/******************************************************************************* * Copyright 2016-2018 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. *******************************************************************************/ #ifndef CPU_JIT_AVX512_CORE_X8S8S32X_CONVOLUTION_HPP #define CPU_JIT_AVX512_CORE_X8S8S32X_CONVOLUTION_HPP #include "c_types_map.hpp" #include "memory_tracking.hpp" #include "mkldnn_thread.hpp" #include "utils.hpp" #include "cpu_convolution_pd.hpp" #include "jit_avx512_core_x8s8s32x_conv_kernel.hpp" namespace mkldnn { namespace impl { namespace cpu { template struct jit_avx512_core_x8s8s32x_convolution_fwd_t : public cpu_primitive_t { struct pd_t : public cpu_convolution_fwd_pd_t { pd_t(engine_t *engine, const convolution_desc_t *adesc, const primitive_attr_t *attr, const typename pd_t::base_class *hint_fwd_pd) : cpu_convolution_fwd_pd_t(engine, adesc, attr, hint_fwd_pd) , jcp_() {} DECLARE_COMMON_PD_T( JIT_IMPL_NAME_HELPER("jit_int8:", avx512_core, ""), jit_avx512_core_x8s8s32x_convolution_fwd_t); virtual status_t init() override { using namespace prop_kind; assert(this->engine()->kind() == engine_kind::cpu); bool ok = true && utils::one_of(this->desc()->prop_kind, forward_training, forward_inference) && utils::one_of(this->desc()->alg_kind, alg_kind::convolution_auto, alg_kind::convolution_direct) && !this->has_zero_dim_memory() && this->desc()->src_desc.data_type == src_type && this->desc()->dst_desc.data_type == dst_type && IMPLICATION(this->with_bias(), utils::one_of( this->desc()->bias_desc.data_type, data_type::f32, data_type::s32, data_type::s8, data_type::u8)) && this->desc()->accum_data_type == data_type::s32; if (!ok) return status::unimplemented; status_t status = jit_avx512_core_x8s8s32x_fwd_kernel::init_conf( jcp_, *this->desc(), this->src_pd_, this->weights_pd_, this->dst_pd_,this->bias_pd_, *this->attr(), mkldnn_get_max_threads()); if (status != status::success) return status; auto scratchpad = scratchpad_registry().registrar(); jit_avx512_core_x8s8s32x_fwd_kernel::init_scratchpad(scratchpad, jcp_, *this->attr()); if (status == status::success && this->desc()->alg_kind == alg_kind::convolution_auto) CHECK(this->set_alg_kind(alg_kind::convolution_direct)); return status; } jit_conv_conf_t jcp_; }; jit_avx512_core_x8s8s32x_convolution_fwd_t(const pd_t *apd, const input_vector &inputs, const output_vector &outputs) : cpu_primitive_t(apd, inputs, outputs) { kernel_ = new jit_avx512_core_x8s8s32x_fwd_kernel(pd()->jcp_, *pd()->attr()); } ~jit_avx512_core_x8s8s32x_convolution_fwd_t() { delete kernel_; } typedef typename prec_traits::type src_data_t; typedef typename prec_traits::type wei_data_t; typedef typename prec_traits::type dst_data_t; virtual void execute(event_t *e) const { const auto &jcp = pd()->jcp_; if (pd()->ndims() == 3) execute_forward_1d(); else if (jcp.is_depthwise) execute_forward_2d_dw(); else execute_forward_2d(); e->set_state(event_t::ready); } private: void execute_forward_1d() const; void execute_forward_2d() const; void execute_forward_2d_dw() const; const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); } jit_avx512_core_x8s8s32x_fwd_kernel *kernel_; }; } } } #endif // vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s