host_conv.hpp 16.5 KB
Newer Older
1
#pragma once
Chao Liu's avatar
Chao Liu committed
2
#include "host_tensor.hpp"
3

Jing Zhang's avatar
Jing Zhang committed
4
5
6
7
8
9
10
11
12
13
14
15
template <typename T>
inline auto activ(T v, const ck::index_t activ_type)
{
    switch(activ_type)
    {
    case 0: return v;
    case 1: return (v >= 0 ? v : 0);
    case 2: return (1 / (1 + exp(-v)));
    default: throw std::runtime_error("unsupported activ type"); break;
    }
}

zjing14's avatar
zjing14 committed
16
17
18
19
20
21
22
template <typename TIn,
          typename TWei,
          typename TOut,
          typename ConvStrides,
          typename ConvDilations,
          typename InLeftPads,
          typename InRightPads>
23
24
25
26
27
28
void host_direct_convolution(const Tensor<TIn>& in,
                             const Tensor<TWei>& wei,
                             Tensor<TOut>& out,
                             const ConvStrides& conv_strides,
                             const ConvDilations& conv_dilations,
                             const InLeftPads& in_left_pads,
Chao Liu's avatar
tidy  
Chao Liu committed
29
                             const InRightPads&,
Jing Zhang's avatar
Jing Zhang committed
30
31
                             const ConvTensorLayout layout = ConvTensorLayout::NCHW,
                             const ck::index_t activ_type  = 0)
32
33
34
{
    using namespace ck;

35
36
    constexpr auto I0 = Number<0>{};
    constexpr auto I1 = Number<1>{};
37

38
    auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
39
        double v = 0;
40
        for(int c = 0; c < wei.mDesc.GetLengths()[1]; ++c)
41
        {
42
            for(int y = 0; y < wei.mDesc.GetLengths()[2]; ++y)
43
            {
44
45
                int hi = ho * conv_strides[I0] + y * conv_dilations[I0] - in_left_pads[I0];
                for(int x = 0; x < wei.mDesc.GetLengths()[3]; ++x)
46
                {
47
48
49
                    int wi = wo * conv_strides[I1] + x * conv_dilations[I1] - in_left_pads[I1];
                    if(hi >= 0 && hi < in.mDesc.GetLengths()[2] && wi >= 0 &&
                       wi < in.mDesc.GetLengths()[3])
50
                    {
51
52
                        v += static_cast<const double>(in(n, c, hi, wi)) *
                             static_cast<const double>(wei(k, c, y, x));
53
54
55
56
                    }
                }
            }
        }
Jing Zhang's avatar
Jing Zhang committed
57
        out(n, k, ho, wo) = activ(v, activ_type);
58
59
    };

60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
    auto f_nhwc = [&](auto n, auto ho, auto wo, auto k) {
        double v = 0;
        for(int c = 0; c < wei.mDesc.GetLengths()[3]; ++c)
        {
            for(int y = 0; y < wei.mDesc.GetLengths()[1]; ++y)
            {
                int hi = ho * conv_strides[I0] + y * conv_dilations[I0] - in_left_pads[I0];
                for(int x = 0; x < wei.mDesc.GetLengths()[2]; ++x)
                {
                    int wi = wo * conv_strides[I1] + x * conv_dilations[I1] - in_left_pads[I1];
                    if(hi >= 0 && hi < in.mDesc.GetLengths()[1] && wi >= 0 &&
                       wi < in.mDesc.GetLengths()[2])
                    {
                        v += static_cast<const double>(in(n, hi, wi, c)) *
                             static_cast<const double>(wei(k, y, x, c));
                    }
                }
            }
        }
Jing Zhang's avatar
Jing Zhang committed
79
        out(n, ho, wo, k) = activ(v, activ_type);
80
    };
81

Chao Liu's avatar
tidy  
Chao Liu committed
82
    if(layout == ConvTensorLayout::NCHW)
83
84
85
86
87
88
    {
        make_ParallelTensorFunctor(f_nchw,
                                   out.mDesc.GetLengths()[0],
                                   out.mDesc.GetLengths()[1],
                                   out.mDesc.GetLengths()[2],
                                   out.mDesc.GetLengths()[3])(std::thread::hardware_concurrency());
Chao Liu's avatar
tidy  
Chao Liu committed
89
90
91
    }
    else if(layout == ConvTensorLayout::NHWC)
    {
92
93
94
95
96
        make_ParallelTensorFunctor(f_nhwc,
                                   out.mDesc.GetLengths()[0],
                                   out.mDesc.GetLengths()[1],
                                   out.mDesc.GetLengths()[2],
                                   out.mDesc.GetLengths()[3])(std::thread::hardware_concurrency());
Chao Liu's avatar
tidy  
Chao Liu committed
97
98
99
100
    }
    else
    {
        throw std::runtime_error("wrong! not supported layout");
101
    }
102
103
}

zjing14's avatar
zjing14 committed
104
template <typename TIn, typename TWei, typename TOut, typename InLeftPads, typename InRightPads>
105
106
107
void host_winograd_3x3_convolution(const Tensor<TIn>& in_nchw,
                                   const Tensor<TWei>& wei_kcyx,
                                   Tensor<TOut>& out_nkhw,
108
109
                                   InLeftPads,
                                   InRightPads)
110
111
112
113
114
115
{
    using namespace ck;

    constexpr std::size_t HoPerTile = 2;
    constexpr std::size_t WoPerTile = 2;

Chao Liu's avatar
tidy  
Chao Liu committed
116
117
    std::size_t N = in_nchw.mDesc.GetLengths()[0];
    std::size_t C = in_nchw.mDesc.GetLengths()[1];
118
119
120
121
122

    std::size_t K = wei_kcyx.mDesc.GetLengths()[0];
    std::size_t Y = wei_kcyx.mDesc.GetLengths()[2];
    std::size_t X = wei_kcyx.mDesc.GetLengths()[3];

Chao Liu's avatar
tidy  
Chao Liu committed
123
124
    std::size_t Ho = out_nkhw.mDesc.GetLengths()[2];
    std::size_t Wo = out_nkhw.mDesc.GetLengths()[3];
125

126
127
    index_t h_pad_low = InLeftPads{}.Get(Number<0>{});
    index_t w_pad_low = InLeftPads{}.Get(Number<1>{});
128
129
130
131

    std::size_t HiPerTile = HoPerTile + Y - 1;
    std::size_t WiPerTile = WoPerTile + X - 1;

Chao Liu's avatar
tidy  
Chao Liu committed
132
133
    std::size_t HTile = (Ho + HoPerTile - 1) / HoPerTile;
    std::size_t WTile = (Wo + WoPerTile - 1) / WoPerTile;
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
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322

    Tensor<double> in_hold({N, C, HTile, WTile, HiPerTile, WiPerTile});
    Tensor<double> in_transform({N, C, HTile, WTile, HiPerTile, WiPerTile});
    Tensor<double> wei_transform({K, C, HiPerTile, WiPerTile});
    Tensor<double> out_transform({N, K, HTile, WTile, HiPerTile, HiPerTile});
    Tensor<double> out_hold({N, K, HTile, WTile, HoPerTile, WoPerTile});

    auto f_in_hold = [&](auto n, auto c, auto htile, auto wtile) {
        for(int j = 0; j < HiPerTile; ++j)
        {
            int hi = HoPerTile * htile + j - h_pad_low;
            for(int i = 0; i < WiPerTile; ++i)
            {
                int wi = WoPerTile * wtile + i - w_pad_low;

                if(hi >= 0 && hi < in_nchw.mDesc.GetLengths()[2] && wi >= 0 &&
                   wi < in_nchw.mDesc.GetLengths()[3])
                {
                    in_hold(n, c, htile, wtile, j, i) = in_nchw(n, c, hi, wi);
                }
                else
                {
                    in_hold(n, c, htile, wtile, j, i) = TIn(0);
                }
            }
        }
    };

    auto f_in_transform = [&](auto n, auto c, auto htile, auto wtile) {
        in_transform(n, c, htile, wtile, 0, 0) =
            in_hold(n, c, htile, wtile, 0, 0) - in_hold(n, c, htile, wtile, 0, 2) -
            in_hold(n, c, htile, wtile, 2, 0) + in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 0, 1) =
            in_hold(n, c, htile, wtile, 0, 1) + in_hold(n, c, htile, wtile, 0, 2) -
            in_hold(n, c, htile, wtile, 2, 1) - in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 0, 2) =
            -in_hold(n, c, htile, wtile, 0, 1) + in_hold(n, c, htile, wtile, 0, 2) +
            in_hold(n, c, htile, wtile, 2, 1) - in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 0, 3) =
            in_hold(n, c, htile, wtile, 0, 1) - in_hold(n, c, htile, wtile, 0, 3) -
            in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 3);

        in_transform(n, c, htile, wtile, 1, 0) =
            in_hold(n, c, htile, wtile, 1, 0) - in_hold(n, c, htile, wtile, 1, 2) +
            in_hold(n, c, htile, wtile, 2, 0) - in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 1, 1) =
            in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 2) +
            in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 1, 2) =
            -in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 2) -
            in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 1, 3) =
            in_hold(n, c, htile, wtile, 1, 1) - in_hold(n, c, htile, wtile, 1, 3) +
            in_hold(n, c, htile, wtile, 2, 1) - in_hold(n, c, htile, wtile, 2, 3);

        in_transform(n, c, htile, wtile, 2, 0) =
            -in_hold(n, c, htile, wtile, 1, 0) + in_hold(n, c, htile, wtile, 1, 2) +
            in_hold(n, c, htile, wtile, 2, 0) - in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 2, 1) =
            -in_hold(n, c, htile, wtile, 1, 1) - in_hold(n, c, htile, wtile, 1, 2) +
            in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 2, 2) =
            in_hold(n, c, htile, wtile, 1, 1) - in_hold(n, c, htile, wtile, 1, 2) -
            in_hold(n, c, htile, wtile, 2, 1) + in_hold(n, c, htile, wtile, 2, 2);
        in_transform(n, c, htile, wtile, 2, 3) =
            -in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 3) +
            in_hold(n, c, htile, wtile, 2, 1) - in_hold(n, c, htile, wtile, 2, 3);

        in_transform(n, c, htile, wtile, 3, 0) =
            in_hold(n, c, htile, wtile, 1, 0) - in_hold(n, c, htile, wtile, 1, 2) -
            in_hold(n, c, htile, wtile, 3, 0) + in_hold(n, c, htile, wtile, 3, 2);
        in_transform(n, c, htile, wtile, 3, 1) =
            in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 2) -
            in_hold(n, c, htile, wtile, 3, 1) - in_hold(n, c, htile, wtile, 3, 2);
        in_transform(n, c, htile, wtile, 3, 2) =
            -in_hold(n, c, htile, wtile, 1, 1) + in_hold(n, c, htile, wtile, 1, 2) +
            in_hold(n, c, htile, wtile, 3, 1) - in_hold(n, c, htile, wtile, 3, 2);
        in_transform(n, c, htile, wtile, 3, 3) =
            in_hold(n, c, htile, wtile, 1, 1) - in_hold(n, c, htile, wtile, 1, 3) -
            in_hold(n, c, htile, wtile, 3, 1) + in_hold(n, c, htile, wtile, 3, 3);
    };

    auto f_wei_transform = [&](auto k, auto c) {
        wei_transform(k, c, 0, 0) = double(wei_kcyx(k, c, 0, 0));
        wei_transform(k, c, 0, 1) = 0.5 * double(wei_kcyx(k, c, 0, 0)) +
                                    0.5 * double(wei_kcyx(k, c, 0, 1)) +
                                    0.5 * double(wei_kcyx(k, c, 0, 2));
        wei_transform(k, c, 0, 2) = 0.5 * double(wei_kcyx(k, c, 0, 0)) -
                                    0.5 * double(wei_kcyx(k, c, 0, 1)) +
                                    0.5 * double(wei_kcyx(k, c, 0, 2));
        wei_transform(k, c, 0, 3) = double(wei_kcyx(k, c, 0, 2));

        wei_transform(k, c, 1, 0) = 0.5 * double(wei_kcyx(k, c, 0, 0)) +
                                    0.5 * double(wei_kcyx(k, c, 1, 0)) +
                                    0.5 * double(wei_kcyx(k, c, 2, 0));
        wei_transform(k, c, 1, 1) =
            0.25 * double(wei_kcyx(k, c, 0, 0)) + 0.25 * double(wei_kcyx(k, c, 0, 1)) +
            0.25 * double(wei_kcyx(k, c, 0, 2)) + 0.25 * double(wei_kcyx(k, c, 1, 0)) +
            0.25 * double(wei_kcyx(k, c, 1, 1)) + 0.25 * double(wei_kcyx(k, c, 1, 2)) +
            0.25 * double(wei_kcyx(k, c, 2, 0)) + 0.25 * double(wei_kcyx(k, c, 2, 1)) +
            0.25 * double(wei_kcyx(k, c, 2, 2));
        wei_transform(k, c, 1, 2) =
            0.25 * double(wei_kcyx(k, c, 0, 0)) - 0.25 * double(wei_kcyx(k, c, 0, 1)) +
            0.25 * double(wei_kcyx(k, c, 0, 2)) + 0.25 * double(wei_kcyx(k, c, 1, 0)) -
            0.25 * double(wei_kcyx(k, c, 1, 1)) + 0.25 * double(wei_kcyx(k, c, 1, 2)) +
            0.25 * double(wei_kcyx(k, c, 2, 0)) - 0.25 * double(wei_kcyx(k, c, 2, 1)) +
            0.25 * double(wei_kcyx(k, c, 2, 2));
        wei_transform(k, c, 1, 3) = 0.5 * double(wei_kcyx(k, c, 0, 2)) +
                                    0.5 * double(wei_kcyx(k, c, 1, 2)) +
                                    0.5 * double(wei_kcyx(k, c, 2, 2));

        wei_transform(k, c, 2, 0) = 0.5 * double(wei_kcyx(k, c, 0, 0)) -
                                    0.5 * double(wei_kcyx(k, c, 1, 0)) +
                                    0.5 * double(wei_kcyx(k, c, 2, 0));
        wei_transform(k, c, 2, 1) =
            0.25 * double(wei_kcyx(k, c, 0, 0)) + 0.25 * double(wei_kcyx(k, c, 0, 1)) +
            0.25 * double(wei_kcyx(k, c, 0, 2)) - 0.25 * double(wei_kcyx(k, c, 1, 0)) -
            0.25 * double(wei_kcyx(k, c, 1, 1)) - 0.25 * double(wei_kcyx(k, c, 1, 2)) +
            0.25 * double(wei_kcyx(k, c, 2, 0)) + 0.25 * double(wei_kcyx(k, c, 2, 1)) +
            0.25 * double(wei_kcyx(k, c, 2, 2));
        wei_transform(k, c, 2, 2) =
            0.25 * double(wei_kcyx(k, c, 0, 0)) - 0.25 * double(wei_kcyx(k, c, 0, 1)) +
            0.25 * double(wei_kcyx(k, c, 0, 2)) - 0.25 * double(wei_kcyx(k, c, 1, 0)) +
            0.25 * double(wei_kcyx(k, c, 1, 1)) - 0.25 * double(wei_kcyx(k, c, 1, 2)) +
            0.25 * double(wei_kcyx(k, c, 2, 0)) - 0.25 * double(wei_kcyx(k, c, 2, 1)) +
            0.25 * double(wei_kcyx(k, c, 2, 2));
        wei_transform(k, c, 2, 3) = 0.5 * double(wei_kcyx(k, c, 0, 2)) -
                                    0.5 * double(wei_kcyx(k, c, 1, 2)) +
                                    0.5 * double(wei_kcyx(k, c, 2, 2));

        wei_transform(k, c, 3, 0) = double(wei_kcyx(k, c, 2, 0));
        wei_transform(k, c, 3, 1) = 0.5 * double(wei_kcyx(k, c, 2, 0)) +
                                    0.5 * double(wei_kcyx(k, c, 2, 1)) +
                                    0.5 * double(wei_kcyx(k, c, 2, 2));
        wei_transform(k, c, 3, 2) = 0.5 * double(wei_kcyx(k, c, 2, 0)) -
                                    0.5 * double(wei_kcyx(k, c, 2, 1)) +
                                    0.5 * double(wei_kcyx(k, c, 2, 2));
        wei_transform(k, c, 3, 3) = double(wei_kcyx(k, c, 2, 2));
    };

    auto f_out_transform = [&](auto n, auto k, auto htile, auto wtile) {
        for(int j = 0; j < HiPerTile; ++j)
        {
            for(int i = 0; i < WiPerTile; ++i)
            {
                double v = 0;
                for(int c = 0; c < C; ++c)
                {
                    v += in_transform(n, c, htile, wtile, j, i) * wei_transform(k, c, j, i);
                }

                out_transform(n, k, htile, wtile, j, i) = v;
            }
        }
    };

    auto f_out_hold = [&](auto n, auto k, auto htile, auto wtile) {
        out_hold(n, k, htile, wtile, 0, 0) =
            out_transform(n, k, htile, wtile, 0, 0) + out_transform(n, k, htile, wtile, 0, 1) +
            out_transform(n, k, htile, wtile, 0, 2) + out_transform(n, k, htile, wtile, 1, 0) +
            out_transform(n, k, htile, wtile, 1, 1) + out_transform(n, k, htile, wtile, 1, 2) +
            out_transform(n, k, htile, wtile, 2, 0) + out_transform(n, k, htile, wtile, 2, 1) +
            out_transform(n, k, htile, wtile, 2, 2);
        out_hold(n, k, htile, wtile, 0, 1) =
            out_transform(n, k, htile, wtile, 0, 1) - out_transform(n, k, htile, wtile, 0, 2) -
            out_transform(n, k, htile, wtile, 0, 3) + out_transform(n, k, htile, wtile, 1, 1) -
            out_transform(n, k, htile, wtile, 1, 2) - out_transform(n, k, htile, wtile, 1, 3) +
            out_transform(n, k, htile, wtile, 2, 1) - out_transform(n, k, htile, wtile, 2, 2) -
            out_transform(n, k, htile, wtile, 2, 3);
        out_hold(n, k, htile, wtile, 1, 0) =
            out_transform(n, k, htile, wtile, 1, 0) + out_transform(n, k, htile, wtile, 1, 1) +
            out_transform(n, k, htile, wtile, 1, 2) - out_transform(n, k, htile, wtile, 2, 0) -
            out_transform(n, k, htile, wtile, 2, 1) - out_transform(n, k, htile, wtile, 2, 2) -
            out_transform(n, k, htile, wtile, 3, 0) - out_transform(n, k, htile, wtile, 3, 1) -
            out_transform(n, k, htile, wtile, 3, 2);
        out_hold(n, k, htile, wtile, 1, 1) =
            out_transform(n, k, htile, wtile, 1, 1) - out_transform(n, k, htile, wtile, 1, 2) -
            out_transform(n, k, htile, wtile, 1, 3) - out_transform(n, k, htile, wtile, 2, 1) +
            out_transform(n, k, htile, wtile, 2, 2) + out_transform(n, k, htile, wtile, 2, 3) -
            out_transform(n, k, htile, wtile, 3, 1) + out_transform(n, k, htile, wtile, 3, 2) +
            out_transform(n, k, htile, wtile, 3, 3);
    };

    auto f_out = [&](auto n, auto k, auto htile, auto wtile) {
        for(int j = 0; j < HoPerTile; ++j)
        {
            std::size_t ho = HoPerTile * htile + j;
            for(int i = 0; i < WoPerTile; ++i)
            {
Chao Liu's avatar
Chao Liu committed
323
                std::size_t wo         = WoPerTile * wtile + i;
324
325
326
327
328
329
330
331
332
333
334
335
336
337
                out_nkhw(n, k, ho, wo) = out_hold(n, k, htile, wtile, j, i);
            }
        }
    };

    std::size_t num_thread = std::thread::hardware_concurrency();

    make_ParallelTensorFunctor(f_in_hold, N, C, HTile, WTile)(num_thread);
    make_ParallelTensorFunctor(f_in_transform, N, C, HTile, WTile)(num_thread);
    make_ParallelTensorFunctor(f_wei_transform, K, C)(num_thread);
    make_ParallelTensorFunctor(f_out_transform, N, K, HTile, WTile)(num_thread);
    make_ParallelTensorFunctor(f_out_hold, N, K, HTile, WTile)(num_thread);
    make_ParallelTensorFunctor(f_out, N, K, HTile, WTile)(num_thread);
}