ncnn / src /layer /cast.cpp
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// Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2019 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// 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.
#include "cast.h"
namespace ncnn {
Cast::Cast()
{
one_blob_only = true;
support_inplace = false;
support_packing = true;
}
int Cast::load_param(const ParamDict& pd)
{
type_from = pd.get(0, 0);
type_to = pd.get(1, 0);
return 0;
}
// round to nearest
signed char float32_to_int8(float value)
{
float tmp;
if (value >= 0.f)
tmp = value + 0.5f;
else
tmp = value - 0.5f;
if (tmp > 127)
return 127;
if (tmp < -128)
return -128;
return static_cast<signed char>(tmp);
}
int Cast::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const
{
if (type_from == type_to)
{
top_blob = bottom_blob;
return 0;
}
int w = bottom_blob.w;
int h = bottom_blob.h;
int d = bottom_blob.d;
int channels = bottom_blob.c;
int dims = bottom_blob.dims;
size_t elemsize = bottom_blob.elemsize;
int elempack = bottom_blob.elempack;
size_t out_elemsize = elemsize;
if (type_to == 1)
{
// float32
out_elemsize = 4 * elempack;
}
else if (type_to == 2)
{
// float16
out_elemsize = 2 * elempack;
}
else if (type_to == 3)
{
// int8
out_elemsize = elempack;
}
else if (type_to == 4)
{
// bfloat16
out_elemsize = 2 * elempack;
}
if (dims == 1)
{
top_blob.create(w, out_elemsize, elempack, opt.blob_allocator);
}
else if (dims == 2)
{
top_blob.create(w, h, out_elemsize, elempack, opt.blob_allocator);
}
else if (dims == 3)
{
top_blob.create(w, h, channels, out_elemsize, elempack, opt.blob_allocator);
}
else if (dims == 4)
{
top_blob.create(w, h, d, channels, out_elemsize, elempack, opt.blob_allocator);
}
if (top_blob.empty())
return -100;
int size = w * h * d * elempack;
if (type_from == 1 && type_to == 2)
{
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < channels; q++)
{
const float* ptr = bottom_blob.channel(q);
unsigned short* outptr = top_blob.channel(q);
for (int i = 0; i < size; i++)
{
outptr[i] = float32_to_float16(ptr[i]);
}
}
}
if (type_from == 2 && type_to == 1)
{
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < channels; q++)
{
const unsigned short* ptr = bottom_blob.channel(q);
float* outptr = top_blob.channel(q);
for (int i = 0; i < size; i++)
{
outptr[i] = float16_to_float32(ptr[i]);
}
}
}
if (type_from == 3 && type_to == 1)
{
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < channels; q++)
{
const signed char* ptr = bottom_blob.channel(q);
float* outptr = top_blob.channel(q);
for (int i = 0; i < size; i++)
{
outptr[i] = (float)ptr[i];
}
}
}
if (type_from == 1 && type_to == 4)
{
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < channels; q++)
{
const float* ptr = bottom_blob.channel(q);
unsigned short* outptr = top_blob.channel(q);
for (int i = 0; i < size; i++)
{
outptr[i] = float32_to_bfloat16(ptr[i]);
}
}
}
if (type_from == 4 && type_to == 1)
{
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < channels; q++)
{
const unsigned short* ptr = bottom_blob.channel(q);
float* outptr = top_blob.channel(q);
for (int i = 0; i < size; i++)
{
outptr[i] = bfloat16_to_float32(ptr[i]);
}
}
}
// TODO more cast type
return 0;
}
} // namespace ncnn