text: /*******************************************************************************
  * Copyright 2018-2020 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 CPU_X64_JIT_AVX512_CORE_X8S8S32X_1X1_CONVOLUTION_HPP
  #define CPU_X64_JIT_AVX512_CORE_X8S8S32X_1X1_CONVOLUTION_HPP
  
  #include "common/c_types_map.hpp"
  #include "common/dnnl_thread.hpp"
  #include "common/memory_tracking.hpp"
  #include "common/primitive.hpp"
  #include "common/primitive_hashing.hpp"
  #include "common/utils.hpp"
  
  #include "cpu/cpu_convolution_pd.hpp"
  #include "cpu/dw_convolution_utils.hpp"
  #include "cpu/platform.hpp"
  
  #include "cpu/x64/jit_avx512_core_x8s8s32x_1x1_conv_kernel.hpp"
  #include "cpu/x64/jit_avx512_core_x8s8s32x_convolution.hpp"
  #include "cpu/x64/jit_uni_1x1_conv_utils.hpp"
  
  namespace dnnl {
  namespace impl {
  namespace cpu {
  namespace x64 {
  
  template <impl::data_type_t src_type, impl::data_type_t dst_type>
  struct jit_avx512_core_x8s8s32x_1x1_convolution_fwd_t : public primitive_t {
      struct pd_t : public cpu_convolution_fwd_pd_t {
          using dw_conv_pd_type = cpu_convolution_fwd_pd_t;
          pd_t(const convolution_desc_t *adesc, const primitive_attr_t *attr,
                  const typename pd_t::base_class *hint_fwd_pd)
              : cpu_convolution_fwd_pd_t(adesc, attr, hint_fwd_pd)
              , jcp_()
              , rtus_()
              , jcp_dw_(nullptr) {}
  
          pd_t(const pd_t &other) : cpu_convolution_fwd_pd_t(other) {
              if (copy(other) != status::success) is_initialized_ = false;
          }
  
          DECLARE_COMMON_PD_T(JIT_IMPL_NAME_HELPER("jit_int8_1x1:",
                                      ((jcp_.ver == ver_vnni) ? avx512_core_vnni
                                                              : avx512_core),
                                      ""),
                  jit_avx512_core_x8s8s32x_1x1_convolution_fwd_t);
  
          status_t init(engine_t *engine) {
              using smask_t = primitive_attr_t::skip_mask_t;
              bool ok = true && is_fwd()
                      && set_default_alg_kind(alg_kind::convolution_direct)
                      && expect_data_types(src_type, data_type::s8,
                              data_type::undef, dst_type, data_type::s32)
                      && IMPLICATION(with_bias(),
                              utils::one_of(desc()->bias_desc.data_type,
                                      data_type::f32, data_type::s32,
                                      data_type::s8, data_type::u8))
                      && attr()->has_default_values(smask_t::oscale
                                      | smask_t::zero_points_runtime
                                      | smask_t::post_ops,
                              dst_type)
                      && !has_zero_dim_memory() && zero_points_ok()
                      && set_default_formats_common(
                              dat_tag(), format_tag::any, dat_tag());
  
              if (!ok) return status::unimplemented;
              const convolution_desc_t *conv_d = desc();
              const memory_desc_t *src_d = src_md();
              rtus_prepare(this, conv_d, src_d, dst_md(), weights_md());
  
              status_t status
                      = jit_avx512_core_x8s8s32x_1x1_conv_kernel::init_conf(jcp_,
                              *conv_d, src_d, weights_md_, dst_md_, bias_md_,
                              *attr(), dnnl_get_max_threads(), rtus_.reduce_src_);
              if (status != status::success) return status;
  
              if (jcp_.with_dw_conv) {
                  status = depthwise_po_init(engine);
                  if (status != status::success) return status;
              }
  
              auto scratchpad = scratchpad_registry().registrar();
              jit_avx512_core_x8s8s32x_1x1_conv_kernel::init_scratchpad(
                      scratchpad, jcp_, *attr());
  
              rtus_prepare_space_info(this, scratchpad, jcp_.nthr);
  
              return status::success;
          }
  
          const memory_desc_t *dst_md(int index = 0) const override {
              return jcp_.with_dw_conv ? dw_conv_pd_->dst_md(index) : &dst_md_;
          }
  
          const memory_desc_t *arg_md(int index = 0) const override {
              if (jcp_.with_dw_conv) {
                  switch (index) {
                      case DNNL_ARG_ATTR_POST_OP_DW | DNNL_ARG_WEIGHTS:
                          return dw_conv_pd_->weights_md(0);
                      case DNNL_ARG_ATTR_POST_OP_DW | DNNL_ARG_BIAS:
                          return dw_conv_pd_->weights_md(1);
                      default: break;
                  }
              }
              return convolution_fwd_pd_t::arg_md(index);
          }
  
          arg_usage_t arg_usage(int arg) const override {
              if (arg == (DNNL_ARG_ATTR_POST_OP_DW | DNNL_ARG_WEIGHTS))
                  return arg_usage_t::input;
  
              if (arg == (DNNL_ARG_ATTR_POST_OP_DW | DNNL_ARG_BIAS)
                      && attr_post_op_dw_inputs() > 1)
                  return arg_usage_t::input;
  
              return convolution_fwd_pd_t::arg_usage(arg);
          }
  
          jit_1x1_conv_conf_t jcp_;
          reduce_to_unit_stride_t rtus_;
          jit_conv_conf_t *jcp_dw_; // doesn't own a resource
          std::unique_ptr<cpu_convolution_fwd_pd_t> dw_conv_pd_;
          template <data_type_t sdt, data_type_t ddt>
          using dw_pd_t = typename jit_avx512_core_x8s8s32x_convolution_fwd_t<sdt,
                  ddt>::pd_t;
  
      protected:
          format_tag_t dat_tag() const {
              return utils::pick(src_md_.ndims - 3, format_tag::nwc,
                      format_tag::nhwc, format_tag::ndhwc);
          }
  
          bool zero_points_ok() const {
              using namespace data_type;
              int mask_src = 0, mask_dst = 0;
              attr()->zero_points_.get(DNNL_ARG_SRC, nullptr, &mask_src, nullptr);
              attr()->zero_points_.get(DNNL_ARG_DST, nullptr, &mask_dst, nullptr);
              return attr()->zero_points_.has_default_values(DNNL_ARG_WEIGHTS)
                      && utils::one_of(mask_src, 0, 0x1, 0x3)
                      && utils::one_of(mask_dst, 0, 0x1, 0x3);
          }
  
          status_t copy(const pd_t &other) {
              jcp_ = other.jcp_;
              rtus_ = other.rtus_;
              jcp_dw_ = nullptr;
  
              if (other.dw_conv_pd_) {
                  dw_conv_pd_.reset(static_cast<cpu_convolution_fwd_pd_t *>(
                          other.dw_conv_pd_->clone()));
                  if (!dw_conv_pd_) return status::out_of_memory;
  #define CASE(sdt, ddt) \
      case ddt: \
          jcp_dw_ = &( \
                  static_cast<dw_pd_t<sdt, ddt> *>(dw_conv_pd_.get())->jcp_); \
          break;
  
                  auto dw_dst_dt = dw_conv_pd_->dst_md()->data_type;
                  if (jcp_.dst_dt == data_type::u8) {
                      switch (dw_dst_dt) {
                          CASE(data_type::u8, data_type::u8);
                          CASE(data_type::u8, data_type::s8);
                          CASE(data_type::u8, data_type::s32);
                          CASE(data_type::u8, data_type::f32);
                          default: assert(!"unreachable");
                      }
                  } else if (jcp_.dst_dt == data_type::s8) {
                      switch (dw_dst_dt) {
                          CASE(data_type::s8, data_type::u8);
                          CASE(data_type::s8, data_type::s8);
                          CASE(data_type::s8, data_type::s32);
                          CASE(data_type::s8, data_type::f32);
                          default: assert(!"unreachable");
                      }
                  } else {
                      assert(!"unreachable");
                  }
  
  #undef CASE
              }
              return status::success;
          }
  
          status_t depthwise_po_init(engine_t *engine) {
              using namespace memory_tracking;
              auto &jcp_1x1 = jcp_;
              primitive_attr_t attr_1x1(*attr());
              if (!attr_1x1.is_initialized()) return status::out_of_memory;
              attr_1x1.set_scratchpad_mode(scratchpad_mode::user);
  
              const auto &src_md = dst_md_;
              const memory_desc_wrapper src_d(src_md);
              const auto nthr = dnnl_get_max_threads();
              auto l2_cache = platform::get_per_core_cache_size(2) * nthr;
  
              // Note: A robust fusion implementation would be to check if both
              // 1x1 conv and dw conv that are considered here for fusion are
              // optimal independently. This would require creating a new
              // primitive_desc through primitive_iterator & check if they match.
              // Due to concern that these creations and/or checks could be heavy,
              // for 1x1: Check that no better ISA is available.
              // for dw: Always fuse with same ISA.
              // Caveat: May be a better dw conv exists.
  
              bool ok = !mayiuse(avx512_core_bf16_amx_int8)
                      && (attr_1x1.post_ops_.find(primitive_kind::sum) == -1)
                      // TODO: Below may be further tuned.
                      && (l2_cache < src_d.size())
                      // load_grp_count check can be redundant due to l2 check
                      // above. Adding it explicitly as the current driver doesn't
                      // work if this condition fails.
                      && (jcp_1x1.load_grp_count < 2);
              if (!ok) return status::unimplemented;
  
              int dw_po_index
                      = attr_1x1.post_ops_.find(primitive_kind::convolution);
  
              convolution_desc_t cd_dw;
              primitive_attr_t attr_dw;
              CHECK(get_depthwise_conv_desc(
                      cd_dw, src_md, attr_1x1, attr_dw, dw_po_index));
  
              auto dw_dst_dt = cd_dw.dst_desc.data_type;
  
  #define CASE(sdt, ddt) \
      case ddt: { \
          std::unique_ptr<dw_pd_t<sdt, ddt>> fusable_pd( \
                  new dw_pd_t<sdt, ddt>(&cd_dw, &attr_dw, nullptr)); \
          CHECK(fusable_pd->init(engine)); \
          jcp_dw_ = &(fusable_pd->jcp_); \
          dw_conv_pd_ = std::move(fusable_pd); \
          break; \
      }
              if (jcp_1x1.dst_dt == data_type::u8) {
                  switch (dw_dst_dt) {
                      CASE(data_type::u8, data_type::u8);
                      CASE(data_type::u8, data_type::s8);
                      CASE(data_type::u8, data_type::s32);
                      CASE(data_type::u8, data_type::f32);
                      default: return status::unimplemented;
                  }
              } else if (jcp_1x1.dst_dt == data_type::s8) {
                  switch (dw_dst_dt) {
                      CASE(data_type::s8, data_type::u8);
                      CASE(data_type::s8, data_type::s8);
                      CASE(data_type::s8, data_type::s32);
                      CASE(data_type::s8, data_type::f32);
                      default: return status::unimplemented;
                  }
              } else
                  return status::unimplemented;
  #undef CASE
  
              ok = true
                      && (dnnl_memory_desc_equal(&src_md, dw_conv_pd_->src_md(0)))
                      && (jcp_1x1.oc_without_padding % jcp_1x1.oc_block == 0)
                      && IMPLICATION(jcp_dw_->ow_block,
                              jcp_dw_->ow_block == jcp_dw_->ow);
              if (!ok) return status::unimplemented;
  
              assert(jcp_dw_);
              assert(dw_conv_pd_->dst_md(0)->format_kind != format_kind::any);
              assert(dw_conv_pd_->weights_md(0)->format_kind != format_kind::any);
              assert(IMPLICATION(
                      dw_conv_pd_->weights_md(1)->data_type != data_type::undef,
                      dw_conv_pd_->weights_md(1)->format_kind
                              != format_kind::any));
  
              jcp_dw_->is_fused_conv = true;
              // TODO: Support/experiment arbitary oc_work in dw conv.
              // Until then we keep ch_work perfectly divisible.
              while (jcp_1x1.nb_load % jcp_1x1.nb_load_blocking != 0)
                  --jcp_1x1.nb_load_blocking;
              jcp_1x1.nb_load_blocking_max = jcp_1x1.nb_load_blocking;
  
              while (jcp_1x1.nb_load_blocking % jcp_dw_->nb_ch_blocking != 0)
                  --jcp_dw_->nb_ch_blocking;
  
              jcp_dw_->dw_conv_buffer_oc
                      = jcp_1x1.nb_load_blocking * jcp_1x1.oc_block;
              jcp_1x1.bcast_loop_output_step = jcp_1x1.ur
                      * (jcp_1x1.nb_load_blocking * jcp_1x1.oc_block)
                      * jcp_1x1.typesize_out;
  
              registrar_t scratchpad(scratchpad_registry_);
              registrar_t dw_scratchpad(scratchpad, names::prefix_fusion);
  
              size_t dw_conv_buffer_size_ = (size_t)nthr * jcp_dw_->kh
                      * jcp_dw_->iw * jcp_dw_->dw_conv_buffer_oc;
              assert(dw_conv_buffer_size_);
              dw_scratchpad.book(memory_tracking::names::key_fusion_inout_buffer,
                      dw_conv_buffer_size_,
                      types::data_type_size(dw_conv_pd_->src_md()->data_type));
  
              dw_conv_kernel_t::init_scratchpad(
                      dw_scratchpad, *jcp_dw_, *(dw_conv_pd_->attr()));
              return status::success;
          }
      };
      template <cpu_isa_t isa, typename conv_t>
      friend status_t init_rtus_driver(conv_t *self);
  
      jit_avx512_core_x8s8s32x_1x1_convolution_fwd_t(const pd_t *apd)
          : primitive_t(apd) {}
  
      typedef typename prec_traits<src_type>::type src_data_t;
      typedef typename prec_traits<data_type::s8>::type wei_data_t;
      typedef typename prec_traits<dst_type>::type dst_data_t;
      // Note: In case of fused depthwise convolution, the final output datatype
      // after fusion may not be dst_data_t.
      typedef typename prec_traits<data_type::s32>::type acc_data_t;
  
      status_t init(engine_t *engine) override {
          CHECK(safe_ptr_assign(kernel_,
                  new jit_avx512_core_x8s8s32x_1x1_conv_kernel(
                          pd()->jcp_, *pd()->attr(), *pd()->dst_md(0))));
          CHECK(kernel_->create_kernel());
  
          if (pd()->jcp_.with_dw_conv) {
              CHECK(safe_ptr_assign(kernel_dw_,
                      new dw_conv_kernel_t(*(pd()->jcp_dw_),
                              *(pd()->dw_conv_pd_->attr()), *pd()->dst_md(0))));
              CHECK(kernel_dw_->create_kernel());
          }
  
          CHECK(init_rtus_driver<avx512_common>(this));
          return status::success;
      }
  
      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;
      void execute_forward_thr(const int ithr, const int nthr,
              const src_data_t *src, const wei_data_t *weights, const char *bias,
              const wei_data_t *weights_dw, const char *bias_dw, dst_data_t *dst,
              const int32_t *src_zero_point, const int32_t *dst_zero_point,
              const memory_tracking::grantor_t &scratchpad,
              const void *post_ops_binary_rhs_arg_vec,
              const void *post_ops_binary_rhs_arg_vec_dw) const;
      const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }
      std::unique_ptr<jit_avx512_core_x8s8s32x_1x1_conv_kernel> kernel_;
      std::unique_ptr<rtus_driver_t<avx512_common>> rtus_driver_;
      using dw_conv_kernel_t = jit_avx512_core_x8s8s32x_fwd_kernel;
      std::unique_ptr<dw_conv_kernel_t> kernel_dw_;
  };
  
  } // namespace x64
  } // namespace cpu
  } // namespace impl
  } // namespace dnnl
  
  #endif
  