device) = in.generate(generator);
+                }
+
+                template <typename InputElementType, unsigned int Rank>
+                void reverse_sequence_sli32(void* input,
+                                            void* output,
+                                            const Shape& input_shape,
+                                            size_t batch_axis,
+                                            size_t sequence_axis,
+                                            void* sequence_lengths)
+                {
+                    reverse_sequence<InputElementType, int32_t, Rank>(
+                        input, output, input_shape, batch_axis, sequence_axis, sequence_lengths);
+                }
+            }
+        }
+    }
+}