virtualx-engine/thirdparty/oidn/mkl-dnn/src/cpu/ncsp_batch_normalization.hpp

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/*******************************************************************************
* Copyright 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_NCSP_BATCH_NORMALIZATION_HPP
#define CPU_NCSP_BATCH_NORMALIZATION_HPP
#include <assert.h>
#include "c_types_map.hpp"
#include "memory_tracking.hpp"
#include "type_helpers.hpp"
#include "utils.hpp"
#include "cpu_batch_normalization_pd.hpp"
#include "cpu_primitive.hpp"
namespace mkldnn {
namespace impl {
namespace cpu {
struct ncsp_batch_normalization_fwd_t : public cpu_primitive_t {
struct pd_t : public cpu_batch_normalization_fwd_pd_t {
using cpu_batch_normalization_fwd_pd_t::cpu_batch_normalization_fwd_pd_t;
DECLARE_COMMON_PD_T("ncsp_bnorm:any", ncsp_batch_normalization_fwd_t);
status_t init() {
using namespace data_type;
using namespace prop_kind;
using namespace format_tag;
bool ok = true
&& is_fwd()
&& !has_zero_dim_memory()
&& src_md()->data_type == f32
&& IMPLICATION(use_scaleshift(), weights_md()->data_type == f32)
&& memory_desc_matches_one_of_tag(*src_md(), ncdhw, nchw, nc)
&& (attr()->has_default_values() || this->with_relu_post_op());
if (!ok) return status::unimplemented;
if (is_training() && fuse_bn_relu()) init_default_ws(8);
init_scratchpad();
return status::success;
}
private:
void init_scratchpad() {
using namespace memory_tracking::names;
auto scratchpad = scratchpad_registry().registrar();
if (!stats_is_src()) {
scratchpad.book(key_bnorm_reduction,
sizeof(data_t) * C() * mkldnn_get_max_threads());
if (!is_training()) {
scratchpad.book(key_bnorm_tmp_mean, sizeof(data_t) * C());
scratchpad.book(key_bnorm_tmp_var, sizeof(data_t) * C());
}
}
}
};
typedef typename prec_traits<data_type::f32>::type data_t;
ncsp_batch_normalization_fwd_t(const pd_t *apd): cpu_primitive_t(apd) {}
~ncsp_batch_normalization_fwd_t() {}
virtual status_t execute(const exec_ctx_t &ctx) const override {
execute_forward(ctx);
return status::success;
}
private:
void execute_forward(const exec_ctx_t &ctx) const;
const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
};
struct ncsp_batch_normalization_bwd_t : public cpu_primitive_t {
struct pd_t : public cpu_batch_normalization_bwd_pd_t {
using cpu_batch_normalization_bwd_pd_t::cpu_batch_normalization_bwd_pd_t;
DECLARE_COMMON_PD_T("ncsp_bnorm:any", ncsp_batch_normalization_bwd_t);
status_t init() {
using namespace data_type;
using namespace format_tag;
bool ok = true
&& is_bwd()
&& !has_zero_dim_memory()
&& utils::everyone_is(f32, src_md()->data_type,
diff_src_md()->data_type)
&& IMPLICATION(use_scaleshift(),
utils::everyone_is(f32,
weights_md()->data_type,
diff_weights_md()->data_type))
&& memory_desc_matches_one_of_tag(*src_md(), ncdhw, nchw, nc)
&& memory_desc_matches_one_of_tag(*diff_src_md(), ncdhw, nchw, nc)
&& attr()->has_default_values();
if (!ok) return status::unimplemented;
if (fuse_bn_relu()) {
init_default_ws(8);
if (!compare_ws(hint_fwd_pd_))
return status::unimplemented;
}
init_scratchpad();
return status::success;
}
private:
void init_scratchpad() {
using namespace memory_tracking::names;
auto scratchpad = scratchpad_registry().registrar();
scratchpad.book(key_bnorm_reduction,
sizeof(data_t) * 2 * C() * mkldnn_get_max_threads());
if (!(use_scaleshift() && desc()->prop_kind == prop_kind::backward))
scratchpad.book(key_bnorm_tmp_diff_ss,
sizeof(data_t) * 2 * C());
}
};
typedef typename prec_traits<data_type::f32>::type data_t;
ncsp_batch_normalization_bwd_t(const pd_t *apd): cpu_primitive_t(apd) {}
~ncsp_batch_normalization_bwd_t() {}
virtual status_t execute(const exec_ctx_t &ctx) const override {
execute_backward(ctx);
return status::success;
}
private:
void execute_backward(const exec_ctx_t &ctx) const;
const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
};
}
}
}
#endif
// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s