Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 1 | #include "gemm-microkernel-tester.h" |
| 2 | |
| 3 | #include <gtest/gtest.h> |
| 4 | |
| 5 | #include <algorithm> |
| 6 | #include <cassert> |
| 7 | #include <cmath> |
| 8 | #include <cstddef> |
| 9 | #include <cstdlib> |
| 10 | #include <functional> |
| 11 | #include <limits> |
| 12 | #include <numeric> |
| 13 | #include <random> |
| 14 | #include <vector> |
| 15 | |
| 16 | #include <fp16.h> |
| 17 | |
| 18 | #include <xnnpack.h> |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 19 | #include <xnnpack/allocator.h> |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 20 | #include <xnnpack/AlignedAllocator.h> |
| 21 | #include <xnnpack/pack.h> |
| 22 | #include <xnnpack/params-init.h> |
| 23 | #include <xnnpack/params.h> |
| 24 | #include <xnnpack/requantization.h> |
| 25 | |
| 26 | void GemmMicrokernelTester::Test( |
| 27 | xnn_qu8_gemm_minmax_ukernel_function gemm, |
| 28 | xnn_init_qu8_conv_minmax_params_fn init_params, |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 29 | xnn_qu8_requantize_fn requantize) const |
| 30 | { |
| 31 | ASSERT_LE(m(), mr()); |
| 32 | |
| 33 | std::random_device random_device; |
| 34 | auto rng = std::mt19937(random_device()); |
| 35 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 36 | auto u8rng = std::bind( |
| 37 | std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), std::ref(rng)); |
| 38 | |
| 39 | std::vector<uint8_t> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(uint8_t)); |
| 40 | std::vector<uint8_t> b(n() * k()); |
| 41 | std::vector<int32_t> bias(n()); |
| 42 | std::vector<uint8_t, AlignedAllocator<uint8_t, 64>> packed_w(packed_n() * packed_k() + packed_n() * sizeof(int32_t) / sizeof(uint8_t)); |
| 43 | std::vector<uint8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 44 | std::vector<int32_t> acc(m() * n()); |
| 45 | std::vector<uint8_t> c_ref(m() * n()); |
| 46 | |
| 47 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 48 | do { |
| 49 | std::generate(a.begin(), a.end(), std::ref(u8rng)); |
| 50 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 51 | do { |
| 52 | std::generate(b.begin(), b.end(), std::ref(u8rng)); |
| 53 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 54 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 55 | std::fill(c.begin(), c.end(), 0xA5); |
| 56 | |
| 57 | std::fill(packed_w.begin(), packed_w.end(), b_zero_point()); |
| 58 | const xnn_qu8_packing_params packing_params = { a_zero_point(), b_zero_point() }; |
| 59 | xnn_pack_qu8_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 60 | b.data(), bias.data(), packed_w.data(), 0, &packing_params); |
| 61 | |
| 62 | // Compute 32-bit results and output quantization arguments. |
| 63 | std::fill(acc.begin(), acc.end(), 0); |
| 64 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 65 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 66 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 67 | acc[m_index * n() + n_index] += |
| 68 | (int32_t(a[m_index * a_stride() + k_index]) - int32_t(a_zero_point())) * |
| 69 | (int32_t(b[n_index * k() + k_index]) - int32_t(b_zero_point())); |
| 70 | } |
| 71 | acc[m_index * n() + n_index] += bias[n_index]; |
| 72 | } |
| 73 | } |
| 74 | |
| 75 | const int32_t accumulated_min = *std::min_element(acc.cbegin(), acc.cend()); |
| 76 | const int32_t accumulated_max = *std::max_element(acc.cbegin(), acc.cend()); |
| 77 | const double c_scale = uint32_t(accumulated_max - accumulated_min) >= 256 ? double(uint32_t(accumulated_max - accumulated_min)) / 255.0 : 1.00001; |
| 78 | const uint8_t c_zero_point = uint8_t(std::max(std::min( |
| 79 | lrint(127.5 - 0.5 * double(accumulated_min + accumulated_max) / c_scale), |
| 80 | long(std::numeric_limits<uint8_t>::max())), long(std::numeric_limits<uint8_t>::min()))); |
| 81 | |
| 82 | const float requantization_scale = 1.0f / float(c_scale); |
| 83 | union xnn_qu8_conv_minmax_params quantization_params; |
| 84 | init_params(&quantization_params, |
| 85 | b_zero_point(), requantization_scale, c_zero_point, qmin(), qmax()); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 86 | |
| 87 | gemm( |
| 88 | m(), n(), k(), |
| 89 | a.data(), a_stride() * sizeof(uint8_t), |
| 90 | packed_w.data(), |
| 91 | c.data(), cm_stride() * sizeof(uint8_t), cn_stride() * sizeof(uint8_t), |
| 92 | &quantization_params); |
| 93 | |
| 94 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 95 | for (size_t n_index = 0; n_index < n(); n_index++) { |
Marat Dukhan | 50323b8 | 2022-01-11 00:12:01 -0800 | [diff] [blame] | 96 | c_ref[m_index * n() + n_index] = requantize( |
| 97 | acc[m_index * n() + n_index], requantization_scale, c_zero_point, qmin(), qmax()); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 98 | } |
| 99 | } |
| 100 | |
| 101 | for (size_t i = 0; i < m(); i++) { |
| 102 | for (size_t j = 0; j < n(); j++) { |
| 103 | ASSERT_LE(uint32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), uint32_t(qmax())); |
| 104 | ASSERT_GE(uint32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), uint32_t(qmin())); |
| 105 | ASSERT_EQ(uint32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), uint32_t(c_ref[i * n() + j])) |
| 106 | << "at " << i << ", " << j << ": reference = " << (uint32_t) c_ref[i * n() + j] |
| 107 | << " (accumulator = " << acc[i * n() + j] |
| 108 | << "), optimized = " << (uint32_t) c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " |
| 109 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 110 | << ", requantization scale = " << requantization_scale << ", output zero point = " << int32_t(c_zero_point); |
| 111 | } |
| 112 | } |
| 113 | } |
| 114 | } |
| 115 | |
| 116 | void GemmMicrokernelTester::Test( |
| 117 | xnn_qu8_igemm_minmax_ukernel_function igemm, |
| 118 | xnn_init_qu8_conv_minmax_params_fn init_params, |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 119 | xnn_qu8_requantize_fn requantize) |
| 120 | { |
| 121 | ASSERT_LE(m(), mr()); |
| 122 | |
| 123 | std::random_device random_device; |
| 124 | auto rng = std::mt19937(random_device()); |
| 125 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 126 | auto u8rng = std::bind( |
| 127 | std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), std::ref(rng)); |
| 128 | |
| 129 | std::vector<uint8_t> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(uint8_t)); |
| 130 | std::vector<uint8_t> b(n() * ks() * k()); |
| 131 | std::vector<uint8_t, AlignedAllocator<uint8_t, 64>> packed_w(ks() * packed_n() * packed_k() + packed_n() * sizeof(int32_t) / sizeof(uint8_t)); |
| 132 | std::vector<int32_t> bias(n()); |
| 133 | std::vector<uint8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 134 | std::vector<int32_t> acc(m() * n()); |
| 135 | std::vector<uint8_t> c_ref(m() * n()); |
| 136 | std::vector<uint8_t> junk(k() + 8); |
| 137 | std::vector<const uint8_t*> im2col(mr() * ks()); |
| 138 | |
| 139 | std::fill(junk.begin(), junk.end(), 0xA5); |
| 140 | |
| 141 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 142 | do { |
| 143 | std::generate(a.begin(), a.end(), std::ref(u8rng)); |
| 144 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 145 | do { |
| 146 | std::generate(b.begin(), b.end(), std::ref(u8rng)); |
| 147 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 148 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 149 | std::fill(c.begin(), c.end(), 0xA5); |
| 150 | |
| 151 | std::fill(packed_w.begin(), packed_w.end(), b_zero_point()); |
| 152 | const xnn_qu8_packing_params packing_params = { a_zero_point(), b_zero_point() }; |
| 153 | xnn_pack_qu8_conv_goki_w( |
| 154 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 155 | b.data(), bias.data(), packed_w.data(), 0 /* extra bytes */, &packing_params); |
| 156 | |
| 157 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 158 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 159 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 160 | } |
| 161 | } |
| 162 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 163 | if (zero_index() != SIZE_MAX) { |
| 164 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 165 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 166 | } |
| 167 | } |
| 168 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 169 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 170 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 171 | } |
| 172 | } |
| 173 | |
| 174 | // Compute 32-bit results and output quantization arguments. |
| 175 | std::fill(acc.begin(), acc.end(), 0); |
| 176 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 177 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 178 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 179 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 180 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 181 | acc[m_index * n() + n_index] += |
| 182 | (int32_t(im2col[ks_index * mr() + m_index][k_index]) - int32_t(a_zero_point())) * |
| 183 | (int32_t(b[(n_index * ks() + ks_index) * k() + k_index]) - int32_t(b_zero_point())); |
| 184 | } else { |
| 185 | acc[m_index * n() + n_index] += |
| 186 | (int32_t(im2col[ks_index * mr() + m_index][k_index + a_offset()]) - int32_t(a_zero_point())) * |
| 187 | (int32_t(b[(n_index * ks() + ks_index) * k() + k_index]) - int32_t(b_zero_point())); |
| 188 | } |
| 189 | } |
| 190 | } |
| 191 | acc[m_index * n() + n_index] += bias[n_index]; |
| 192 | } |
| 193 | } |
| 194 | |
| 195 | const int32_t accumulated_min = *std::min_element(acc.cbegin(), acc.cend()); |
| 196 | const int32_t accumulated_max = *std::max_element(acc.cbegin(), acc.cend()); |
| 197 | const double c_scale = uint32_t(accumulated_max - accumulated_min) >= 256 ? double(uint32_t(accumulated_max - accumulated_min)) / 255.0 : 1.00001; |
| 198 | const uint8_t c_zero_point = uint8_t(std::max(std::min( |
| 199 | lrint(127.5 - 0.5 * double(accumulated_min + accumulated_max) / c_scale), |
| 200 | long(std::numeric_limits<uint8_t>::max())), long(std::numeric_limits<uint8_t>::min()))); |
| 201 | |
| 202 | const float requantization_scale = 1.0f / float(c_scale); |
| 203 | union xnn_qu8_conv_minmax_params quantization_params; |
| 204 | init_params(&quantization_params, |
| 205 | b_zero_point(), requantization_scale, c_zero_point, qmin(), qmax()); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 206 | |
| 207 | const uint8_t* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 208 | |
| 209 | igemm( |
| 210 | m(), n(), k(), ks() * mr() * sizeof(void*), |
| 211 | im2col.data(), packed_w.data(), |
| 212 | c.data(), cm_stride() * sizeof(uint8_t), cn_stride() * sizeof(uint8_t), |
| 213 | a_offset() * sizeof(uint8_t), zero_pointer, |
| 214 | &quantization_params); |
| 215 | |
| 216 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 217 | for (size_t n_index = 0; n_index < n(); n_index++) { |
Marat Dukhan | 50323b8 | 2022-01-11 00:12:01 -0800 | [diff] [blame] | 218 | c_ref[m_index * n() + n_index] = requantize( |
| 219 | acc[m_index * n() + n_index], requantization_scale, c_zero_point, qmin(), qmax()); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 220 | } |
| 221 | } |
| 222 | |
| 223 | for (size_t i = 0; i < m(); i++) { |
| 224 | for (size_t j = 0; j < n(); j++) { |
| 225 | ASSERT_LE(uint32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), uint32_t(qmax())); |
| 226 | ASSERT_GE(uint32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), uint32_t(qmin())); |
| 227 | ASSERT_EQ(uint32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), uint32_t(c_ref[i * n() + j])) |
| 228 | << "at " << i << ", " << j << ": reference = " << uint32_t(c_ref[i * n() + j]) |
| 229 | << " (accumulator = " << acc[i * n() + j] |
| 230 | << "), optimized = " << (uint32_t) c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " |
| 231 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 232 | << ", requantization scale = " << requantization_scale << ", output zero point = " << int32_t(c_zero_point); |
| 233 | } |
| 234 | } |
| 235 | } |
| 236 | } |
| 237 | |
| 238 | void GemmMicrokernelTester::Test( |
| 239 | xnn_qc8_gemm_minmax_ukernel_function gemm, |
| 240 | xnn_init_qs8_minmax_params_fn init_params, |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 241 | xnn_qs8_requantize_fn requantize) const |
| 242 | { |
| 243 | ASSERT_LE(m(), mr()); |
| 244 | |
| 245 | std::random_device random_device; |
| 246 | auto rng = std::mt19937(random_device()); |
| 247 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 248 | auto i8rng = std::bind( |
| 249 | std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), |
| 250 | std::ref(rng)); |
| 251 | auto w8rng = std::bind( |
| 252 | std::uniform_int_distribution<int32_t>(-std::numeric_limits<int8_t>::max(), std::numeric_limits<int8_t>::max()), |
| 253 | std::ref(rng)); |
| 254 | |
| 255 | std::vector<int8_t> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(int8_t)); |
| 256 | std::vector<int8_t> b(n() * k()); |
| 257 | std::vector<int32_t> bias(n()); |
| 258 | std::vector<int8_t, AlignedAllocator<int8_t, 64>> packed_w(packed_n() * packed_k() + packed_n() * (sizeof(int32_t) + sizeof(float)) / sizeof(int8_t)); |
| 259 | std::vector<int16_t, AlignedAllocator<int16_t, 64>> packed_xw(packed_n() * packed_k() + packed_n() * (sizeof(int32_t) + sizeof(float)) / sizeof(int16_t)); |
| 260 | std::vector<int8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 261 | std::vector<int32_t> acc(m() * n()); |
| 262 | std::vector<float> scale(n()); |
| 263 | std::vector<int8_t> c_ref(m() * n()); |
| 264 | |
| 265 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 266 | do { |
| 267 | std::generate(a.begin(), a.end(), std::ref(i8rng)); |
| 268 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 269 | do { |
| 270 | std::generate(b.begin(), b.end(), std::ref(w8rng)); |
| 271 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 272 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 273 | std::fill(c.begin(), c.end(), 0xA5); |
| 274 | |
| 275 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 276 | const xnn_qs8_packing_params packing_params = { int8_t(a_zero_point() - 0x80) }; |
| 277 | if (extended_weights()) { |
| 278 | xnn_pack_qs8_gemm_xw_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 279 | b.data(), bias.data(), packed_xw.data(), nr() * sizeof(float), &packing_params); |
| 280 | } else { |
| 281 | xnn_pack_qs8_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 282 | b.data(), bias.data(), packed_w.data(), nr() * sizeof(float), &packing_params); |
| 283 | } |
| 284 | |
| 285 | // Compute 32-bit results and output quantization arguments. |
| 286 | std::fill(acc.begin(), acc.end(), 0); |
| 287 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 288 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 289 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 290 | acc[m_index * n() + n_index] += |
| 291 | (int32_t(a[m_index * a_stride() + k_index]) - int32_t(a_zero_point() - 0x80)) * |
| 292 | int32_t(b[n_index * k() + k_index]); |
| 293 | } |
| 294 | acc[m_index * n() + n_index] += bias[n_index]; |
| 295 | } |
| 296 | } |
| 297 | |
| 298 | const int8_t c_zero_point = -1; |
| 299 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 300 | int32_t accumulated_min = acc[n_index]; |
| 301 | int32_t accumulated_max = acc[n_index]; |
| 302 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 303 | accumulated_min = std::min(accumulated_min, acc[m_index * n() + n_index]); |
| 304 | accumulated_max = std::max(accumulated_max, acc[m_index * n() + n_index]); |
| 305 | } |
| 306 | const uint32_t accumulated_range = uint32_t(accumulated_max - accumulated_min); |
| 307 | const float c_scale = accumulated_range >= 256 ? double(accumulated_range) / 255.0 : 1.00001; |
| 308 | scale[n_index] = 1.0f / c_scale; |
| 309 | } |
| 310 | |
| 311 | if (extended_weights()) { |
| 312 | xnn_init_qc8_scale_fp32_params( |
| 313 | n(), nr(), |
| 314 | nr() * (packed_k() * sizeof(int16_t) + (sizeof(int32_t) + sizeof(float))), scale.data(), |
| 315 | (void*) ((uintptr_t) packed_xw.data() + nr() * (packed_k() * sizeof(int16_t) + sizeof(int32_t)))); |
| 316 | } else { |
| 317 | xnn_init_qc8_scale_fp32_params( |
| 318 | n(), nr(), |
| 319 | nr() * (packed_k() * sizeof(int8_t) + (sizeof(int32_t) + sizeof(float))), scale.data(), |
| 320 | (void*) ((uintptr_t) packed_w.data() + nr() * (packed_k() * sizeof(int8_t) + sizeof(int32_t)))); |
| 321 | } |
| 322 | |
| 323 | union xnn_qs8_minmax_params minmax_params; |
| 324 | init_params(&minmax_params, |
| 325 | c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 326 | |
| 327 | gemm( |
| 328 | m(), n(), k(), |
| 329 | a.data(), a_stride() * sizeof(int8_t), |
| 330 | extended_weights() ? static_cast<const void*>(packed_xw.data()) : static_cast<const void*>(packed_w.data()), |
| 331 | c.data(), cm_stride() * sizeof(int8_t), cn_stride() * sizeof(int8_t), |
| 332 | &minmax_params); |
| 333 | |
| 334 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 335 | for (size_t n_index = 0; n_index < n(); n_index++) { |
Marat Dukhan | 50323b8 | 2022-01-11 00:12:01 -0800 | [diff] [blame] | 336 | c_ref[m_index * n() + n_index] = requantize( |
| 337 | acc[m_index * n() + n_index], scale[n_index], c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 338 | } |
| 339 | } |
| 340 | |
| 341 | for (size_t i = 0; i < m(); i++) { |
| 342 | for (size_t j = 0; j < n(); j++) { |
| 343 | ASSERT_LE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmax()) - 0x80); |
| 344 | ASSERT_GE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmin()) - 0x80); |
| 345 | ASSERT_EQ(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(c_ref[i * n() + j])) |
| 346 | << "at " << i << ", " << j << ": reference = " << int32_t(c_ref[i * n() + j]) |
| 347 | << " (accumulator = " << acc[i * n() + j] |
| 348 | << "), optimized = " << int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]) << ", Mr x Nr x Kr = " << mr() << " x " |
| 349 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 350 | << ", requantization scale = " << scale[j] << ", output zero point = " << int32_t(c_zero_point); |
| 351 | } |
| 352 | } |
| 353 | } |
| 354 | } |
| 355 | |
| 356 | void GemmMicrokernelTester::Test( |
| 357 | xnn_qc8_igemm_minmax_ukernel_function igemm, |
| 358 | xnn_init_qs8_minmax_params_fn init_params, |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 359 | xnn_qs8_requantize_fn requantize) const |
| 360 | { |
| 361 | ASSERT_LE(m(), mr()); |
| 362 | |
| 363 | std::random_device random_device; |
| 364 | auto rng = std::mt19937(random_device()); |
| 365 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 366 | auto i8rng = std::bind( |
| 367 | std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), |
| 368 | std::ref(rng)); |
| 369 | auto w8rng = std::bind( |
| 370 | std::uniform_int_distribution<int32_t>(-std::numeric_limits<int8_t>::max(), std::numeric_limits<int8_t>::max()), |
| 371 | std::ref(rng)); |
| 372 | |
| 373 | std::vector<int8_t> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(uint8_t)); |
| 374 | std::vector<int8_t> b(n() * ks() * k()); |
| 375 | std::vector<int8_t, AlignedAllocator<int8_t, 64>> packed_w(ks() * packed_n() * packed_k() + packed_n() * (sizeof(int32_t) + sizeof(float)) / sizeof(int8_t)); |
| 376 | std::vector<int32_t> bias(n()); |
| 377 | std::vector<int8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 378 | std::vector<int32_t> acc(m() * n()); |
| 379 | std::vector<float> scale(n()); |
| 380 | std::vector<int8_t> c_ref(m() * n()); |
| 381 | std::vector<int8_t> junk(k() + 8); |
| 382 | std::vector<const int8_t*> im2col(mr() * ks()); |
| 383 | |
| 384 | std::fill(junk.begin(), junk.end(), 0xA5); |
| 385 | |
| 386 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 387 | do { |
| 388 | std::generate(a.begin(), a.end(), std::ref(i8rng)); |
| 389 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 390 | do { |
| 391 | std::generate(b.begin(), b.end(), std::ref(w8rng)); |
| 392 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 393 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 394 | std::fill(c.begin(), c.end(), 0xA5); |
| 395 | |
| 396 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 397 | const xnn_qs8_packing_params packing_params = { int8_t(a_zero_point() - 0x80) }; |
| 398 | xnn_pack_qs8_conv_goki_w( |
| 399 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 400 | b.data(), bias.data(), packed_w.data(), nr() * sizeof(float), &packing_params); |
| 401 | |
| 402 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 403 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 404 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 405 | } |
| 406 | } |
| 407 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 408 | if (zero_index() != SIZE_MAX) { |
| 409 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 410 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 411 | } |
| 412 | } |
| 413 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 414 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 415 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 416 | } |
| 417 | } |
| 418 | |
| 419 | // Compute 32-bit results and output quantization arguments. |
| 420 | std::fill(acc.begin(), acc.end(), 0); |
| 421 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 422 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 423 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 424 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 425 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 426 | acc[m_index * n() + n_index] += |
| 427 | (int32_t(im2col[ks_index * mr() + m_index][k_index]) - int32_t(a_zero_point() - 0x80)) * |
| 428 | int32_t(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 429 | } else { |
| 430 | acc[m_index * n() + n_index] += |
| 431 | (int32_t(im2col[ks_index * mr() + m_index][k_index + a_offset()]) - int32_t(a_zero_point() - 0x80)) * |
| 432 | int32_t(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 433 | } |
| 434 | } |
| 435 | } |
| 436 | acc[m_index * n() + n_index] += bias[n_index]; |
| 437 | } |
| 438 | } |
| 439 | |
| 440 | const int8_t c_zero_point = -1; |
| 441 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 442 | int32_t accumulated_min = acc[n_index]; |
| 443 | int32_t accumulated_max = acc[n_index]; |
| 444 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 445 | accumulated_min = std::min(accumulated_min, acc[m_index * n() + n_index]); |
| 446 | accumulated_max = std::max(accumulated_max, acc[m_index * n() + n_index]); |
| 447 | } |
| 448 | const uint32_t accumulated_range = uint32_t(accumulated_max - accumulated_min); |
| 449 | const float c_scale = accumulated_range >= 256 ? double(accumulated_range) / 255.0 : 1.00001; |
| 450 | scale[n_index] = 1.0f / c_scale; |
| 451 | } |
| 452 | |
| 453 | xnn_init_qc8_scale_fp32_params( |
| 454 | n(), nr(), |
| 455 | nr() * (ks() * packed_k() * sizeof(int8_t) + (sizeof(int32_t) + sizeof(float))), scale.data(), |
| 456 | (void*) ((uintptr_t) packed_w.data() + nr() * (ks() * packed_k() * sizeof(int8_t) + sizeof(int32_t)))); |
| 457 | |
| 458 | union xnn_qs8_minmax_params minmax_params; |
| 459 | init_params(&minmax_params, |
| 460 | c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 461 | |
| 462 | const int8_t* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 463 | |
| 464 | igemm( |
| 465 | m(), n(), k(), ks() * mr() * sizeof(void*), |
| 466 | im2col.data(), packed_w.data(), |
| 467 | c.data(), cm_stride() * sizeof(int8_t), cn_stride() * sizeof(int8_t), |
| 468 | a_offset() * sizeof(uint8_t), zero_pointer, |
| 469 | &minmax_params); |
| 470 | |
| 471 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 472 | for (size_t n_index = 0; n_index < n(); n_index++) { |
Marat Dukhan | 50323b8 | 2022-01-11 00:12:01 -0800 | [diff] [blame] | 473 | c_ref[m_index * n() + n_index] = requantize( |
| 474 | acc[m_index * n() + n_index], scale[n_index], c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 475 | } |
| 476 | } |
| 477 | |
| 478 | for (size_t i = 0; i < m(); i++) { |
| 479 | for (size_t j = 0; j < n(); j++) { |
| 480 | ASSERT_LE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmax()) - 0x80); |
| 481 | ASSERT_GE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmin()) - 0x80); |
| 482 | ASSERT_EQ(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(c_ref[i * n() + j])) |
| 483 | << "at " << i << ", " << j << ": reference = " << uint32_t(c_ref[i * n() + j]) |
| 484 | << " (accumulator = " << acc[i * n() + j] |
| 485 | << "), optimized = " << (uint32_t) c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " |
| 486 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 487 | << ", requantization scale = " << scale[j] << ", output zero point = " << int32_t(c_zero_point); |
| 488 | } |
| 489 | } |
| 490 | } |
| 491 | } |
| 492 | |
| 493 | void GemmMicrokernelTester::Test( |
| 494 | xnn_qs8_gemm_minmax_ukernel_function gemm, |
| 495 | xnn_init_qs8_conv_minmax_params_fn init_params, |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 496 | xnn_qs8_requantize_fn requantize) const |
| 497 | { |
| 498 | ASSERT_LE(m(), mr()); |
| 499 | |
| 500 | std::random_device random_device; |
| 501 | auto rng = std::mt19937(random_device()); |
| 502 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 503 | auto i8rng = std::bind( |
| 504 | std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), |
| 505 | std::ref(rng)); |
| 506 | auto w8rng = std::bind( |
| 507 | std::uniform_int_distribution<int32_t>(-std::numeric_limits<int8_t>::max(), std::numeric_limits<int8_t>::max()), |
| 508 | std::ref(rng)); |
| 509 | |
| 510 | std::vector<int8_t> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(int8_t)); |
| 511 | std::vector<int8_t> b(n() * k()); |
| 512 | std::vector<int32_t> bias(n()); |
| 513 | std::vector<int8_t, AlignedAllocator<int8_t, 64>> packed_w(packed_n() * packed_k() + packed_n() * sizeof(int32_t) / sizeof(int8_t)); |
| 514 | std::vector<int16_t, AlignedAllocator<int16_t, 64>> packed_xw(packed_n() * packed_k() + packed_n() * sizeof(int32_t) / sizeof(int16_t)); |
| 515 | std::vector<int8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 516 | std::vector<int32_t> acc(m() * n()); |
| 517 | std::vector<int8_t> c_ref(m() * n()); |
| 518 | |
| 519 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 520 | do { |
| 521 | std::generate(a.begin(), a.end(), std::ref(i8rng)); |
| 522 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 523 | do { |
| 524 | std::generate(b.begin(), b.end(), std::ref(w8rng)); |
| 525 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 526 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 527 | std::fill(c.begin(), c.end(), 0xA5); |
| 528 | |
| 529 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 530 | const xnn_qs8_packing_params packing_params = { int8_t(a_zero_point() - 0x80) }; |
| 531 | if (extended_weights()) { |
| 532 | xnn_pack_qs8_gemm_xw_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 533 | b.data(), bias.data(), packed_xw.data(), 0, &packing_params); |
| 534 | } else { |
| 535 | xnn_pack_qs8_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 536 | b.data(), bias.data(), packed_w.data(), 0, &packing_params); |
| 537 | } |
| 538 | |
| 539 | // Compute 32-bit results and output quantization arguments. |
| 540 | std::fill(acc.begin(), acc.end(), 0); |
| 541 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 542 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 543 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 544 | acc[m_index * n() + n_index] += |
| 545 | (int32_t(a[m_index * a_stride() + k_index]) - int32_t(a_zero_point() - 0x80)) * |
| 546 | int32_t(b[n_index * k() + k_index]); |
| 547 | } |
| 548 | acc[m_index * n() + n_index] += bias[n_index]; |
| 549 | } |
| 550 | } |
| 551 | |
| 552 | const int32_t accumulated_min = *std::min_element(acc.cbegin(), acc.cend()); |
| 553 | const int32_t accumulated_max = *std::max_element(acc.cbegin(), acc.cend()); |
| 554 | const double c_scale = uint32_t(accumulated_max - accumulated_min) >= 256 ? double(uint32_t(accumulated_max - accumulated_min)) / 255.0 : 1.00001; |
| 555 | const int8_t c_zero_point = int8_t(std::max(std::min( |
| 556 | lrint(-0.5 - 0.5 * double(accumulated_min + accumulated_max) / c_scale), |
| 557 | long(std::numeric_limits<int8_t>::max())), long(std::numeric_limits<int8_t>::min()))); |
| 558 | |
| 559 | const float requantization_scale = 1.0f / float(c_scale); |
| 560 | union xnn_qs8_conv_minmax_params quantization_params; |
| 561 | init_params(&quantization_params, |
| 562 | requantization_scale, c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 563 | |
| 564 | gemm( |
| 565 | m(), n(), k(), |
| 566 | a.data(), a_stride() * sizeof(int8_t), |
| 567 | extended_weights() ? static_cast<const void*>(packed_xw.data()) : static_cast<const void*>(packed_w.data()), |
| 568 | c.data(), cm_stride() * sizeof(int8_t), cn_stride() * sizeof(int8_t), |
| 569 | &quantization_params); |
| 570 | |
| 571 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 572 | for (size_t n_index = 0; n_index < n(); n_index++) { |
Marat Dukhan | 50323b8 | 2022-01-11 00:12:01 -0800 | [diff] [blame] | 573 | c_ref[m_index * n() + n_index] = requantize( |
| 574 | acc[m_index * n() + n_index], requantization_scale, c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 575 | } |
| 576 | } |
| 577 | |
| 578 | for (size_t i = 0; i < m(); i++) { |
| 579 | for (size_t j = 0; j < n(); j++) { |
| 580 | ASSERT_LE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmax()) - 0x80); |
| 581 | ASSERT_GE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmin()) - 0x80); |
| 582 | ASSERT_EQ(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(c_ref[i * n() + j])) |
| 583 | << "at " << i << ", " << j << ": reference = " << int32_t(c_ref[i * n() + j]) |
| 584 | << " (accumulator = " << acc[i * n() + j] |
| 585 | << "), optimized = " << int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]) << ", Mr x Nr x Kr = " << mr() << " x " |
| 586 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 587 | << ", requantization scale = " << requantization_scale << ", output zero point = " << int32_t(c_zero_point); |
| 588 | } |
| 589 | } |
| 590 | } |
| 591 | } |
| 592 | |
| 593 | void GemmMicrokernelTester::Test( |
| 594 | xnn_qs8_igemm_minmax_ukernel_function igemm, |
| 595 | xnn_init_qs8_conv_minmax_params_fn init_params, |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 596 | xnn_qs8_requantize_fn requantize) const |
| 597 | { |
| 598 | ASSERT_LE(m(), mr()); |
| 599 | |
| 600 | std::random_device random_device; |
| 601 | auto rng = std::mt19937(random_device()); |
| 602 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 603 | auto i8rng = std::bind( |
| 604 | std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), |
| 605 | std::ref(rng)); |
| 606 | auto w8rng = std::bind( |
| 607 | std::uniform_int_distribution<int32_t>(-std::numeric_limits<int8_t>::max(), std::numeric_limits<int8_t>::max()), |
| 608 | std::ref(rng)); |
| 609 | |
| 610 | std::vector<int8_t> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(uint8_t)); |
| 611 | std::vector<int8_t> b(n() * ks() * k()); |
| 612 | std::vector<int8_t, AlignedAllocator<int8_t, 64>> packed_w(ks() * packed_n() * packed_k() + packed_n() * sizeof(int32_t) / sizeof(int8_t)); |
| 613 | std::vector<int32_t> bias(n()); |
| 614 | std::vector<int8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 615 | std::vector<int32_t> acc(m() * n()); |
| 616 | std::vector<int8_t> c_ref(m() * n()); |
| 617 | std::vector<int8_t> junk(k() + 8); |
| 618 | std::vector<const int8_t*> im2col(mr() * ks()); |
| 619 | |
| 620 | std::fill(junk.begin(), junk.end(), 0xA5); |
| 621 | |
| 622 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 623 | do { |
| 624 | std::generate(a.begin(), a.end(), std::ref(i8rng)); |
| 625 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 626 | do { |
| 627 | std::generate(b.begin(), b.end(), std::ref(w8rng)); |
| 628 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 629 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 630 | std::fill(c.begin(), c.end(), 0xA5); |
| 631 | |
| 632 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 633 | const xnn_qs8_packing_params packing_params = { int8_t(a_zero_point() - 0x80) }; |
| 634 | xnn_pack_qs8_conv_goki_w( |
| 635 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 636 | b.data(), bias.data(), packed_w.data(), 0 /* extra bytes */, &packing_params); |
| 637 | |
| 638 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 639 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 640 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 641 | } |
| 642 | } |
| 643 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 644 | if (zero_index() != SIZE_MAX) { |
| 645 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 646 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 647 | } |
| 648 | } |
| 649 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 650 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 651 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 652 | } |
| 653 | } |
| 654 | |
| 655 | // Compute 32-bit results and output quantization arguments. |
| 656 | std::fill(acc.begin(), acc.end(), 0); |
| 657 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 658 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 659 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 660 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 661 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 662 | acc[m_index * n() + n_index] += |
| 663 | (int32_t(im2col[ks_index * mr() + m_index][k_index]) - int32_t(a_zero_point() - 0x80)) * |
| 664 | int32_t(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 665 | } else { |
| 666 | acc[m_index * n() + n_index] += |
| 667 | (int32_t(im2col[ks_index * mr() + m_index][k_index + a_offset()]) - int32_t(a_zero_point() - 0x80)) * |
| 668 | int32_t(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 669 | } |
| 670 | } |
| 671 | } |
| 672 | acc[m_index * n() + n_index] += bias[n_index]; |
| 673 | } |
| 674 | } |
| 675 | |
| 676 | const int32_t accumulated_min = *std::min_element(acc.cbegin(), acc.cend()); |
| 677 | const int32_t accumulated_max = *std::max_element(acc.cbegin(), acc.cend()); |
| 678 | const double c_scale = uint32_t(accumulated_max - accumulated_min) >= 256 ? double(uint32_t(accumulated_max - accumulated_min)) / 255.0 : 1.00001; |
| 679 | const uint8_t c_zero_point = uint8_t(std::max(std::min( |
| 680 | lrint(-0.5 - 0.5 * double(accumulated_min + accumulated_max) / c_scale), |
| 681 | long(std::numeric_limits<int8_t>::max())), long(std::numeric_limits<int8_t>::min()))); |
| 682 | |
| 683 | const float requantization_scale = 1.0f / float(c_scale); |
| 684 | union xnn_qs8_conv_minmax_params quantization_params; |
| 685 | init_params(&quantization_params, |
| 686 | requantization_scale, c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 687 | |
| 688 | const int8_t* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 689 | |
| 690 | igemm( |
| 691 | m(), n(), k(), ks() * mr() * sizeof(void*), |
| 692 | im2col.data(), packed_w.data(), |
| 693 | c.data(), cm_stride() * sizeof(int8_t), cn_stride() * sizeof(int8_t), |
| 694 | a_offset() * sizeof(uint8_t), zero_pointer, |
| 695 | &quantization_params); |
| 696 | |
| 697 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 698 | for (size_t n_index = 0; n_index < n(); n_index++) { |
Marat Dukhan | 50323b8 | 2022-01-11 00:12:01 -0800 | [diff] [blame] | 699 | c_ref[m_index * n() + n_index] = requantize( |
| 700 | acc[m_index * n() + n_index], requantization_scale, c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 701 | } |
| 702 | } |
| 703 | |
| 704 | for (size_t i = 0; i < m(); i++) { |
| 705 | for (size_t j = 0; j < n(); j++) { |
| 706 | ASSERT_LE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmax()) - 0x80); |
| 707 | ASSERT_GE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmin()) - 0x80); |
| 708 | ASSERT_EQ(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(c_ref[i * n() + j])) |
| 709 | << "at " << i << ", " << j << ": reference = " << uint32_t(c_ref[i * n() + j]) |
| 710 | << " (accumulator = " << acc[i * n() + j] |
| 711 | << "), optimized = " << (uint32_t) c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " |
| 712 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 713 | << ", requantization scale = " << requantization_scale << ", output zero point = " << int32_t(c_zero_point); |
| 714 | } |
| 715 | } |
| 716 | } |
| 717 | } |
| 718 | |
| 719 | void GemmMicrokernelTester::Test(xnn_f16_gemm_minmax_ukernel_function gemm_minmax, xnn_init_f16_scaleminmax_params_fn init_params) const |
| 720 | { |
| 721 | ASSERT_LE(m(), mr()); |
| 722 | ASSERT_GE(a_stride(), k()); |
| 723 | ASSERT_GE(cm_stride(), n()); |
| 724 | |
| 725 | std::random_device random_device; |
| 726 | auto rng = std::mt19937(random_device()); |
| 727 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 728 | auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng); |
| 729 | |
| 730 | std::vector<uint16_t> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(uint16_t)); |
| 731 | std::vector<uint16_t> b(n() * k()); |
| 732 | std::vector<uint16_t, AlignedAllocator<uint16_t, 64>> packed_w(packed_n() * packed_k() + packed_n()); |
| 733 | std::vector<uint16_t> bias(n()); |
| 734 | std::vector<uint16_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 735 | std::vector<float> c_ref(m() * n()); |
| 736 | |
| 737 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 738 | std::generate(a.begin(), a.end(), std::ref(f16rng)); |
| 739 | std::generate(b.begin(), b.end(), std::ref(f16rng)); |
| 740 | std::generate(bias.begin(), bias.end(), std::ref(f16rng)); |
| 741 | std::fill(c.begin(), c.end(), UINT16_C(0x7E00) /* NaN */); |
| 742 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 743 | |
| 744 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 745 | xnn_pack_f16_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), b.data(), bias.data(), packed_w.data(), 0, nullptr); |
| 746 | |
| 747 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 748 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 749 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 750 | ASSERT_LE(n(), packed_n()); |
| 751 | ASSERT_LT(m_index * n() + n_index, c_ref.size()); |
| 752 | ASSERT_LT(m_index * k() + k_index, a.size()); |
| 753 | c_ref[m_index * n() + n_index] += |
| 754 | fp16_ieee_to_fp32_value(a[m_index * a_stride() + k_index]) * |
| 755 | fp16_ieee_to_fp32_value(b[n_index * k() + k_index]); |
| 756 | } |
| 757 | c_ref[m_index * n() + n_index] += fp16_ieee_to_fp32_value(bias[n_index]); |
| 758 | } |
| 759 | } |
| 760 | |
| 761 | const float accumulated_min = *std::min_element(c_ref.cbegin(), c_ref.cend()); |
| 762 | const float accumulated_max = *std::max_element(c_ref.cbegin(), c_ref.cend()); |
| 763 | const float c_min = fp16_ieee_to_fp32_value(fp16_ieee_from_fp32_value(accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()))); |
| 764 | const float c_max = fp16_ieee_to_fp32_value(fp16_ieee_from_fp32_value(accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()))); |
| 765 | |
| 766 | // Prepare parameters. |
| 767 | xnn_f16_scaleminmax_params params; |
| 768 | init_params(¶ms, |
| 769 | UINT16_C(0x3C00) /* 1.0 */, |
| 770 | fp16_ieee_from_fp32_value(c_min), |
| 771 | fp16_ieee_from_fp32_value(c_max)); |
| 772 | |
| 773 | for (float& c_value : c_ref) { |
| 774 | c_value = std::max(std::min(c_value, c_max), c_min); |
| 775 | } |
| 776 | |
| 777 | gemm_minmax(m(), n(), k() * sizeof(uint16_t), |
| 778 | a.data(), a_stride() * sizeof(uint16_t), |
| 779 | packed_w.data(), |
| 780 | c.data(), cm_stride() * sizeof(uint16_t), cn_stride() * sizeof(uint16_t), |
| 781 | ¶ms); |
| 782 | |
| 783 | // Validate micro-kernel outputs. |
| 784 | for (size_t i = 0; i < m(); i++) { |
| 785 | for (size_t j = 0; j < n(); j++) { |
| 786 | ASSERT_NEAR(fp16_ieee_to_fp32_value(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), c_ref[i * n() + j], std::max(1.0e-4f, std::abs(c_ref[i * n() + j]) * 1.0e-2f)) |
| 787 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 788 | << ", optimized = " << fp16_ieee_to_fp32_value(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]) << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 789 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 790 | } |
| 791 | } |
| 792 | } |
| 793 | } |
| 794 | |
| 795 | void GemmMicrokernelTester::Test(xnn_f16_igemm_minmax_ukernel_function igemm_minmax, xnn_init_f16_scaleminmax_params_fn init_params) const { |
| 796 | ASSERT_LE(m(), mr()); |
| 797 | |
| 798 | std::random_device random_device; |
| 799 | auto rng = std::mt19937(random_device()); |
| 800 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 801 | auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng); |
| 802 | |
| 803 | std::vector<uint16_t> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(uint16_t)); |
| 804 | std::vector<uint16_t> b(n() * ks() * k()); |
| 805 | std::vector<uint16_t, AlignedAllocator<uint16_t, 64>> packed_w(ks() * packed_k() * packed_n() + packed_n()); |
| 806 | std::vector<uint16_t> bias(n()); |
| 807 | std::vector<uint16_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 808 | std::vector<float> c_ref(m() * n()); |
| 809 | std::vector<uint16_t> junk(k() + XNN_EXTRA_BYTES / sizeof(uint16_t)); |
| 810 | std::vector<const uint16_t*> im2col(mr() * ks()); |
| 811 | std::fill(junk.begin(), junk.end(), UINT16_C(0x7E00) /* NaN */); |
| 812 | |
| 813 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 814 | std::generate(a.begin(), a.end(), std::ref(f16rng)); |
| 815 | std::generate(b.begin(), b.end(), std::ref(f16rng)); |
| 816 | std::generate(bias.begin(), bias.end(), std::ref(f16rng)); |
| 817 | std::fill(c.begin(), c.end(), UINT16_C(0x7E00) /* NaN */); |
| 818 | std::fill(c_ref.begin(), c_ref.end(), 0); |
| 819 | |
| 820 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 821 | xnn_pack_f16_conv_goki_w( |
| 822 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 823 | b.data(), bias.data(), packed_w.data(), 0 /* extra bytes */, nullptr); |
| 824 | |
| 825 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 826 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 827 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 828 | } |
| 829 | } |
| 830 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 831 | if (zero_index() != SIZE_MAX) { |
| 832 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 833 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 834 | } |
| 835 | } |
| 836 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 837 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 838 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 839 | } |
| 840 | } |
| 841 | |
| 842 | std::fill(c_ref.begin(), c_ref.end(), 0.0); |
| 843 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 844 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 845 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 846 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 847 | ASSERT_LT(ks_index * mr() + m_index, im2col.size()); |
| 848 | ASSERT_LT(k_index, k()); |
| 849 | ASSERT_LT(k_index, a_stride()); |
| 850 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 851 | c_ref[m_index * n() + n_index] += |
| 852 | fp16_ieee_to_fp32_value(im2col[ks_index * mr() + m_index][k_index]) * |
| 853 | fp16_ieee_to_fp32_value(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 854 | } else { |
| 855 | c_ref[m_index * n() + n_index] += |
| 856 | fp16_ieee_to_fp32_value(im2col[ks_index * mr() + m_index][k_index + a_offset()]) * |
| 857 | fp16_ieee_to_fp32_value(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 858 | } |
| 859 | } |
| 860 | } |
| 861 | c_ref[m_index * n() + n_index] += fp16_ieee_to_fp32_value(bias[n_index]); |
| 862 | } |
| 863 | } |
| 864 | |
| 865 | const float accumulated_min = *std::min_element(c_ref.cbegin(), c_ref.cend()); |
| 866 | const float accumulated_max = *std::max_element(c_ref.cbegin(), c_ref.cend()); |
| 867 | const float c_min = fp16_ieee_to_fp32_value(fp16_ieee_from_fp32_value(accumulated_min + (accumulated_max - accumulated_min) / 255.0f * uint16_t(qmin()))); |
| 868 | const float c_max = fp16_ieee_to_fp32_value(fp16_ieee_from_fp32_value(accumulated_max - (accumulated_max - accumulated_min) / 255.0f * uint16_t(255 - qmax()))); |
| 869 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 870 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 871 | c_ref[m_index * n() + n_index] = std::min(c_ref[m_index * n() + n_index], c_max); |
| 872 | c_ref[m_index * n() + n_index] = std::max(c_ref[m_index * n() + n_index], c_min); |
| 873 | } |
| 874 | } |
| 875 | |
| 876 | // Prepare parameters. |
| 877 | xnn_f16_scaleminmax_params params; |
| 878 | init_params(¶ms, |
| 879 | UINT16_C(0x3C00) /* 1.0 */, |
| 880 | fp16_ieee_from_fp32_value(c_min), |
| 881 | fp16_ieee_from_fp32_value(c_max)); |
| 882 | |
| 883 | for (float& c_value : c_ref) { |
| 884 | c_value = std::max(std::min(c_value, c_max), c_min); |
| 885 | } |
| 886 | |
| 887 | const uint16_t* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 888 | |
| 889 | igemm_minmax( |
| 890 | m(), n(), k() * sizeof(uint16_t), ks() * mr() * sizeof(void*), |
| 891 | reinterpret_cast<const void**>(im2col.data()), packed_w.data(), |
| 892 | c.data(), cm_stride() * sizeof(uint16_t), cn_stride() * sizeof(uint16_t), |
| 893 | a_offset() * sizeof(uint16_t), zero_pointer, |
| 894 | ¶ms); |
| 895 | |
| 896 | for (size_t i = 0; i < m(); i++) { |
| 897 | for (size_t j = 0; j < n(); j++) { |
| 898 | ASSERT_LE(fp16_ieee_to_fp32_value(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), c_max) |
| 899 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 900 | << ", optimized = " << fp16_ieee_to_fp32_value(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]) << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 901 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 902 | ASSERT_GE(fp16_ieee_to_fp32_value(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), c_min) |
| 903 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 904 | << ", optimized = " << fp16_ieee_to_fp32_value(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]) << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 905 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 906 | ASSERT_NEAR(fp16_ieee_to_fp32_value(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), c_ref[i * n() + j], std::max(1.0e-4f, std::abs(c_ref[i * n() + j]) * 1.0e-2f)) |
| 907 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 908 | << ", optimized = " << fp16_ieee_to_fp32_value(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]) << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 909 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 910 | } |
| 911 | } |
| 912 | } |
| 913 | } |
| 914 | |
| 915 | void GemmMicrokernelTester::Test(xnn_f32_ppmm_minmax_ukernel_function ppmm_minmax, xnn_init_f32_minmax_params_fn init_params) const { |
| 916 | ASSERT_LE(m(), mr()); |
| 917 | ASSERT_GE(cm_stride(), n()); |
| 918 | |
| 919 | std::random_device random_device; |
| 920 | auto rng = std::mt19937(random_device()); |
| 921 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 922 | |
| 923 | std::vector<float> a(packed_k() * mr()); |
| 924 | std::vector<float> b(n() * k()); |
| 925 | std::vector<float> bias(n()); |
| 926 | std::vector<float, AlignedAllocator<float, 64>> packed_w(packed_n() * packed_k() + packed_n()); |
| 927 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 928 | std::vector<float> c_ref(m() * n()); |
| 929 | |
| 930 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 931 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 932 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 933 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 934 | std::fill(c.begin(), c.end(), nanf("")); |
| 935 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 936 | |
| 937 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 938 | xnn_pack_f32_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), b.data(), bias.data(), packed_w.data(), 0, nullptr); |
| 939 | |
| 940 | for (size_t i = m(); i < mr(); i++) { |
| 941 | for (size_t l = 0; l < k(); l++) { |
| 942 | a[l * mr() + i] = a[l * mr() + m() - 1]; |
| 943 | } |
| 944 | } |
| 945 | |
| 946 | for (size_t i = 0; i < m(); i++) { |
| 947 | for (size_t j = 0; j < n(); j++) { |
| 948 | for (size_t l = 0; l < k(); l++) { |
| 949 | c_ref[i * n() + j] += |
| 950 | a[l * mr() + i] * |
| 951 | b[j * k() + l]; |
| 952 | } |
| 953 | c_ref[i * n() + j] += bias[j]; |
| 954 | } |
| 955 | } |
| 956 | |
| 957 | const float accumulated_min = *std::min_element(c_ref.cbegin(), c_ref.cend()); |
| 958 | const float accumulated_max = *std::max_element(c_ref.cbegin(), c_ref.cend()); |
| 959 | const float c_min = accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()); |
| 960 | const float c_max = accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()); |
| 961 | |
| 962 | // Prepare parameters. |
| 963 | xnn_f32_minmax_params params; |
| 964 | init_params(¶ms, c_min, c_max); |
| 965 | |
| 966 | for (float& c_value : c_ref) { |
| 967 | c_value = std::max(std::min(c_value, c_max), c_min); |
| 968 | } |
| 969 | |
| 970 | ppmm_minmax(m(), n(), k() * sizeof(float), |
| 971 | a.data(), packed_w.data(), |
| 972 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 973 | ¶ms); |
| 974 | |
| 975 | // Validate micro-kernel outputs. |
| 976 | for (size_t i = 0; i < m(); i++) { |
| 977 | for (size_t j = 0; j < n(); j++) { |
| 978 | ASSERT_NEAR( |
| 979 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 980 | c_ref[i * n() + j], |
| 981 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 982 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 983 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 984 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 985 | } |
| 986 | } |
| 987 | } |
| 988 | } |
| 989 | |
| 990 | void GemmMicrokernelTester::Test(xnn_f32_gemm_ukernel_function gemm) const { |
| 991 | ASSERT_LE(m(), mr()); |
| 992 | ASSERT_GE(a_stride(), k()); |
| 993 | ASSERT_GE(cm_stride(), n()); |
| 994 | |
| 995 | std::random_device random_device; |
| 996 | auto rng = std::mt19937(random_device()); |
| 997 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 998 | |
| 999 | std::vector<float> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1000 | std::vector<float> b(n() * k()); |
| 1001 | std::vector<float> bias(n()); |
| 1002 | std::vector<float, AlignedAllocator<float, 64>> packed_w(packed_n() * packed_k() + packed_n()); |
| 1003 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1004 | std::vector<float> c_ref(m() * n()); |
| 1005 | |
| 1006 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1007 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1008 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1009 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 1010 | std::fill(c.begin(), c.end(), nanf("")); |
| 1011 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1012 | |
| 1013 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1014 | xnn_pack_f32_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), b.data(), bias.data(), packed_w.data(), 0, nullptr); |
| 1015 | |
| 1016 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1017 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1018 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1019 | ASSERT_LE(n(), packed_n()); |
| 1020 | ASSERT_LT(m_index * n() + n_index, c_ref.size()); |
| 1021 | c_ref[m_index * n() + n_index] += |
| 1022 | a[m_index * a_stride() + k_index] * |
| 1023 | b[n_index * k() + k_index]; |
| 1024 | } |
| 1025 | c_ref[m_index * n() + n_index] += bias[n_index]; |
| 1026 | } |
| 1027 | } |
| 1028 | |
| 1029 | gemm(m(), n(), k() * sizeof(float), |
| 1030 | a.data(), a_stride() * sizeof(float), |
| 1031 | packed_w.data(), |
| 1032 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1033 | nullptr); |
| 1034 | |
| 1035 | // Validate micro-kernel outputs. |
| 1036 | for (size_t i = 0; i < m(); i++) { |
| 1037 | for (size_t j = 0; j < n(); j++) { |
| 1038 | ASSERT_NEAR( |
| 1039 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1040 | c_ref[i * n() + j], |
| 1041 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1042 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1043 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1044 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1045 | } |
| 1046 | } |
| 1047 | } |
| 1048 | } |
| 1049 | |
| 1050 | void GemmMicrokernelTester::Test(xnn_f32_gemm_relu_ukernel_function gemm_relu) const { |
| 1051 | ASSERT_LE(m(), mr()); |
| 1052 | ASSERT_GE(a_stride(), k()); |
| 1053 | ASSERT_GE(cm_stride(), n()); |
| 1054 | |
| 1055 | std::random_device random_device; |
| 1056 | auto rng = std::mt19937(random_device()); |
| 1057 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 1058 | |
| 1059 | std::vector<float> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1060 | std::vector<float> b(n() * k()); |
| 1061 | std::vector<float> bias(n()); |
| 1062 | std::vector<float, AlignedAllocator<float, 64>> packed_w(packed_n() * packed_k() + packed_n()); |
| 1063 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1064 | std::vector<float> c_ref(m() * n()); |
| 1065 | |
| 1066 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1067 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1068 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1069 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 1070 | std::fill(c.begin(), c.end(), nanf("")); |
| 1071 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1072 | |
| 1073 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1074 | xnn_pack_f32_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), b.data(), bias.data(), packed_w.data(), 0, nullptr); |
| 1075 | |
| 1076 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1077 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1078 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1079 | ASSERT_LE(n(), packed_n()); |
| 1080 | ASSERT_LT(m_index * n() + n_index, c_ref.size()); |
| 1081 | c_ref[m_index * n() + n_index] += |
| 1082 | a[m_index * a_stride() + k_index] * |
| 1083 | b[n_index * k() + k_index]; |
| 1084 | } |
| 1085 | c_ref[m_index * n() + n_index] = std::max(0.0f, c_ref[m_index * n() + n_index] + bias[n_index]); |
| 1086 | } |
| 1087 | } |
| 1088 | |
| 1089 | gemm_relu(m(), n(), k() * sizeof(float), |
| 1090 | a.data(), a_stride() * sizeof(float), |
| 1091 | packed_w.data(), |
| 1092 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1093 | nullptr); |
| 1094 | |
| 1095 | // Validate micro-kernel outputs. |
| 1096 | for (size_t i = 0; i < m(); i++) { |
| 1097 | for (size_t j = 0; j < n(); j++) { |
| 1098 | ASSERT_GE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], 0.0f) |
| 1099 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1100 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1101 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1102 | ASSERT_NEAR( |
| 1103 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1104 | c_ref[i * n() + j], |
| 1105 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1106 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1107 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1108 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1109 | } |
| 1110 | } |
| 1111 | } |
| 1112 | } |
| 1113 | |
| 1114 | void GemmMicrokernelTester::Test(xnn_f32_gemm_minmax_ukernel_function gemm_minmax, xnn_init_f32_minmax_params_fn init_params) const { |
| 1115 | ASSERT_LE(m(), mr()); |
| 1116 | ASSERT_GE(a_stride(), k()); |
| 1117 | ASSERT_GE(cm_stride(), n()); |
| 1118 | |
| 1119 | std::random_device random_device; |
| 1120 | auto rng = std::mt19937(random_device()); |
| 1121 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 1122 | |
| 1123 | std::vector<float> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1124 | std::vector<float> b(n() * k()); |
| 1125 | std::vector<float> bias(n()); |
| 1126 | std::vector<float, AlignedAllocator<float, 64>> packed_w(packed_n() * packed_k() + packed_n()); |
| 1127 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1128 | std::vector<float> c_ref(m() * n()); |
| 1129 | |
| 1130 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1131 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1132 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1133 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 1134 | std::fill(c.begin(), c.end(), nanf("")); |
| 1135 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1136 | |
| 1137 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1138 | xnn_pack_f32_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), b.data(), bias.data(), packed_w.data(), 0, nullptr); |
| 1139 | |
| 1140 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1141 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1142 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1143 | ASSERT_LE(n(), packed_n()); |
| 1144 | ASSERT_LT(m_index * n() + n_index, c_ref.size()); |
| 1145 | c_ref[m_index * n() + n_index] += |
| 1146 | a[m_index * a_stride() + k_index] * |
| 1147 | b[n_index * k() + k_index]; |
| 1148 | } |
| 1149 | c_ref[m_index * n() + n_index] += bias[n_index]; |
| 1150 | } |
| 1151 | } |
| 1152 | |
| 1153 | const float accumulated_min = *std::min_element(c_ref.cbegin(), c_ref.cend()); |
| 1154 | const float accumulated_max = *std::max_element(c_ref.cbegin(), c_ref.cend()); |
Zhi An Ng | 70ea0a2 | 2022-01-20 10:55:00 -0800 | [diff] [blame] | 1155 | const float c_min = |
| 1156 | qmin() == std::numeric_limits<uint8_t>::min() ? -std::numeric_limits<float>::infinity() |
| 1157 | : accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()); |
| 1158 | const float c_max = |
| 1159 | qmax() == std::numeric_limits<uint8_t>::max() ? +std::numeric_limits<float>::infinity() |
| 1160 | : accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()); |
Zhi An Ng | d90af6f | 2022-01-10 14:36:26 -0800 | [diff] [blame] | 1161 | |
| 1162 | // Prepare parameters. |
| 1163 | xnn_f32_minmax_params params; |
| 1164 | init_params(¶ms, c_min, c_max); |
| 1165 | |
| 1166 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1167 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1168 | c_ref[m_index * n() + n_index] = std::max(std::min(c_ref[m_index * n() + n_index], c_max), c_min); |
| 1169 | } |
| 1170 | } |
| 1171 | |
| 1172 | gemm_minmax(m(), n(), k() * sizeof(float), |
| 1173 | a.data(), a_stride() * sizeof(float), |
| 1174 | packed_w.data(), |
| 1175 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1176 | ¶ms); |
| 1177 | |
| 1178 | // Validate micro-kernel outputs. |
| 1179 | for (size_t i = 0; i < m(); i++) { |
| 1180 | for (size_t j = 0; j < n(); j++) { |
| 1181 | ASSERT_LE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_max) |
| 1182 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1183 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1184 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1185 | ASSERT_GE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_min) |
| 1186 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1187 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1188 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1189 | ASSERT_NEAR( |
| 1190 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1191 | c_ref[i * n() + j], |
| 1192 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1193 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1194 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1195 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1196 | } |
| 1197 | } |
| 1198 | } |
| 1199 | } |
| 1200 | |
| 1201 | void GemmMicrokernelTester::Test(xnn_f32_gemminc_minmax_ukernel_function gemminc, xnn_init_f32_minmax_params_fn init_params) const { |
| 1202 | ASSERT_LE(m(), mr()); |
| 1203 | ASSERT_GE(a_stride(), k()); |
| 1204 | ASSERT_GE(cm_stride(), n()); |
| 1205 | |
| 1206 | std::random_device random_device; |
| 1207 | auto rng = std::mt19937(random_device()); |
| 1208 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 1209 | |
| 1210 | std::vector<float> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1211 | std::vector<float> b(n() * k()); |
| 1212 | std::vector<float> bias(n()); |
| 1213 | std::vector<float, AlignedAllocator<float, 64>> packed_w(packed_n() * packed_k()); // no packed_n() |
| 1214 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1215 | std::vector<float> c_ref(m() * n()); |
| 1216 | std::vector<float, AlignedAllocator<float, 64>> acc(mr() * packed_n()); |
| 1217 | |
| 1218 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1219 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1220 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1221 | std::fill(c.begin(), c.end(), nanf("")); |
| 1222 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1223 | std::generate(acc.begin(), acc.end(), std::ref(f32rng)); |
| 1224 | |
| 1225 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1226 | xnn_pack_f32_gemminc_goi_w(1, n(), k(), nr(), kr(), sr(), b.data(), packed_w.data(), nullptr); |
| 1227 | |
| 1228 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1229 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1230 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1231 | ASSERT_LE(n(), packed_n()); |
| 1232 | ASSERT_LT(m_index * n() + n_index, c_ref.size()); |
| 1233 | c_ref[m_index * n() + n_index] += |
| 1234 | a[m_index * a_stride() + k_index] * |
| 1235 | b[n_index * k() + k_index]; |
| 1236 | } |
| 1237 | c_ref[m_index * n() + n_index] += acc[n_index / nr() * nr() * mr() + m_index % mr() * nr() + n_index % nr()]; |
| 1238 | } |
| 1239 | } |
| 1240 | |
| 1241 | const float accumulated_min = *std::min_element(c_ref.cbegin(), c_ref.cend()); |
| 1242 | const float accumulated_max = *std::max_element(c_ref.cbegin(), c_ref.cend()); |
| 1243 | const float c_min = accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()); |
| 1244 | const float c_max = accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()); |
| 1245 | |
| 1246 | // Prepare parameters. |
| 1247 | xnn_f32_minmax_params params; |
| 1248 | init_params(¶ms, c_min, c_max); |
| 1249 | |
| 1250 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1251 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1252 | c_ref[m_index * n() + n_index] = std::max(std::min(c_ref[m_index * n() + n_index], c_max), c_min); |
| 1253 | } |
| 1254 | } |
| 1255 | |
| 1256 | gemminc(m(), n(), k() * sizeof(float), |
| 1257 | a.data(), a_stride() * sizeof(float), |
| 1258 | packed_w.data(), |
| 1259 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1260 | acc.data(), |
| 1261 | ¶ms); |
| 1262 | |
| 1263 | // Validate micro-kernel outputs. |
| 1264 | for (size_t i = 0; i < m(); i++) { |
| 1265 | for (size_t j = 0; j < n(); j++) { |
| 1266 | ASSERT_LE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_max) |
| 1267 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1268 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1269 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1270 | ASSERT_GE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_min) |
| 1271 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1272 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1273 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1274 | ASSERT_NEAR( |
| 1275 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1276 | c_ref[i * n() + j], |
| 1277 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1278 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1279 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1280 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1281 | } |
| 1282 | } |
| 1283 | } |
| 1284 | } |
| 1285 | |
| 1286 | void GemmMicrokernelTester::Test(xnn_f32_igemm_ukernel_function igemm) const { |
| 1287 | ASSERT_LE(m(), mr()); |
| 1288 | |
| 1289 | std::random_device random_device; |
| 1290 | auto rng = std::mt19937(random_device()); |
| 1291 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 1292 | |
| 1293 | std::vector<float> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1294 | std::vector<float> b(n() * ks() * k()); |
| 1295 | std::vector<float, AlignedAllocator<float, 64>> packed_w(ks() * packed_k() * packed_n() + packed_n()); |
| 1296 | std::vector<float> bias(n()); |
| 1297 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1298 | std::vector<float> c_ref(m() * n()); |
| 1299 | std::vector<float> junk(k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1300 | std::vector<const float*> im2col(mr() * ks()); |
| 1301 | std::fill(junk.begin(), junk.end(), nanf("")); |
| 1302 | |
| 1303 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1304 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1305 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1306 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 1307 | std::fill(c.begin(), c.end(), nanf("")); |
| 1308 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1309 | |
| 1310 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1311 | xnn_pack_f32_conv_goki_w( |
| 1312 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 1313 | b.data(), bias.data(), packed_w.data(), 0 /* extra bytes */, nullptr); |
| 1314 | |
| 1315 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1316 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 1317 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 1318 | } |
| 1319 | } |
| 1320 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 1321 | if (zero_index() != SIZE_MAX) { |
| 1322 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1323 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 1324 | } |
| 1325 | } |
| 1326 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1327 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 1328 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 1329 | } |
| 1330 | } |
| 1331 | |
| 1332 | std::fill(c_ref.begin(), c_ref.end(), 0.0); |
| 1333 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1334 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1335 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1336 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1337 | ASSERT_LT(ks_index * mr() + m_index, im2col.size()); |
| 1338 | ASSERT_LT(k_index, k()); |
| 1339 | ASSERT_LT(k_index, a_stride()); |
| 1340 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 1341 | c_ref[m_index * n() + n_index] += |
| 1342 | (im2col[ks_index * mr() + m_index][k_index]) * |
| 1343 | (b[(n_index * ks() + ks_index) * k() + k_index]); |
| 1344 | } else { |
| 1345 | c_ref[m_index * n() + n_index] += |
| 1346 | (im2col[ks_index * mr() + m_index][k_index + a_offset()]) * |
| 1347 | (b[(n_index * ks() + ks_index) * k() + k_index]); |
| 1348 | } |
| 1349 | } |
| 1350 | } |
| 1351 | c_ref[m_index * n() + n_index] += bias[n_index]; |
| 1352 | } |
| 1353 | } |
| 1354 | |
| 1355 | const float* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 1356 | |
| 1357 | igemm( |
| 1358 | m(), n(), k() * sizeof(float), ks() * mr() * sizeof(void*), |
| 1359 | im2col.data(), packed_w.data(), |
| 1360 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1361 | a_offset() * sizeof(float), zero_pointer, |
| 1362 | nullptr); |
| 1363 | |
| 1364 | for (size_t i = 0; i < m(); i++) { |
| 1365 | for (size_t j = 0; j < n(); j++) { |
| 1366 | ASSERT_NEAR( |
| 1367 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1368 | c_ref[i * n() + j], |
| 1369 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1370 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1371 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1372 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1373 | } |
| 1374 | } |
| 1375 | } |
| 1376 | } |
| 1377 | |
| 1378 | void GemmMicrokernelTester::Test(xnn_f32_igemm_relu_ukernel_function igemm_relu) const { |
| 1379 | ASSERT_LE(m(), mr()); |
| 1380 | |
| 1381 | std::random_device random_device; |
| 1382 | auto rng = std::mt19937(random_device()); |
| 1383 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 1384 | |
| 1385 | std::vector<float> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1386 | std::vector<float> b(n() * ks() * k()); |
| 1387 | std::vector<float, AlignedAllocator<float, 64>> packed_w(ks() * packed_k() * packed_n() + packed_n()); |
| 1388 | std::vector<float> bias(n()); |
| 1389 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1390 | std::vector<float> c_ref(m() * n()); |
| 1391 | std::vector<float> junk(k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1392 | std::vector<const float*> im2col(mr() * ks()); |
| 1393 | std::fill(junk.begin(), junk.end(), nanf("")); |
| 1394 | |
| 1395 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1396 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1397 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1398 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 1399 | std::fill(c.begin(), c.end(), nanf("")); |
| 1400 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1401 | |
| 1402 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1403 | xnn_pack_f32_conv_goki_w( |
| 1404 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 1405 | b.data(), bias.data(), packed_w.data(), 0 /* extra bytes */, nullptr); |
| 1406 | |
| 1407 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1408 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 1409 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 1410 | } |
| 1411 | } |
| 1412 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 1413 | if (zero_index() != SIZE_MAX) { |
| 1414 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1415 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 1416 | } |
| 1417 | } |
| 1418 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1419 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 1420 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 1421 | } |
| 1422 | } |
| 1423 | |
| 1424 | std::fill(c_ref.begin(), c_ref.end(), 0.0); |
| 1425 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1426 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1427 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1428 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1429 | ASSERT_LT(ks_index * mr() + m_index, im2col.size()); |
| 1430 | ASSERT_LT(k_index, k()); |
| 1431 | ASSERT_LT(k_index, a_stride()); |
| 1432 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 1433 | c_ref[m_index * n() + n_index] += |
| 1434 | (im2col[ks_index * mr() + m_index][k_index]) * |
| 1435 | (b[(n_index * ks() + ks_index) * k() + k_index]); |
| 1436 | } else { |
| 1437 | c_ref[m_index * n() + n_index] += |
| 1438 | (im2col[ks_index * mr() + m_index][k_index + a_offset()]) * |
| 1439 | (b[(n_index * ks() + ks_index) * k() + k_index]); |
| 1440 | } |
| 1441 | } |
| 1442 | } |
| 1443 | c_ref[m_index * n() + n_index] = std::max(0.0f, bias[n_index] + c_ref[m_index * n() + n_index]); |
| 1444 | } |
| 1445 | } |
| 1446 | |
| 1447 | const float* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 1448 | |
| 1449 | igemm_relu( |
| 1450 | m(), n(), k() * sizeof(float), ks() * mr() * sizeof(void*), |
| 1451 | im2col.data(), packed_w.data(), |
| 1452 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1453 | a_offset() * sizeof(float), zero_pointer, |
| 1454 | nullptr); |
| 1455 | |
| 1456 | for (size_t i = 0; i < m(); i++) { |
| 1457 | for (size_t j = 0; j < n(); j++) { |
| 1458 | ASSERT_GE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], 0.0f) |
| 1459 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1460 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1461 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1462 | ASSERT_NEAR( |
| 1463 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1464 | c_ref[i * n() + j], |
| 1465 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1466 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1467 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1468 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1469 | } |
| 1470 | } |
| 1471 | } |
| 1472 | } |
| 1473 | |
| 1474 | void GemmMicrokernelTester::Test(xnn_f32_igemm_minmax_ukernel_function igemm_minmax, xnn_init_f32_minmax_params_fn init_params) const { |
| 1475 | ASSERT_LE(m(), mr()); |
| 1476 | |
| 1477 | std::random_device random_device; |
| 1478 | auto rng = std::mt19937(random_device()); |
| 1479 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 1480 | |
| 1481 | std::vector<float> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1482 | std::vector<float> b(n() * ks() * k()); |
| 1483 | std::vector<float, AlignedAllocator<float, 64>> packed_w(ks() * packed_k() * packed_n() + packed_n()); |
| 1484 | std::vector<float> bias(n()); |
| 1485 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1486 | std::vector<float> c_ref(m() * n()); |
| 1487 | std::vector<float> junk(k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1488 | std::vector<const float*> im2col(mr() * ks()); |
| 1489 | std::fill(junk.begin(), junk.end(), nanf("")); |
| 1490 | |
| 1491 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1492 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1493 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1494 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 1495 | std::fill(c.begin(), c.end(), nanf("")); |
| 1496 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1497 | |
| 1498 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1499 | xnn_pack_f32_conv_goki_w( |
| 1500 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 1501 | b.data(), bias.data(), packed_w.data(), 0 /* extra bytes */, nullptr); |
| 1502 | |
| 1503 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1504 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 1505 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 1506 | } |
| 1507 | } |
| 1508 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 1509 | if (zero_index() != SIZE_MAX) { |
| 1510 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1511 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 1512 | } |
| 1513 | } |
| 1514 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1515 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 1516 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 1517 | } |
| 1518 | } |
| 1519 | |
| 1520 | std::fill(c_ref.begin(), c_ref.end(), 0.0); |
| 1521 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1522 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1523 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1524 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1525 | ASSERT_LT(ks_index * mr() + m_index, im2col.size()); |
| 1526 | ASSERT_LT(k_index, k()); |
| 1527 | ASSERT_LT(k_index, a_stride()); |
| 1528 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 1529 | c_ref[m_index * n() + n_index] += |
| 1530 | (im2col[ks_index * mr() + m_index][k_index]) * |
| 1531 | (b[(n_index * ks() + ks_index) * k() + k_index]); |
| 1532 | } else { |
| 1533 | c_ref[m_index * n() + n_index] += |
| 1534 | (im2col[ks_index * mr() + m_index][k_index + a_offset()]) * |
| 1535 | (b[(n_index * ks() + ks_index) * k() + k_index]); |
| 1536 | } |
| 1537 | } |
| 1538 | } |
| 1539 | c_ref[m_index * n() + n_index] += bias[n_index]; |
| 1540 | } |
| 1541 | } |
| 1542 | |
| 1543 | const float accumulated_min = *std::min_element(c_ref.cbegin(), c_ref.cend()); |
| 1544 | const float accumulated_max = *std::max_element(c_ref.cbegin(), c_ref.cend()); |
| 1545 | const float c_min = accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()); |
| 1546 | const float c_max = accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()); |
| 1547 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1548 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1549 | c_ref[m_index * n() + n_index] = std::min(c_ref[m_index * n() + n_index], c_max); |
| 1550 | c_ref[m_index * n() + n_index] = std::max(c_ref[m_index * n() + n_index], c_min); |
| 1551 | } |
| 1552 | } |
| 1553 | |
| 1554 | // Prepare parameters. |
| 1555 | xnn_f32_minmax_params params; |
| 1556 | init_params(¶ms, c_min, c_max); |
| 1557 | |
| 1558 | const float* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 1559 | |
| 1560 | igemm_minmax( |
| 1561 | m(), n(), k() * sizeof(float), ks() * mr() * sizeof(void*), |
| 1562 | im2col.data(), packed_w.data(), |
| 1563 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1564 | a_offset() * sizeof(float), zero_pointer, |
| 1565 | ¶ms); |
| 1566 | |
| 1567 | for (size_t i = 0; i < m(); i++) { |
| 1568 | for (size_t j = 0; j < n(); j++) { |
| 1569 | ASSERT_LE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_max) |
| 1570 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1571 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1572 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1573 | ASSERT_GE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_min) |
| 1574 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1575 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1576 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1577 | ASSERT_NEAR( |
| 1578 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1579 | c_ref[i * n() + j], |
| 1580 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1581 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1582 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1583 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1584 | } |
| 1585 | } |
| 1586 | } |
| 1587 | } |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 1588 | |
| 1589 | #if XNN_PLATFORM_JIT |
| 1590 | void GemmMicrokernelTester::Test(xnn_jit_gemm_code_generator_function gemm_generator, xnn_init_f32_minmax_params_fn init_params) const { |
| 1591 | ASSERT_LE(m(), mr()); |
| 1592 | ASSERT_GE(a_stride(), k()); |
| 1593 | ASSERT_GE(cm_stride(), n()); |
| 1594 | |
| 1595 | std::random_device random_device; |
| 1596 | auto rng = std::mt19937(random_device()); |
| 1597 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 1598 | |
| 1599 | std::vector<float> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1600 | std::vector<float> b(n() * k()); |
| 1601 | std::vector<float> bias(n()); |
| 1602 | std::vector<float, AlignedAllocator<float, 64>> packed_w(packed_n() * packed_k() + packed_n()); |
| 1603 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1604 | std::vector<float> c_ref(m() * n()); |
| 1605 | |
| 1606 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1607 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1608 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1609 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 1610 | std::fill(c.begin(), c.end(), nanf("")); |
| 1611 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1612 | |
| 1613 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1614 | xnn_pack_f32_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), b.data(), bias.data(), packed_w.data(), 0, nullptr); |
| 1615 | |
| 1616 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1617 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1618 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1619 | ASSERT_LE(n(), packed_n()); |
| 1620 | ASSERT_LT(m_index * n() + n_index, c_ref.size()); |
| 1621 | c_ref[m_index * n() + n_index] += |
| 1622 | a[m_index * a_stride() + k_index] * |
| 1623 | b[n_index * k() + k_index]; |
| 1624 | } |
| 1625 | c_ref[m_index * n() + n_index] += bias[n_index]; |
| 1626 | } |
| 1627 | } |
| 1628 | |
| 1629 | const float accumulated_min = *std::min_element(c_ref.cbegin(), c_ref.cend()); |
| 1630 | const float accumulated_max = *std::max_element(c_ref.cbegin(), c_ref.cend()); |
Zhi An Ng | 70ea0a2 | 2022-01-20 10:55:00 -0800 | [diff] [blame] | 1631 | const float c_min = |
| 1632 | qmin() == std::numeric_limits<uint8_t>::min() ? -std::numeric_limits<float>::infinity() |
| 1633 | : accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()); |
| 1634 | const float c_max = |
| 1635 | qmax() == std::numeric_limits<uint8_t>::max() ? +std::numeric_limits<float>::infinity() |
| 1636 | : accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()); |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 1637 | |
| 1638 | // Prepare parameters. |
| 1639 | xnn_f32_minmax_params params; |
| 1640 | init_params(¶ms, c_min, c_max); |
| 1641 | |
| 1642 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1643 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1644 | c_ref[m_index * n() + n_index] = std::max(std::min(c_ref[m_index * n() + n_index], c_max), c_min); |
| 1645 | } |
| 1646 | } |
| 1647 | |
| 1648 | struct xnn_code_buffer code_buffer; |
| 1649 | ASSERT_EQ(xnn_status_success, xnn_allocate_code_memory(&code_buffer, XNN_DEFAULT_CODE_BUFFER_SIZE)); |
| 1650 | jit_gemm_params p = (jit_gemm_params) { |
Zhi An Ng | f9fc9ec | 2022-02-01 13:19:31 -0800 | [diff] [blame] | 1651 | .f32_minmax = { |
| 1652 | .min = c_min, |
| 1653 | .max = c_max |
| 1654 | } |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 1655 | }; |
Zhi An Ng | c2e2da8 | 2022-01-25 16:51:58 -0800 | [diff] [blame] | 1656 | ASSERT_EQ(xnn_status_success, gemm_generator(&code_buffer, n(), k() * sizeof(float), &p)); |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 1657 | xnn_f32_gemm_minmax_ukernel_function gemm_minmax = reinterpret_cast<xnn_f32_gemm_minmax_ukernel_function>(code_buffer.code); |
| 1658 | |
| 1659 | gemm_minmax(m(), n(), k() * sizeof(float), |
| 1660 | a.data(), a_stride() * sizeof(float), |
| 1661 | packed_w.data(), |
| 1662 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1663 | ¶ms); |
| 1664 | |
| 1665 | ASSERT_EQ(xnn_status_success, xnn_release_code_memory(&code_buffer)); |
| 1666 | |
| 1667 | // Validate micro-kernel outputs. |
| 1668 | for (size_t i = 0; i < m(); i++) { |
| 1669 | for (size_t j = 0; j < n(); j++) { |
| 1670 | ASSERT_LE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_max) |
| 1671 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1672 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1673 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1674 | ASSERT_GE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_min) |
| 1675 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1676 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1677 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1678 | ASSERT_NEAR( |
| 1679 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1680 | c_ref[i * n() + j], |
| 1681 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1682 | << "at " << i << ", " << j << ": reference = " << c_ref[i * n() + j] |
| 1683 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1684 | << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k(); |
| 1685 | } |
| 1686 | } |
| 1687 | } |
| 1688 | } |
| 1689 | |
| 1690 | void GemmMicrokernelTester::Test(xnn_jit_igemm_code_generator_function igemm_generator, xnn_init_f32_minmax_params_fn init_params) const { |
| 1691 | ASSERT_LE(m(), mr()); |
| 1692 | |
| 1693 | std::random_device random_device; |
| 1694 | auto rng = std::mt19937(random_device()); |
| 1695 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), std::ref(rng)); |
| 1696 | |
| 1697 | std::vector<float> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1698 | std::vector<float> b(n() * ks() * k()); |
| 1699 | std::vector<float, AlignedAllocator<float, 64>> packed_w(ks() * packed_k() * packed_n() + packed_n()); |
| 1700 | std::vector<float> bias(n()); |
| 1701 | std::vector<float> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1702 | std::vector<float> c_ref(m() * n()); |
| 1703 | std::vector<float> junk(k() + XNN_EXTRA_BYTES / sizeof(float)); |
| 1704 | std::vector<const float*> im2col(mr() * ks()); |
| 1705 | std::fill(junk.begin(), junk.end(), nanf("")); |
| 1706 | |
| 1707 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1708 | std::generate(a.begin(), a.end(), std::ref(f32rng)); |
| 1709 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 1710 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
| 1711 | std::fill(c.begin(), c.end(), nanf("")); |
| 1712 | std::fill(c_ref.begin(), c_ref.end(), 0.0f); |
| 1713 | |
| 1714 | std::fill(packed_w.begin(), packed_w.end(), 0.0f); |
| 1715 | xnn_pack_f32_conv_goki_w( |
| 1716 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 1717 | b.data(), bias.data(), packed_w.data(), 0 /* extra bytes */, nullptr); |
| 1718 | |
| 1719 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1720 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 1721 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 1722 | } |
| 1723 | } |
| 1724 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 1725 | if (zero_index() != SIZE_MAX) { |
| 1726 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1727 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 1728 | } |
| 1729 | } |
| 1730 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1731 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 1732 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 1733 | } |
| 1734 | } |
| 1735 | |
| 1736 | std::fill(c_ref.begin(), c_ref.end(), 0.0); |
| 1737 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1738 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1739 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1740 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1741 | ASSERT_LT(ks_index * mr() + m_index, im2col.size()); |
| 1742 | ASSERT_LT(k_index, k()); |
| 1743 | ASSERT_LT(k_index, a_stride()); |
| 1744 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 1745 | c_ref[m_index * n() + n_index] += |
| 1746 | (im2col[ks_index * mr() + m_index][k_index]) * |
| 1747 | (b[(n_index * ks() + ks_index) * k() + k_index]); |
| 1748 | } else { |
| 1749 | c_ref[m_index * n() + n_index] += |
| 1750 | (im2col[ks_index * mr() + m_index][k_index + a_offset()]) * |
| 1751 | (b[(n_index * ks() + ks_index) * k() + k_index]); |
| 1752 | } |
| 1753 | } |
| 1754 | } |
| 1755 | c_ref[m_index * n() + n_index] += bias[n_index]; |
| 1756 | } |
| 1757 | } |
| 1758 | |
| 1759 | const float accumulated_min = *std::min_element(c_ref.cbegin(), c_ref.cend()); |
| 1760 | const float accumulated_max = *std::max_element(c_ref.cbegin(), c_ref.cend()); |
| 1761 | const float c_min = accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()); |
| 1762 | const float c_max = accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()); |
| 1763 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1764 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1765 | c_ref[m_index * n() + n_index] = std::min(c_ref[m_index * n() + n_index], c_max); |
| 1766 | c_ref[m_index * n() + n_index] = std::max(c_ref[m_index * n() + n_index], c_min); |
| 1767 | } |
| 1768 | } |
| 1769 | |
| 1770 | // Prepare parameters. |
| 1771 | xnn_f32_minmax_params params; |
| 1772 | init_params(¶ms, c_min, c_max); |
| 1773 | |
| 1774 | const float* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 1775 | |
| 1776 | struct xnn_code_buffer code_buffer; |
| 1777 | ASSERT_EQ(xnn_status_success, xnn_allocate_code_memory(&code_buffer, XNN_DEFAULT_CODE_BUFFER_SIZE)); |
| 1778 | jit_gemm_params p = (jit_gemm_params) { |
| 1779 | .f32_minmax = { |
Zhi An Ng | f9fc9ec | 2022-02-01 13:19:31 -0800 | [diff] [blame] | 1780 | .min = c_min, |
| 1781 | .max = c_max |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 1782 | } |
| 1783 | }; |
| 1784 | ASSERT_EQ(xnn_status_success, igemm_generator(&code_buffer,n(), k() * sizeof(float), ks() * mr() * sizeof(void*), &p)); |
| 1785 | xnn_f32_igemm_minmax_ukernel_function igemm_minmax = reinterpret_cast<xnn_f32_igemm_minmax_ukernel_function>(code_buffer.code); |
| 1786 | |
| 1787 | igemm_minmax( |
| 1788 | m(), n(), k() * sizeof(float), ks() * mr() * sizeof(void*), |
| 1789 | im2col.data(), packed_w.data(), |
| 1790 | c.data(), cm_stride() * sizeof(float), cn_stride() * sizeof(float), |
| 1791 | a_offset() * sizeof(float), zero_pointer, |
| 1792 | ¶ms); |
| 1793 | |
| 1794 | ASSERT_EQ(xnn_status_success, xnn_release_code_memory(&code_buffer)); |
| 1795 | |
| 1796 | for (size_t i = 0; i < m(); i++) { |
| 1797 | for (size_t j = 0; j < n(); j++) { |
| 1798 | ASSERT_LE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_max) |
| 1799 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1800 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1801 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1802 | ASSERT_GE(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], c_min) |
| 1803 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1804 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1805 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1806 | ASSERT_NEAR( |
| 1807 | c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()], |
| 1808 | c_ref[i * n() + j], |
| 1809 | std::abs(c_ref[i * n() + j]) * 1.0e-6f) |
| 1810 | << "at " << i << ", " << i << ": reference = " << c_ref[i * n() + j] |
| 1811 | << ", optimized = " << c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " << nr() |
| 1812 | << " x " << kr() << ", M x N x KC x KS = " << m() << " x " << n() << " x " << k() << " x " << ks(); |
| 1813 | } |
| 1814 | } |
| 1815 | } |
| 1816 | } |
| 1817 | |
| 1818 | void GemmMicrokernelTester::Test( |
| 1819 | xnn_jit_gemm_code_generator_function gemm_generator, |
| 1820 | xnn_init_qs8_minmax_params_fn init_params, |
| 1821 | xnn_qs8_requantize_fn requantize) const |
| 1822 | { |
| 1823 | ASSERT_LE(m(), mr()); |
| 1824 | |
| 1825 | std::random_device random_device; |
| 1826 | auto rng = std::mt19937(random_device()); |
| 1827 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 1828 | auto i8rng = std::bind( |
| 1829 | std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), |
| 1830 | std::ref(rng)); |
| 1831 | auto w8rng = std::bind( |
| 1832 | std::uniform_int_distribution<int32_t>(-std::numeric_limits<int8_t>::max(), std::numeric_limits<int8_t>::max()), |
| 1833 | std::ref(rng)); |
| 1834 | |
| 1835 | std::vector<int8_t> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(int8_t)); |
| 1836 | std::vector<int8_t> b(n() * k()); |
| 1837 | std::vector<int32_t> bias(n()); |
| 1838 | std::vector<int8_t, AlignedAllocator<int8_t, 64>> packed_w(packed_n() * packed_k() + packed_n() * (sizeof(int32_t) + sizeof(float)) / sizeof(int8_t)); |
| 1839 | std::vector<int16_t, AlignedAllocator<int16_t, 64>> packed_xw(packed_n() * packed_k() + packed_n() * (sizeof(int32_t) + sizeof(float)) / sizeof(int16_t)); |
| 1840 | std::vector<int8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1841 | std::vector<int32_t> acc(m() * n()); |
| 1842 | std::vector<float> scale(n()); |
| 1843 | std::vector<int8_t> c_ref(m() * n()); |
| 1844 | |
| 1845 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1846 | do { |
| 1847 | std::generate(a.begin(), a.end(), std::ref(i8rng)); |
| 1848 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 1849 | do { |
| 1850 | std::generate(b.begin(), b.end(), std::ref(w8rng)); |
| 1851 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 1852 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 1853 | std::fill(c.begin(), c.end(), 0xA5); |
| 1854 | |
| 1855 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 1856 | const xnn_qs8_packing_params packing_params = { int8_t(a_zero_point() - 0x80) }; |
| 1857 | if (extended_weights()) { |
| 1858 | xnn_pack_qs8_gemm_xw_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 1859 | b.data(), bias.data(), packed_xw.data(), nr() * sizeof(float), &packing_params); |
| 1860 | } else { |
| 1861 | xnn_pack_qs8_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 1862 | b.data(), bias.data(), packed_w.data(), nr() * sizeof(float), &packing_params); |
| 1863 | } |
| 1864 | |
| 1865 | // Compute 32-bit results and output quantization arguments. |
| 1866 | std::fill(acc.begin(), acc.end(), 0); |
| 1867 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1868 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1869 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 1870 | acc[m_index * n() + n_index] += |
| 1871 | (int32_t(a[m_index * a_stride() + k_index]) - int32_t(a_zero_point() - 0x80)) * |
| 1872 | int32_t(b[n_index * k() + k_index]); |
| 1873 | } |
| 1874 | acc[m_index * n() + n_index] += bias[n_index]; |
| 1875 | } |
| 1876 | } |
| 1877 | |
| 1878 | const int8_t c_zero_point = -1; |
| 1879 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1880 | int32_t accumulated_min = acc[n_index]; |
| 1881 | int32_t accumulated_max = acc[n_index]; |
| 1882 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1883 | accumulated_min = std::min(accumulated_min, acc[m_index * n() + n_index]); |
| 1884 | accumulated_max = std::max(accumulated_max, acc[m_index * n() + n_index]); |
| 1885 | } |
| 1886 | const uint32_t accumulated_range = uint32_t(accumulated_max - accumulated_min); |
| 1887 | const float c_scale = accumulated_range >= 256 ? double(accumulated_range) / 255.0 : 1.00001; |
| 1888 | scale[n_index] = 1.0f / c_scale; |
| 1889 | } |
| 1890 | |
| 1891 | if (extended_weights()) { |
| 1892 | xnn_init_qc8_scale_fp32_params( |
| 1893 | n(), nr(), |
| 1894 | nr() * (packed_k() * sizeof(int16_t) + (sizeof(int32_t) + sizeof(float))), scale.data(), |
| 1895 | (void*) ((uintptr_t) packed_xw.data() + nr() * (packed_k() * sizeof(int16_t) + sizeof(int32_t)))); |
| 1896 | } else { |
| 1897 | xnn_init_qc8_scale_fp32_params( |
| 1898 | n(), nr(), |
| 1899 | nr() * (packed_k() * sizeof(int8_t) + (sizeof(int32_t) + sizeof(float))), scale.data(), |
| 1900 | (void*) ((uintptr_t) packed_w.data() + nr() * (packed_k() * sizeof(int8_t) + sizeof(int32_t)))); |
| 1901 | } |
| 1902 | |
| 1903 | union xnn_qs8_minmax_params minmax_params; |
| 1904 | init_params(&minmax_params, |
| 1905 | c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
| 1906 | |
| 1907 | struct xnn_code_buffer code_buffer; |
| 1908 | ASSERT_EQ(xnn_status_success, xnn_allocate_code_memory(&code_buffer, XNN_DEFAULT_CODE_BUFFER_SIZE)); |
Zhi An Ng | 60c9bcb | 2022-02-02 14:53:28 -0800 | [diff] [blame] | 1909 | ASSERT_EQ(xnn_status_success, gemm_generator(&code_buffer, n(), k(), nullptr)); |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 1910 | xnn_qc8_gemm_minmax_ukernel_function gemm = reinterpret_cast<xnn_qc8_gemm_minmax_ukernel_function>(code_buffer.code); |
| 1911 | |
| 1912 | gemm( |
| 1913 | m(), n(), k(), |
| 1914 | a.data(), a_stride() * sizeof(int8_t), |
| 1915 | extended_weights() ? static_cast<const void*>(packed_xw.data()) : static_cast<const void*>(packed_w.data()), |
| 1916 | c.data(), cm_stride() * sizeof(int8_t), cn_stride() * sizeof(int8_t), |
| 1917 | &minmax_params); |
| 1918 | |
| 1919 | ASSERT_EQ(xnn_status_success, xnn_release_code_memory(&code_buffer)); |
| 1920 | |
| 1921 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 1922 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 1923 | c_ref[m_index * n() + n_index] = requantize( |
| 1924 | acc[m_index * n() + n_index], scale[n_index], c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
| 1925 | } |
| 1926 | } |
| 1927 | |
| 1928 | for (size_t i = 0; i < m(); i++) { |
| 1929 | for (size_t j = 0; j < n(); j++) { |
| 1930 | ASSERT_LE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmax()) - 0x80); |
| 1931 | ASSERT_GE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmin()) - 0x80); |
| 1932 | ASSERT_EQ(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(c_ref[i * n() + j])) |
| 1933 | << "at " << i << ", " << j << ": reference = " << int32_t(c_ref[i * n() + j]) |
| 1934 | << " (accumulator = " << acc[i * n() + j] |
| 1935 | << "), optimized = " << int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]) << ", Mr x Nr x Kr = " << mr() << " x " |
| 1936 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 1937 | << ", requantization scale = " << scale[j] << ", output zero point = " << int32_t(c_zero_point); |
| 1938 | } |
| 1939 | } |
| 1940 | } |
| 1941 | } |
| 1942 | |
| 1943 | void GemmMicrokernelTester::Test( |
| 1944 | xnn_jit_igemm_code_generator_function igemm_generator, |
| 1945 | xnn_init_qs8_minmax_params_fn init_params, |
| 1946 | xnn_qs8_requantize_fn requantize) const |
| 1947 | { |
| 1948 | ASSERT_LE(m(), mr()); |
| 1949 | |
| 1950 | std::random_device random_device; |
| 1951 | auto rng = std::mt19937(random_device()); |
| 1952 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 1953 | auto i8rng = std::bind( |
| 1954 | std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), |
| 1955 | std::ref(rng)); |
| 1956 | auto w8rng = std::bind( |
| 1957 | std::uniform_int_distribution<int32_t>(-std::numeric_limits<int8_t>::max(), std::numeric_limits<int8_t>::max()), |
| 1958 | std::ref(rng)); |
| 1959 | |
| 1960 | std::vector<int8_t> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(uint8_t)); |
| 1961 | std::vector<int8_t> b(n() * ks() * k()); |
| 1962 | std::vector<int8_t, AlignedAllocator<int8_t, 64>> packed_w(ks() * packed_n() * packed_k() + packed_n() * (sizeof(int32_t) + sizeof(float)) / sizeof(int8_t)); |
| 1963 | std::vector<int32_t> bias(n()); |
| 1964 | std::vector<int8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 1965 | std::vector<int32_t> acc(m() * n()); |
| 1966 | std::vector<float> scale(n()); |
| 1967 | std::vector<int8_t> c_ref(m() * n()); |
| 1968 | std::vector<int8_t> junk(k() + 8); |
| 1969 | std::vector<const int8_t*> im2col(mr() * ks()); |
| 1970 | |
| 1971 | std::fill(junk.begin(), junk.end(), 0xA5); |
| 1972 | |
| 1973 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 1974 | do { |
| 1975 | std::generate(a.begin(), a.end(), std::ref(i8rng)); |
| 1976 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 1977 | do { |
| 1978 | std::generate(b.begin(), b.end(), std::ref(w8rng)); |
| 1979 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 1980 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 1981 | std::fill(c.begin(), c.end(), 0xA5); |
| 1982 | |
| 1983 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 1984 | const xnn_qs8_packing_params packing_params = { int8_t(a_zero_point() - 0x80) }; |
| 1985 | xnn_pack_qs8_conv_goki_w( |
| 1986 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 1987 | b.data(), bias.data(), packed_w.data(), nr() * sizeof(float), &packing_params); |
| 1988 | |
| 1989 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1990 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 1991 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 1992 | } |
| 1993 | } |
| 1994 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 1995 | if (zero_index() != SIZE_MAX) { |
| 1996 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 1997 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 1998 | } |
| 1999 | } |
| 2000 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 2001 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 2002 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 2003 | } |
| 2004 | } |
| 2005 | |
| 2006 | // Compute 32-bit results and output quantization arguments. |
| 2007 | std::fill(acc.begin(), acc.end(), 0); |
| 2008 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 2009 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 2010 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 2011 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 2012 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 2013 | acc[m_index * n() + n_index] += |
| 2014 | (int32_t(im2col[ks_index * mr() + m_index][k_index]) - int32_t(a_zero_point() - 0x80)) * |
| 2015 | int32_t(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 2016 | } else { |
| 2017 | acc[m_index * n() + n_index] += |
| 2018 | (int32_t(im2col[ks_index * mr() + m_index][k_index + a_offset()]) - int32_t(a_zero_point() - 0x80)) * |
| 2019 | int32_t(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 2020 | } |
| 2021 | } |
| 2022 | } |
| 2023 | acc[m_index * n() + n_index] += bias[n_index]; |
| 2024 | } |
| 2025 | } |
| 2026 | |
| 2027 | const int8_t c_zero_point = -1; |
| 2028 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 2029 | int32_t accumulated_min = acc[n_index]; |
| 2030 | int32_t accumulated_max = acc[n_index]; |
| 2031 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 2032 | accumulated_min = std::min(accumulated_min, acc[m_index * n() + n_index]); |
| 2033 | accumulated_max = std::max(accumulated_max, acc[m_index * n() + n_index]); |
| 2034 | } |
| 2035 | const uint32_t accumulated_range = uint32_t(accumulated_max - accumulated_min); |
| 2036 | const float c_scale = accumulated_range >= 256 ? double(accumulated_range) / 255.0 : 1.00001; |
| 2037 | scale[n_index] = 1.0f / c_scale; |
| 2038 | } |
| 2039 | |
| 2040 | xnn_init_qc8_scale_fp32_params( |
| 2041 | n(), nr(), |
| 2042 | nr() * (ks() * packed_k() * sizeof(int8_t) + (sizeof(int32_t) + sizeof(float))), scale.data(), |
| 2043 | (void*) ((uintptr_t) packed_w.data() + nr() * (ks() * packed_k() * sizeof(int8_t) + sizeof(int32_t)))); |
| 2044 | |
| 2045 | union xnn_qs8_minmax_params minmax_params; |
| 2046 | init_params(&minmax_params, |
| 2047 | c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
| 2048 | |
| 2049 | const int8_t* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 2050 | |
| 2051 | struct xnn_code_buffer code_buffer; |
| 2052 | ASSERT_EQ(xnn_status_success, xnn_allocate_code_memory(&code_buffer, XNN_DEFAULT_CODE_BUFFER_SIZE)); |
Zhi An Ng | 60c9bcb | 2022-02-02 14:53:28 -0800 | [diff] [blame] | 2053 | ASSERT_EQ(xnn_status_success, igemm_generator(&code_buffer,n(), k(), ks() * mr() * sizeof(void*), nullptr)); |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 2054 | xnn_qc8_igemm_minmax_ukernel_function igemm = reinterpret_cast<xnn_qc8_igemm_minmax_ukernel_function>(code_buffer.code); |
| 2055 | |
| 2056 | igemm( |
| 2057 | m(), n(), k(), ks() * mr() * sizeof(void*), |
| 2058 | im2col.data(), packed_w.data(), |
| 2059 | c.data(), cm_stride() * sizeof(int8_t), cn_stride() * sizeof(int8_t), |
| 2060 | a_offset() * sizeof(uint8_t), zero_pointer, |
| 2061 | &minmax_params); |
| 2062 | |
| 2063 | ASSERT_EQ(xnn_status_success, xnn_release_code_memory(&code_buffer)); |
| 2064 | |
| 2065 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 2066 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 2067 | c_ref[m_index * n() + n_index] = requantize( |
| 2068 | acc[m_index * n() + n_index], scale[n_index], c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
| 2069 | } |
| 2070 | } |
| 2071 | |
| 2072 | for (size_t i = 0; i < m(); i++) { |
| 2073 | for (size_t j = 0; j < n(); j++) { |
| 2074 | ASSERT_LE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmax()) - 0x80); |
| 2075 | ASSERT_GE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmin()) - 0x80); |
| 2076 | ASSERT_EQ(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(c_ref[i * n() + j])) |
| 2077 | << "at " << i << ", " << j << ": reference = " << uint32_t(c_ref[i * n() + j]) |
| 2078 | << " (accumulator = " << acc[i * n() + j] |
| 2079 | << "), optimized = " << (uint32_t) c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " |
| 2080 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 2081 | << ", requantization scale = " << scale[j] << ", output zero point = " << int32_t(c_zero_point); |
| 2082 | } |
| 2083 | } |
| 2084 | } |
| 2085 | } |
| 2086 | |
| 2087 | void GemmMicrokernelTester::Test( |
| 2088 | xnn_jit_gemm_code_generator_function gemm_generator, |
| 2089 | xnn_init_qs8_conv_minmax_params_fn init_params, |
| 2090 | xnn_qs8_requantize_fn requantize) const |
| 2091 | { |
| 2092 | ASSERT_LE(m(), mr()); |
| 2093 | |
| 2094 | std::random_device random_device; |
| 2095 | auto rng = std::mt19937(random_device()); |
| 2096 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 2097 | auto i8rng = std::bind( |
| 2098 | std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), |
| 2099 | std::ref(rng)); |
| 2100 | auto w8rng = std::bind( |
| 2101 | std::uniform_int_distribution<int32_t>(-std::numeric_limits<int8_t>::max(), std::numeric_limits<int8_t>::max()), |
| 2102 | std::ref(rng)); |
| 2103 | |
| 2104 | std::vector<int8_t> a((m() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(int8_t)); |
| 2105 | std::vector<int8_t> b(n() * k()); |
| 2106 | std::vector<int32_t> bias(n()); |
| 2107 | std::vector<int8_t, AlignedAllocator<int8_t, 64>> packed_w(packed_n() * packed_k() + packed_n() * sizeof(int32_t) / sizeof(int8_t)); |
| 2108 | std::vector<int16_t, AlignedAllocator<int16_t, 64>> packed_xw(packed_n() * packed_k() + packed_n() * sizeof(int32_t) / sizeof(int16_t)); |
| 2109 | std::vector<int8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 2110 | std::vector<int32_t> acc(m() * n()); |
| 2111 | std::vector<int8_t> c_ref(m() * n()); |
| 2112 | |
| 2113 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 2114 | do { |
| 2115 | std::generate(a.begin(), a.end(), std::ref(i8rng)); |
| 2116 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 2117 | do { |
| 2118 | std::generate(b.begin(), b.end(), std::ref(w8rng)); |
| 2119 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 2120 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 2121 | std::fill(c.begin(), c.end(), 0xA5); |
| 2122 | |
| 2123 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 2124 | const xnn_qs8_packing_params packing_params = { int8_t(a_zero_point() - 0x80) }; |
| 2125 | if (extended_weights()) { |
| 2126 | xnn_pack_qs8_gemm_xw_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 2127 | b.data(), bias.data(), packed_xw.data(), 0, &packing_params); |
| 2128 | } else { |
| 2129 | xnn_pack_qs8_gemm_goi_w(1, n(), k(), nr(), kr(), sr(), |
| 2130 | b.data(), bias.data(), packed_w.data(), 0, &packing_params); |
| 2131 | } |
| 2132 | |
| 2133 | // Compute 32-bit results and output quantization arguments. |
| 2134 | std::fill(acc.begin(), acc.end(), 0); |
| 2135 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 2136 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 2137 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 2138 | acc[m_index * n() + n_index] += |
| 2139 | (int32_t(a[m_index * a_stride() + k_index]) - int32_t(a_zero_point() - 0x80)) * |
| 2140 | int32_t(b[n_index * k() + k_index]); |
| 2141 | } |
| 2142 | acc[m_index * n() + n_index] += bias[n_index]; |
| 2143 | } |
| 2144 | } |
| 2145 | |
| 2146 | const int32_t accumulated_min = *std::min_element(acc.cbegin(), acc.cend()); |
| 2147 | const int32_t accumulated_max = *std::max_element(acc.cbegin(), acc.cend()); |
| 2148 | const double c_scale = uint32_t(accumulated_max - accumulated_min) >= 256 ? double(uint32_t(accumulated_max - accumulated_min)) / 255.0 : 1.00001; |
| 2149 | const int8_t c_zero_point = int8_t(std::max(std::min( |
| 2150 | lrint(-0.5 - 0.5 * double(accumulated_min + accumulated_max) / c_scale), |
| 2151 | long(std::numeric_limits<int8_t>::max())), long(std::numeric_limits<int8_t>::min()))); |
| 2152 | |
| 2153 | const float requantization_scale = 1.0f / float(c_scale); |
| 2154 | union xnn_qs8_conv_minmax_params quantization_params; |
| 2155 | init_params(&quantization_params, |
| 2156 | requantization_scale, c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
| 2157 | |
| 2158 | struct xnn_code_buffer code_buffer; |
| 2159 | ASSERT_EQ(xnn_status_success, xnn_allocate_code_memory(&code_buffer, XNN_DEFAULT_CODE_BUFFER_SIZE)); |
Zhi An Ng | 60c9bcb | 2022-02-02 14:53:28 -0800 | [diff] [blame] | 2160 | ASSERT_EQ(xnn_status_success, gemm_generator(&code_buffer,n(), k(), nullptr)); |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 2161 | xnn_qs8_gemm_minmax_ukernel_function gemm = reinterpret_cast<xnn_qs8_gemm_minmax_ukernel_function >(code_buffer.code); |
| 2162 | |
| 2163 | gemm( |
| 2164 | m(), n(), k(), |
| 2165 | a.data(), a_stride() * sizeof(int8_t), |
| 2166 | extended_weights() ? static_cast<const void*>(packed_xw.data()) : static_cast<const void*>(packed_w.data()), |
| 2167 | c.data(), cm_stride() * sizeof(int8_t), cn_stride() * sizeof(int8_t), |
| 2168 | &quantization_params); |
| 2169 | |
| 2170 | ASSERT_EQ(xnn_status_success, xnn_release_code_memory(&code_buffer)); |
| 2171 | |
| 2172 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 2173 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 2174 | c_ref[m_index * n() + n_index] = requantize( |
| 2175 | acc[m_index * n() + n_index], requantization_scale, c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
| 2176 | } |
| 2177 | } |
| 2178 | |
| 2179 | for (size_t i = 0; i < m(); i++) { |
| 2180 | for (size_t j = 0; j < n(); j++) { |
| 2181 | ASSERT_LE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmax()) - 0x80); |
| 2182 | ASSERT_GE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmin()) - 0x80); |
| 2183 | ASSERT_EQ(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(c_ref[i * n() + j])) |
| 2184 | << "at " << i << ", " << j << ": reference = " << int32_t(c_ref[i * n() + j]) |
| 2185 | << " (accumulator = " << acc[i * n() + j] |
| 2186 | << "), optimized = " << int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]) << ", Mr x Nr x Kr = " << mr() << " x " |
| 2187 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 2188 | << ", requantization scale = " << requantization_scale << ", output zero point = " << int32_t(c_zero_point); |
| 2189 | } |
| 2190 | } |
| 2191 | } |
| 2192 | } |
| 2193 | |
| 2194 | void GemmMicrokernelTester::Test( |
| 2195 | xnn_jit_igemm_code_generator_function igemm_generator, |
| 2196 | xnn_init_qs8_conv_minmax_params_fn init_params, |
| 2197 | xnn_qs8_requantize_fn requantize) const |
| 2198 | { |
| 2199 | ASSERT_LE(m(), mr()); |
| 2200 | |
| 2201 | std::random_device random_device; |
| 2202 | auto rng = std::mt19937(random_device()); |
| 2203 | auto i32rng = std::bind(std::uniform_int_distribution<int32_t>(-10000, 10000), std::ref(rng)); |
| 2204 | auto i8rng = std::bind( |
| 2205 | std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), |
| 2206 | std::ref(rng)); |
| 2207 | auto w8rng = std::bind( |
| 2208 | std::uniform_int_distribution<int32_t>(-std::numeric_limits<int8_t>::max(), std::numeric_limits<int8_t>::max()), |
| 2209 | std::ref(rng)); |
| 2210 | |
| 2211 | std::vector<int8_t> a((mr() - 1) * a_stride() + k() + XNN_EXTRA_BYTES / sizeof(uint8_t)); |
| 2212 | std::vector<int8_t> b(n() * ks() * k()); |
| 2213 | std::vector<int8_t, AlignedAllocator<int8_t, 64>> packed_w(ks() * packed_n() * packed_k() + packed_n() * sizeof(int32_t) / sizeof(int8_t)); |
| 2214 | std::vector<int32_t> bias(n()); |
| 2215 | std::vector<int8_t> c((mr() - 1) * cm_stride() + ((n() - 1) / nr()) * cn_stride() + (n() - 1) % nr() + 1); |
| 2216 | std::vector<int32_t> acc(m() * n()); |
| 2217 | std::vector<int8_t> c_ref(m() * n()); |
| 2218 | std::vector<int8_t> junk(k() + 8); |
| 2219 | std::vector<const int8_t*> im2col(mr() * ks()); |
| 2220 | |
| 2221 | std::fill(junk.begin(), junk.end(), 0xA5); |
| 2222 | |
| 2223 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 2224 | do { |
| 2225 | std::generate(a.begin(), a.end(), std::ref(i8rng)); |
| 2226 | } while (a.size() > 1 && *std::max_element(a.cbegin(), a.cend()) == *std::min_element(a.cbegin(), a.cend())); |
| 2227 | do { |
| 2228 | std::generate(b.begin(), b.end(), std::ref(w8rng)); |
| 2229 | } while (b.size() > 1 && *std::max_element(b.cbegin(), b.cend()) == *std::min_element(b.cbegin(), b.cend())); |
| 2230 | std::generate(bias.begin(), bias.end(), std::ref(i32rng)); |
| 2231 | std::fill(c.begin(), c.end(), 0xA5); |
| 2232 | |
| 2233 | std::fill(packed_w.begin(), packed_w.end(), 0); |
| 2234 | const xnn_qs8_packing_params packing_params = { int8_t(a_zero_point() - 0x80) }; |
| 2235 | xnn_pack_qs8_conv_goki_w( |
| 2236 | 1, n(), ks(), k(), nr(), kr(), sr(), |
| 2237 | b.data(), bias.data(), packed_w.data(), 0 /* extra bytes */, &packing_params); |
| 2238 | |
| 2239 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 2240 | for (size_t m_index = 0; m_index < mr(); m_index++) { |
| 2241 | im2col[ks_index * mr() + m_index] = a.data() + a_stride() * m_index - a_offset(); |
| 2242 | } |
| 2243 | } |
| 2244 | std::shuffle(im2col.begin(), im2col.end(), rng); |
| 2245 | if (zero_index() != SIZE_MAX) { |
| 2246 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 2247 | im2col[ks_index * mr() + zero_index()] = a.data(); |
| 2248 | } |
| 2249 | } |
| 2250 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 2251 | for (size_t m_index = m(); m_index < mr(); m_index++) { |
| 2252 | im2col[ks_index * mr() + m_index] = junk.data(); |
| 2253 | } |
| 2254 | } |
| 2255 | |
| 2256 | // Compute 32-bit results and output quantization arguments. |
| 2257 | std::fill(acc.begin(), acc.end(), 0); |
| 2258 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 2259 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 2260 | for (size_t ks_index = 0; ks_index < ks(); ks_index++) { |
| 2261 | for (size_t k_index = 0; k_index < k(); k_index++) { |
| 2262 | if (im2col[ks_index * mr() + m_index] == a.data()) { |
| 2263 | acc[m_index * n() + n_index] += |
| 2264 | (int32_t(im2col[ks_index * mr() + m_index][k_index]) - int32_t(a_zero_point() - 0x80)) * |
| 2265 | int32_t(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 2266 | } else { |
| 2267 | acc[m_index * n() + n_index] += |
| 2268 | (int32_t(im2col[ks_index * mr() + m_index][k_index + a_offset()]) - int32_t(a_zero_point() - 0x80)) * |
| 2269 | int32_t(b[(n_index * ks() + ks_index) * k() + k_index]); |
| 2270 | } |
| 2271 | } |
| 2272 | } |
| 2273 | acc[m_index * n() + n_index] += bias[n_index]; |
| 2274 | } |
| 2275 | } |
| 2276 | |
| 2277 | const int32_t accumulated_min = *std::min_element(acc.cbegin(), acc.cend()); |
| 2278 | const int32_t accumulated_max = *std::max_element(acc.cbegin(), acc.cend()); |
| 2279 | const double c_scale = uint32_t(accumulated_max - accumulated_min) >= 256 ? double(uint32_t(accumulated_max - accumulated_min)) / 255.0 : 1.00001; |
| 2280 | const uint8_t c_zero_point = uint8_t(std::max(std::min( |
| 2281 | lrint(-0.5 - 0.5 * double(accumulated_min + accumulated_max) / c_scale), |
| 2282 | long(std::numeric_limits<int8_t>::max())), long(std::numeric_limits<int8_t>::min()))); |
| 2283 | |
| 2284 | const float requantization_scale = 1.0f / float(c_scale); |
| 2285 | union xnn_qs8_conv_minmax_params quantization_params; |
| 2286 | init_params(&quantization_params, |
| 2287 | requantization_scale, c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
| 2288 | |
| 2289 | const int8_t* zero_pointer = (zero_index() != SIZE_MAX) ? a.data() : NULL; |
| 2290 | |
| 2291 | struct xnn_code_buffer code_buffer; |
| 2292 | ASSERT_EQ(xnn_status_success, xnn_allocate_code_memory(&code_buffer, XNN_DEFAULT_CODE_BUFFER_SIZE)); |
Zhi An Ng | 60c9bcb | 2022-02-02 14:53:28 -0800 | [diff] [blame] | 2293 | ASSERT_EQ(xnn_status_success, igemm_generator(&code_buffer,n(), k(), ks() * mr() * sizeof(void*), nullptr)); |
Zhi An Ng | 0ec25cf | 2022-01-19 11:38:55 -0800 | [diff] [blame] | 2294 | xnn_qs8_igemm_minmax_ukernel_function igemm = reinterpret_cast<xnn_qs8_igemm_minmax_ukernel_function>(code_buffer.code); |
| 2295 | |
| 2296 | igemm( |
| 2297 | m(), n(), k(), ks() * mr() * sizeof(void*), |
| 2298 | im2col.data(), packed_w.data(), |
| 2299 | c.data(), cm_stride() * sizeof(int8_t), cn_stride() * sizeof(int8_t), |
| 2300 | a_offset() * sizeof(uint8_t), zero_pointer, |
| 2301 | &quantization_params); |
| 2302 | |
| 2303 | ASSERT_EQ(xnn_status_success, xnn_release_code_memory(&code_buffer)); |
| 2304 | |
| 2305 | for (size_t m_index = 0; m_index < m(); m_index++) { |
| 2306 | for (size_t n_index = 0; n_index < n(); n_index++) { |
| 2307 | c_ref[m_index * n() + n_index] = requantize( |
| 2308 | acc[m_index * n() + n_index], requantization_scale, c_zero_point, int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); |
| 2309 | } |
| 2310 | } |
| 2311 | |
| 2312 | for (size_t i = 0; i < m(); i++) { |
| 2313 | for (size_t j = 0; j < n(); j++) { |
| 2314 | ASSERT_LE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmax()) - 0x80); |
| 2315 | ASSERT_GE(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(qmin()) - 0x80); |
| 2316 | ASSERT_EQ(int32_t(c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()]), int32_t(c_ref[i * n() + j])) |
| 2317 | << "at " << i << ", " << j << ": reference = " << uint32_t(c_ref[i * n() + j]) |
| 2318 | << " (accumulator = " << acc[i * n() + j] |
| 2319 | << "), optimized = " << (uint32_t) c[i * cm_stride() + (j / nr()) * cn_stride() + j % nr()] << ", Mr x Nr x Kr = " << mr() << " x " |
| 2320 | << nr() << " x " << kr() << ", M x N x K = " << m() << " x " << n() << " x " << k() |
| 2321 | << ", requantization scale = " << requantization_scale << ", output zero point = " << int32_t(c_zero_point); |
| 2322 | } |
| 2323 | } |
| 2324 | } |
| 2325 | } |
| 2326 | |
| 2327 | #endif // XNN_PLATFORM_JIT |