text: /*******************************************************************************
  * Copyright 2019-2020 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.
  *******************************************************************************/
  
  #ifndef GPU_OCL_REF_LRN_HPP
  #define GPU_OCL_REF_LRN_HPP
  
  #include "common/c_types_map.hpp"
  #include "common/nstl.hpp"
  #include "common/primitive.hpp"
  #include "common/type_helpers.hpp"
  #include "gpu/compute/compute.hpp"
  #include "gpu/gpu_lrn_pd.hpp"
  #include "gpu/gpu_primitive.hpp"
  #include "gpu/gpu_resource.hpp"
  #include "gpu/ocl/ocl_stream.hpp"
  #include "gpu/ocl/ocl_utils.hpp"
  #include "gpu/primitive_conf.hpp"
  
  namespace dnnl {
  namespace impl {
  namespace gpu {
  namespace ocl {
  
  struct ref_lrn_fwd_t : public gpu_primitive_t {
      struct pd_t : public gpu_lrn_fwd_pd_t {
          pd_t(const lrn_desc_t *adesc, const primitive_attr_t *attr,
                  const lrn_fwd_pd_t *hint_fwd_pd)
              : gpu_lrn_fwd_pd_t(adesc, attr, hint_fwd_pd) {}
          virtual ~pd_t() {}
  
          DECLARE_COMMON_PD_T("ref:any", ref_lrn_fwd_t);
  
          status_t init(engine_t *engine) {
              using namespace data_type;
              assert(engine->kind() == engine_kind::gpu);
              auto *compute_engine
                      = utils::downcast<compute::compute_engine_t *>(engine);
              bool ok = true
                      && utils::one_of(desc()->prop_kind,
                              prop_kind::forward_inference,
                              prop_kind::forward_training)
                      && utils::one_of(desc()->alg_kind,
                              alg_kind::lrn_across_channels,
                              alg_kind::lrn_within_channel)
                      && utils::one_of(
                              desc()->data_desc.data_type, f32, f16, bf16)
                      && attr()->has_default_values()
                      && IMPLICATION(desc()->data_desc.data_type == f16,
                              compute_engine->mayiuse(
                                      compute::device_ext_t::khr_fp16));
              if (!ok) return status::unimplemented;
  
              if (desc_.prop_kind == prop_kind::forward_training) {
                  ws_md_ = *src_md();
                  if (ws_md_.data_type == data_type::bf16)
                      ws_md_.data_type = data_type::f32;
              }
  
              dispatch = compute_engine->create_dispatch(&data_md_);
              dispatch.define_dim("MB", 0, MB());
              dispatch.define_dim("IC", 1, C());
              dispatch.define_dim("ID", nstl::max(1, data_md_.ndims - 3), D());
              dispatch.define_dim("IH", nstl::max(1, data_md_.ndims - 2), H());
              dispatch.define_dim("IW", nstl::max(1, data_md_.ndims - 1), W());
              dispatch.generate();
  
              return status::success;
          }
  
          compute::dispatch_t dispatch;
      };
  
      ref_lrn_fwd_t(const pd_t *apd) : gpu_primitive_t(apd) {}
  
      status_t init(engine_t *engine) override {
          using namespace alg_kind;
  
          compute::kernel_ctx_t kernel_ctx;
  
          status_t status = status::success;
          const auto *desc = pd()->desc();
  
          kernel_ctx.set_data_type(desc->data_desc.data_type);
  
          kernel_ctx.define_int("IS_FWD", 1);
  
          if (desc->prop_kind == prop_kind::forward_training)
              kernel_ctx.define_int("IS_TRAINING", 1);
  
          switch (desc->alg_kind) {
              case lrn_across_channels:
                  kernel_ctx.define_int("ACROSS_CHANNEL", 1);
                  break;
              case lrn_within_channel:
                  kernel_ctx.define_int("WITHIN_CHANNEL", 1);
                  break;
              default: status = status::unimplemented;
          }
          if (status != status::success) return status;
  
          const memory_desc_wrapper src_d(pd()->src_md());
          const memory_desc_wrapper dst_d(pd()->dst_md());
          const int ndims = src_d.ndims();
  
          kernel_ctx.define_int("NDIMS", ndims);
          kernel_ctx.define_int("MB", pd()->MB());
          kernel_ctx.define_int("IC", pd()->C());
          kernel_ctx.define_int("ID", pd()->D());
          kernel_ctx.define_int("IH", pd()->H());
          kernel_ctx.define_int("IW", pd()->W());
  
          const uint32_t round_norm_size = desc->local_size;
          uint32_t num_elements = pow(round_norm_size, nstl::max(0, ndims - 2));
          if (desc->alg_kind == lrn_across_channels) {
              num_elements = round_norm_size;
          }
          const float num_element_div = 1.f / (float)num_elements;
          const auto padding = (desc->local_size - 1) / 2;
  
          kernel_ctx.define_float("NUM_ELEMENTS_DIV", num_element_div);
          kernel_ctx.define_int("PADDING", padding);
          kernel_ctx.define_int(
                  "LOCAL_SIZE", desc->local_size - 1 + desc->local_size % 2);
          kernel_ctx.define_float("LRN_ALPHA", desc->lrn_alpha);
          kernel_ctx.define_float("LRN_BETA", desc->lrn_beta);
          kernel_ctx.define_float("LRN_K", desc->lrn_k);
  
          offsets_t off;
          set_offsets(src_d, off.src_off);
          set_offsets(dst_d, off.dst_off);
          def_offsets(off.src_off, kernel_ctx, "SRC", ndims);
          def_offsets(off.dst_off, kernel_ctx, "DST", ndims);
  
          def_dispatch(kernel_ctx, pd()->dispatch);
  
          create_kernel(engine, &kernel_, "ref_lrn_fwd", kernel_ctx);
          if (!kernel_) return status::runtime_error;
  
          return status::success;
      }
  
      virtual status_t execute(const exec_ctx_t &ctx) const override {
          return execute_forward(ctx);
      }
  
  private:
      status_t execute_forward(const exec_ctx_t &ctx) const;
      const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }
      compute::kernel_t kernel_;
  };
  
  struct ref_lrn_bwd_t : public gpu_primitive_t {
      struct pd_t : public gpu_lrn_bwd_pd_t {
          pd_t(const lrn_desc_t *adesc, const primitive_attr_t *attr,
                  const lrn_fwd_pd_t *hint_fwd_pd)
              : gpu_lrn_bwd_pd_t(adesc, attr, hint_fwd_pd) {}
          virtual ~pd_t() {}
  
          DECLARE_COMMON_PD_T("ref:any", ref_lrn_bwd_t);
  
          status_t init(engine_t *engine) {
              assert(engine->kind() == engine_kind::gpu);
              auto *compute_engine
                      = utils::downcast<compute::compute_engine_t *>(engine);
              bool ok = true
                      && utils::one_of(
                              desc()->prop_kind, prop_kind::backward_data)
                      && utils::one_of(desc()->alg_kind,
                              alg_kind::lrn_across_channels,
                              alg_kind::lrn_within_channel)
                      && utils::one_of(desc()->data_desc.data_type,
                              data_type::f32, data_type::bf16)
                      && set_default_formats_common()
                      && attr()->has_default_values()
                      && IMPLICATION(
                              desc()->data_desc.data_type == data_type::f16,
                              compute_engine->mayiuse(
                                      compute::device_ext_t::khr_fp16));
              if (!ok) return status::unimplemented;
  
              ws_md_ = *src_md();
              if (ws_md_.data_type == data_type::bf16)
                  ws_md_.data_type = data_type::f32;
              if (!compare_ws(hint_fwd_pd_)) return status::unimplemented;
  
              dispatch = compute_engine->create_dispatch(&diff_data_md_);
              dispatch.define_dim("MB", 0, MB());
              dispatch.define_dim("IC", 1, C());
              dispatch.define_dim("ID", nstl::max(1, data_md_.ndims - 3), D());
              dispatch.define_dim("IH", nstl::max(1, data_md_.ndims - 2), H());
              dispatch.define_dim("IW", nstl::max(1, data_md_.ndims - 1), W());
              dispatch.generate();
  
              return status::success;
          }
  
          compute::dispatch_t dispatch;
      };
  
      ref_lrn_bwd_t(const pd_t *apd) : gpu_primitive_t(apd) {}
  
      status_t init(engine_t *engine) override {
          using namespace alg_kind;
  
          compute::kernel_ctx_t kernel_ctx;
  
          status_t status = status::success;
          const auto *desc = pd()->desc();
  
          kernel_ctx.set_data_type(desc->data_desc.data_type);
  
          kernel_ctx.define_int("IS_BWD", 1);
  
          switch (desc->alg_kind) {
              case lrn_across_channels:
                  kernel_ctx.define_int("ACROSS_CHANNEL", 1);
                  break;
              case lrn_within_channel:
                  kernel_ctx.define_int("WITHIN_CHANNEL", 1);
                  break;
              default: status = status::unimplemented;
          }
          if (status != status::success) return status;
  
          const memory_desc_wrapper src_d(pd()->src_md());
          const memory_desc_wrapper diff_dst_d(pd()->diff_dst_md());
          const int ndims = src_d.ndims();
  
          kernel_ctx.define_int("NDIMS", ndims);
          kernel_ctx.define_int("MB", pd()->MB());
          kernel_ctx.define_int("IC", pd()->C());
          kernel_ctx.define_int("ID", pd()->D());
          kernel_ctx.define_int("IH", pd()->H());
          kernel_ctx.define_int("IW", pd()->W());
  
          const uint32_t round_norm_size = desc->local_size;
          uint32_t num_elements = pow(round_norm_size, nstl::max(0, ndims - 2));
          if (desc->alg_kind == lrn_across_channels) {
              num_elements = round_norm_size;
          }
          const float num_element_div = 1.f / (float)num_elements;
          const auto padding = (desc->local_size - 1) / 2;
  
          kernel_ctx.define_float("NUM_ELEMENTS_DIV", num_element_div);
          kernel_ctx.define_int("PADDING", padding);
          kernel_ctx.define_int(
                  "LOCAL_SIZE", desc->local_size - 1 + desc->local_size % 2);
          kernel_ctx.define_float("LRN_ALPHA", desc->lrn_alpha);
          kernel_ctx.define_float("LRN_BETA", desc->lrn_beta);
          kernel_ctx.define_float("LRN_K", desc->lrn_k);
  
          offsets_t off;
          set_offsets(src_d, off.src_off);
          set_offsets(diff_dst_d, off.dst_off);
          def_offsets(off.src_off, kernel_ctx, "SRC", ndims);
          def_offsets(off.dst_off, kernel_ctx, "DST", ndims);
  
          def_dispatch(kernel_ctx, pd()->dispatch);
  
          create_kernel(engine, &kernel_, "ref_lrn_bwd", kernel_ctx);
          if (!kernel_) return status::runtime_error;
  
          return status::success;
      }
  
      virtual status_t execute(const exec_ctx_t &ctx) const override {
          return execute_backward(ctx);
      }
  
  private:
      status_t execute_backward(const exec_ctx_t &ctx) const;
      const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }
  
      compute::kernel_t kernel_;
  };
  
  } // namespace ocl
  } // namespace gpu
  } // namespace impl
  } // namespace dnnl
  
  #endif
  