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be903e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2021 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_riscv.h"
#if __riscv_vector
#include <riscv_vector.h>
#endif // __riscv_vector
namespace ncnn {
Cast_riscv::Cast_riscv()
{
#if __riscv_vector
support_packing = true;
#if __riscv_zfh
support_fp16_storage = true;
#endif
#endif // __riscv_vector
}
int Cast_riscv::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 __riscv_vector && __riscv_zfh
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);
__fp16* outptr = top_blob.channel(q);
int n = size;
while (n > 0)
{
size_t vl = vsetvl_e32m8(n);
vfloat32m8_t _p = vle32_v_f32m8(ptr, vl);
vfloat16m4_t _outp = vfncvt_f_f_w_f16m4(_p, vl);
vse16_v_f16m4(outptr, _outp, vl);
ptr += vl;
outptr += vl;
n -= vl;
}
}
}
if (type_from == 2 && type_to == 1)
{
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q < channels; q++)
{
const __fp16* ptr = bottom_blob.channel(q);
float* outptr = top_blob.channel(q);
int n = size;
while (n > 0)
{
size_t vl = vsetvl_e16m4(n);
vfloat16m4_t _p = vle16_v_f16m4(ptr, vl);
vfloat32m8_t _outp = vfwcvt_f_f_v_f32m8(_p, vl);
vse32_v_f32m8(outptr, _outp, vl);
ptr += vl;
outptr += vl;
n -= vl;
}
}
}
#endif // __riscv_vector && __riscv_zfh
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];
}
}
}
// TODO more cast type
return Cast::forward(bottom_blob, top_blob, opt);
}
} // namespace ncnn
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