//*****************************************************************************
// Copyright 2017-2018 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 <array>
#include <set>
#include <string>
#include <vector>

namespace ngraph
{
    namespace codegen
    {
        class CodeWriter;
    }
    namespace runtime
    {
        namespace gpu
        {
            class GPUKernelArgs;
            class CudaKernelBuilder
            {
            public:
                static void get_elementwise_op(codegen::CodeWriter& writer,
                                               const std::string& name,
                                               const std::string& op,
                                               const std::vector<std::string>& data_types);

                static void get_broadcast_op(codegen::CodeWriter& writer,
                                             const std::string& name,
                                             GPUKernelArgs& args,
                                             const size_t rank);

                static void get_concat_op(codegen::CodeWriter& writer,
                                          const std::string& name,
                                          const std::vector<std::string>& data_types,
                                          size_t num_inputs);

                static void get_onehot_op(codegen::CodeWriter& writer,
                                          const std::string& name,
                                          const std::array<std::string, 2>& data_types);

                static void get_reshape_op(codegen::CodeWriter& writer,
                                           const std::string& name,
                                           runtime::gpu::GPUKernelArgs& args,
                                           const std::array<std::string, 2>& data_types,
                                           size_t rank);

                static void get_reshape_op_3d(codegen::CodeWriter& writer,
                                              const std::string& name,
                                              runtime::gpu::GPUKernelArgs& args,
                                              const std::string& data_type,
                                              const std::vector<uint32_t>& order,
                                              const std::vector<uint32_t>& block_size);

                static void get_reshape_op_2d(codegen::CodeWriter& writer,
                                              const std::string& name,
                                              runtime::gpu::GPUKernelArgs& args,
                                              const std::string& data_type,
                                              uint32_t block_size);

                static void get_reduce_to_nd_op(codegen::CodeWriter& writer,
                                                const std::string& name,
                                                runtime::gpu::GPUKernelArgs& args,
                                                const std::vector<std::string>& data_types,
                                                const std::string& reduce_op,
                                                size_t out_rank,
                                                size_t reduce_rank);

                //using one block with at most 512 threads to reduce to scalar.
                static void get_reduce_to_scalar_op(codegen::CodeWriter& writer,
                                                    const std::string& name,
                                                    runtime::gpu::GPUKernelArgs& args,
                                                    const std::vector<std::string>& data_types,
                                                    const std::string& reduce_op,
                                                    uint32_t block_size_x);

                //This is the preprocess to reduce to scalar if the data size is large than a number.
                //The number can be tuned based on hardware.
                //This cuda kernel will accumulate reduction to a certain number of bins depends on hardware.
                static void get_reduce_to_scalar_acc_op(codegen::CodeWriter& writer,
                                                        const std::string& name,
                                                        runtime::gpu::GPUKernelArgs& args,
                                                        const std::vector<std::string>& data_types,
                                                        const std::string& reduce_op);

                static void get_slice_op(codegen::CodeWriter& writer,
                                         const std::string& name,
                                         const std::array<std::string, 2>& data_types,
                                         size_t rank);

                static void get_reverse_op(codegen::CodeWriter& writer,
                                           const std::string& name,
                                           const std::array<std::string, 2>& data_types);

                static void get_replace_slice_op(codegen::CodeWriter& writer,
                                                 const std::string& name,
                                                 GPUKernelArgs& args,
                                                 const size_t rank);

                static void get_reduce_window_op(codegen::CodeWriter& writer,
                                                 const std::string& name,
                                                 const std::string& op,
                                                 const std::vector<std::string>& data_types,
                                                 const size_t rank);

                static void get_reverse_sequence_op(codegen::CodeWriter& writer,
                                                    const std::string& name,
                                                    const std::array<std::string, 3>& data_types,
                                                    const size_t batch_axis,
                                                    const size_t sequence_axis,
                                                    const size_t rank);

                static void get_device_helper(codegen::CodeWriter& writer,
                                              const std::string& name,
                                              const std::string& math_kernel,
                                              const std::vector<std::string>& data_types);

                static void get_pad_op(codegen::CodeWriter& writer,
                                       const std::string& name,
                                       GPUKernelArgs& args,
                                       size_t rank);

                static void get_pad_fill_op(codegen::CodeWriter& writer,
                                            const std::string& name,
                                            GPUKernelArgs& args,
                                            size_t rank);

                static void get_ew_collective_op(codegen::CodeWriter& writer,
                                                 const std::string& name,
                                                 GPUKernelArgs& args,
                                                 const std::string& op,
                                                 const std::string& reduce_op,
                                                 const std::vector<std::string>& data_types,
                                                 const std::set<size_t>& reduced_tensors,
                                                 bool save_elementwise,
                                                 size_t rank);

                static void get_max_pool_1d(codegen::CodeWriter& writer,
                                            const std::string& name,
                                            const std::array<std::string, 2>& data_types,
                                            size_t input_width,
                                            size_t output_width,
                                            size_t window_width,
                                            size_t window_stride);

                static void get_avg_pool(codegen::CodeWriter& writer,
                                         const std::string& name,
                                         const std::array<std::string, 2>& data_types,
                                         bool include_pad);

                static void get_convolution_forward(codegen::CodeWriter& writer,
                                                    const std::string& name,
                                                    const std::array<std::string, 3>& data_types,
                                                    GPUKernelArgs& args,
                                                    int N,
                                                    int K,
                                                    int rank,
                                                    int filter_size,
                                                    int sm_tile_size = 8,
                                                    int reg_tile_size = 1);

                static void get_softmax_divide_op(codegen::CodeWriter& writer,
                                                  const std::string& name,
                                                  const std::vector<std::string>& data_types,
                                                  std::vector<size_t> axes_flag,
                                                  size_t rank);

                static void add_pod_typedefs(codegen::CodeWriter& writer);

                /// \brief Given kernel input variables i_* produce register variables o_coordinates{i}
                ///        of the non-reduced tensor and return the string name of integer index into reduced tensor
                static std::string
                    collective_coordinate_transform_helper(codegen::CodeWriter& writer,
                                                           std::string i_thread_index,
                                                           std::string i_strides,
                                                           std::string i_stride_magic,
                                                           std::string i_stride_shift,
                                                           std::string i_reduced_strides,
                                                           std::string o_coordinates,
                                                           size_t rank,
                                                           bool register_arguments = false);
                static void coordinate_transform_to_multi_d(codegen::CodeWriter& writer,
                                                            std::string i_strides,
                                                            std::string i_stride_magic,
                                                            std::string i_stride_shift,
                                                            std::string i_coord_product,
                                                            std::string o_coordinates,
                                                            size_t rank,
                                                            bool register_arguments = false);
            };
        }
    }
}
