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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_REF_SHUFFLE_HPP
#define CPU_REF_SHUFFLE_HPP
#include <assert.h>
#include "c_types_map.hpp"
#include "type_helpers.hpp"
#include "utils.hpp"
#include "cpu_shuffle_pd.hpp"
#include "cpu_primitive.hpp"
namespace mkldnn {
namespace impl {
namespace cpu {
template<int data_type_size>
struct ref_shuffle_t : public cpu_primitive_t {
using shuffle_class = ref_shuffle_t<data_type_size>;
struct pd_t: public cpu_shuffle_pd_t {
using cpu_shuffle_pd_t::cpu_shuffle_pd_t;
DECLARE_COMMON_PD_T("ref:any", shuffle_class);
status_t init() {
using namespace format_tag;
bool ok = true
&& data_type_size
== types::data_type_size(data_md()->data_type);
if (!ok) return status::unimplemented;
if (ndims() == 5) {
dat_tag_ = memory_desc_matches_one_of_tag(
*data_md(), nCdhw16c, nCdhw8c, ncdhw, ndhwc);
} else if (ndims() == 4) {
dat_tag_ = memory_desc_matches_one_of_tag(
*data_md(), nChw16c, nChw8c, nchw, nhwc);
} else
dat_tag_ = any;
return status::success;
}
format_tag_t dat_tag_;
};
ref_shuffle_t(const pd_t *apd): cpu_primitive_t(apd) {
const int axis_size = pd()->axis_size();
const int group_size = pd()->group_size();
const int transpose_row = pd()->is_fwd() ? group_size
: axis_size / group_size;
const int transpose_col = pd()->is_fwd() ? axis_size / group_size
: group_size;
rev_transposed_ = (int *)malloc(axis_size * sizeof(int), 64);
parallel_nd(transpose_col, transpose_row, [&](int i, int j) {
rev_transposed_[j * transpose_col + i] = i * transpose_row + j;
});
}
~ref_shuffle_t() { free(rev_transposed_); }
typedef typename typesize_traits<data_type_size>::type data_t;
virtual status_t execute(const exec_ctx_t &ctx) const override {
using namespace format_tag;
switch (pd()->dat_tag_) {
case nCdhw16c: execute_<nCdhw16c>(ctx); break;
case nChw16c: execute_<nChw16c>(ctx); break;
case nCdhw8c: execute_<nCdhw8c>(ctx); break;
case nChw8c: execute_<nChw8c>(ctx); break;
case ncdhw: execute_<ncdhw>(ctx); break;
case nchw: execute_<nchw>(ctx); break;
case ndhwc: execute_<ndhwc>(ctx); break;
case nhwc: execute_<nhwc>(ctx); break;
default: execute_<any>(ctx); break;
}
return status::success;
}
private:
template<format_tag_t tag>
void execute_(const exec_ctx_t &ctx) const;
const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
int *rev_transposed_;
};
}
}
}
#endif
// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s
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