diff options
Diffstat (limited to 'inference-engine/thirdparty/mkl-dnn/src/cpu/jit_avx512_core_x8s8s32x_convolution.hpp')
| -rw-r--r-- | inference-engine/thirdparty/mkl-dnn/src/cpu/jit_avx512_core_x8s8s32x_convolution.hpp | 132 |
1 files changed, 132 insertions, 0 deletions
diff --git a/inference-engine/thirdparty/mkl-dnn/src/cpu/jit_avx512_core_x8s8s32x_convolution.hpp b/inference-engine/thirdparty/mkl-dnn/src/cpu/jit_avx512_core_x8s8s32x_convolution.hpp new file mode 100644 index 000000000..6ac59f996 --- /dev/null +++ b/inference-engine/thirdparty/mkl-dnn/src/cpu/jit_avx512_core_x8s8s32x_convolution.hpp @@ -0,0 +1,132 @@ +/******************************************************************************* +* 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 "cpu_convolution_pd.hpp" +#include "cpu_engine.hpp" +#include "jit_transpose_src_utils.hpp" +#include "cpu_reducer.hpp" +#include "cpu_barrier.hpp" + +#include "jit_avx512_core_x8s8s32x_conv_kernel.hpp" + +namespace mkldnn { +namespace impl { +namespace cpu { + +template <bool with_relu, impl::data_type_t src_type, impl::data_type_t dst_type> +struct _jit_avx512_core_x8s8s32x_convolution_fwd_t : public cpu_primitive_t { + struct pd_t : public _cpu_convolution_fwd_pd_t<with_relu> { + pd_t(engine_t *engine, const typename pd_t::base_desc_t *adesc, + const primitive_attr_t *attr, + const typename pd_t::base_class *hint_fwd_pd) + : _cpu_convolution_fwd_pd_t<with_relu>(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<with_relu, src_type, + dst_type>); + + virtual status_t init() override + { + using namespace prop_kind; + assert(this->engine()->kind() == engine_kind::cpu); + bool ok = true + && utils::one_of(this->cdesc_().prop_kind, forward_training, + forward_inference) + && this->cdesc_().alg_kind == alg_kind::convolution_direct + && !this->has_zero_dim_memory() + && this->cdesc_().src_desc.data_type == src_type + && this->cdesc_().dst_desc.data_type == dst_type + && IMPLICATION(this->with_bias(), utils::one_of( + this->cdesc_().bias_desc.data_type, data_type::f32, + data_type::s32, data_type::s8, data_type::u8)) + && this->cdesc_().accum_data_type == data_type::s32; + if (!ok) + return status::unimplemented; + + return jit_avx512_core_x8s8s32x_fwd_kernel::init_conf( + jcp_, this->cdesc_(), this->src_pd_, this->weights_pd_, + this->dst_pd_,this->bias_pd_, *this->attr(), + mkldnn_get_max_threads(), + with_relu, this->negative_slope()); + } + + jit_conv_conf_t jcp_; + }; + + _jit_avx512_core_x8s8s32x_convolution_fwd_t(const pd_t *pd, + const input_vector &inputs, const output_vector &outputs) + : cpu_primitive_t(&conf_, inputs, outputs), conf_(*pd) + , local_scales_(nullptr) + { + kernel_ = new jit_avx512_core_x8s8s32x_fwd_kernel(conf_.jcp_, + *conf_.attr()); + if (conf_.jcp_.signed_input && conf_.jcp_.ver != ver_vnni) { + size_t scales_size = (conf_.attr()->output_scales_.count_ == 1) + ? 16 + : conf_.attr()->output_scales_.count_; + local_scales_ = (float *)malloc(sizeof(float) * scales_size, 64); + for (size_t i = 0; i < scales_size; i++) { + local_scales_[i] = conf_.attr()->output_scales_.scales_[i] * + (1.f / conf_.jcp_.wei_adj_scale); + } + } + } + + ~_jit_avx512_core_x8s8s32x_convolution_fwd_t() { + delete kernel_; + if (local_scales_) free(local_scales_); + }; + + 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; + + virtual void execute(event_t *e) + { + execute_forward(); + e->set_state(event_t::ready); + } + +private: + void execute_forward(); + pd_t conf_; + jit_avx512_core_x8s8s32x_fwd_kernel *kernel_; + float *local_scales_; +}; + +template <impl::data_type_t src_type, impl::data_type_t dst_type> +using jit_avx512_core_x8s8s32x_convolution_fwd_t = + _jit_avx512_core_x8s8s32x_convolution_fwd_t<false, src_type, dst_type>; + +template <impl::data_type_t src_type, impl::data_type_t dst_type> +using jit_avx512_core_x8s8s32x_convolution_relu_t = + _jit_avx512_core_x8s8s32x_convolution_fwd_t<true, src_type, dst_type>; + +} +} +} + +#endif + +// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s |