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/*******************************************************************************
* 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_REF_SOFTMAX_HPP
#define CPU_REF_SOFTMAX_HPP
#include <assert.h>
#include "c_types_map.hpp"
#include "memory_tracking.hpp"
#include "type_helpers.hpp"
#include "utils.hpp"
#include "cpu_softmax_pd.hpp"
#include "cpu_primitive.hpp"
namespace mkldnn {
namespace impl {
namespace cpu {
template <impl::data_type_t data_type>
struct ref_softmax_fwd_t: public cpu_primitive_t {
struct pd_t: public cpu_softmax_fwd_pd_t {
using cpu_softmax_fwd_pd_t::cpu_softmax_fwd_pd_t;
DECLARE_COMMON_PD_T("ref:any", ref_softmax_fwd_t);
status_t init() {
bool ok = true
&& is_fwd()
&& src_md()->data_type == data_type
&& attr()->has_default_values();
if (!ok) return status::unimplemented;
init_scratchpad();
return status::success;
}
private:
void init_scratchpad() {
const int inner_size = utils::array_product(
desc()->data_desc.dims + desc()->softmax_axis + 1,
desc()->data_desc.ndims - desc()->softmax_axis - 1);
if (inner_size > 1) {
auto scratchpad = scratchpad_registry().registrar();
scratchpad.book(memory_tracking::names::key_softmax_reduction,
sizeof(data_t) * 2 * inner_size);
}
}
};
ref_softmax_fwd_t(const pd_t *apd): cpu_primitive_t(apd)
{
auto ndims = pd()->desc()->data_desc.ndims;
auto dims = pd()->desc()->data_desc.dims;
auto axis = pd()->desc()->softmax_axis;
outer_size_ = utils::array_product(dims, axis);
channels_ = dims[axis];
inner_size_ = utils::array_product(dims + axis + 1, ndims - axis - 1);
const memory_desc_wrapper data_d(pd()->src_md());
bool no_axis_blocking = true;
for (int iblk = 0; iblk < data_d.blocking_desc().inner_nblks; ++iblk)
if (data_d.blocking_desc().inner_idxs[iblk] == axis)
no_axis_blocking = false;
use_dense_ = inner_size_ == 1 && data_d.is_dense()
&& no_axis_blocking
&& data_d.blocking_desc().strides[axis] == 1;
}
typedef typename prec_traits<data_type>::type data_t;
virtual status_t execute(const exec_ctx_t &ctx) const override {
if (use_dense_)
execute_forward_dense(ctx);
else
execute_forward_generic(ctx);
return status::success;
}
private:
void execute_forward_dense(const exec_ctx_t &ctx) const;
void execute_forward_generic(const exec_ctx_t &ctx) const;
void _max(int n, const data_t *x, data_t *max_data) const;
void _sub(int n, data_t alpha, const data_t *x, data_t *y) const;
void _exp(int n, const data_t *a, data_t *r) const;
void _sum(int n, const data_t *x, data_t *sum_data) const;
void _scal(int n, data_t alpha, data_t *x) const;
const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
bool use_dense_;
int outer_size_, channels_, inner_size_;
};
template <impl::data_type_t data_type>
struct ref_softmax_bwd_t: public cpu_primitive_t {
struct pd_t: public cpu_softmax_bwd_pd_t {
using cpu_softmax_bwd_pd_t::cpu_softmax_bwd_pd_t;
DECLARE_COMMON_PD_T("ref:any", ref_softmax_bwd_t);
status_t init() {
bool ok = true
&& !is_fwd()
&& utils::everyone_is(data_type,
dst_md()->data_type,
diff_src_md()->data_type)
&& attr()->has_default_values();
if (!ok) return status::unimplemented;
return status::success;
}
};
ref_softmax_bwd_t(const pd_t *apd): cpu_primitive_t(apd) {
auto dims = pd()->desc()->diff_desc.dims;
auto axis = pd()->desc()->softmax_axis;
auto ndims = pd()->desc()->diff_desc.ndims;
outer_size_ = utils::array_product(dims, axis);
channels_ = dims[axis];
inner_size_ = utils::array_product(dims + axis + 1, ndims - axis - 1);
const memory_desc_wrapper data_d(pd()->dst_md());
const memory_desc_wrapper diff_d(pd()->diff_dst_md());
bool no_axis_blocking = true;
for (int iblk = 0; iblk < diff_d.blocking_desc().inner_nblks; ++iblk)
if (diff_d.blocking_desc().inner_idxs[iblk] == axis)
no_axis_blocking = false;
use_dense_ = true
&& inner_size_ == 1
&& diff_d == data_d
&& diff_d.is_dense()
&& no_axis_blocking
&& diff_d.blocking_desc().strides[axis] == 1;
}
typedef typename prec_traits<data_type>::type data_t;
virtual status_t execute(const exec_ctx_t &ctx) const override {
if (use_dense_)
execute_backward_dense(ctx);
else
execute_backward_generic(ctx);
return status::success;
}
private:
void execute_backward_dense(const exec_ctx_t &ctx) const;
void execute_backward_generic(const exec_ctx_t &ctx) const;
const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
bool use_dense_;
int outer_size_, channels_, inner_size_;
};
}
}
}
#endif
// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s
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