XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 1 | // Copyright 2019 Google LLC |
| 2 | // |
| 3 | // This source code is licensed under the BSD-style license found in the |
| 4 | // LICENSE file in the root directory of this source tree. |
| 5 | |
| 6 | #pragma once |
| 7 | |
| 8 | #include <gtest/gtest.h> |
| 9 | |
| 10 | #include <algorithm> |
| 11 | #include <cassert> |
| 12 | #include <cmath> |
| 13 | #include <cstddef> |
| 14 | #include <cstdlib> |
| 15 | #include <functional> |
| 16 | #include <random> |
| 17 | #include <vector> |
| 18 | |
Frank Barchard | 9c1a735 | 2020-06-04 20:15:01 -0700 | [diff] [blame] | 19 | #include <fp16.h> |
| 20 | |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 21 | #include <xnnpack.h> |
| 22 | #include <xnnpack/AlignedAllocator.h> |
Marat Dukhan | eeaa7bd | 2019-10-25 17:31:25 -0700 | [diff] [blame] | 23 | #include <xnnpack/params-init.h> |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 24 | #include <xnnpack/params.h> |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 25 | |
| 26 | |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 27 | static inline bool is_fp16_zero(uint16_t x) { |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 28 | const uint16_t two_x = x + x; |
| 29 | return two_x == 0; |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 30 | } |
| 31 | |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 32 | class SpMMMicrokernelTester { |
| 33 | public: |
| 34 | enum class Variant { |
| 35 | Native, |
| 36 | Scalar, |
| 37 | }; |
| 38 | |
| 39 | inline SpMMMicrokernelTester& mr(size_t mr) { |
| 40 | this->mr_ = mr; |
| 41 | return *this; |
| 42 | } |
| 43 | |
| 44 | inline size_t mr() const { |
| 45 | return this->mr_; |
| 46 | } |
| 47 | |
| 48 | inline SpMMMicrokernelTester& nr(size_t nr) { |
| 49 | this->nr_ = nr; |
| 50 | return *this; |
| 51 | } |
| 52 | |
| 53 | inline size_t nr() const { |
| 54 | return this->nr_; |
| 55 | } |
| 56 | |
| 57 | inline SpMMMicrokernelTester& m(size_t m) { |
| 58 | this->m_ = m; |
| 59 | return *this; |
| 60 | } |
| 61 | |
| 62 | inline size_t m() const { |
| 63 | return this->m_; |
| 64 | } |
| 65 | |
| 66 | inline SpMMMicrokernelTester& n(size_t n) { |
| 67 | this->n_ = n; |
| 68 | return *this; |
| 69 | } |
| 70 | |
| 71 | inline size_t n() const { |
| 72 | return this->n_; |
| 73 | } |
| 74 | |
| 75 | inline SpMMMicrokernelTester& k(size_t k) { |
| 76 | this->k_ = k; |
| 77 | return *this; |
| 78 | } |
| 79 | |
| 80 | inline size_t k() const { |
| 81 | return this->k_; |
| 82 | } |
| 83 | |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 84 | inline SpMMMicrokernelTester& output_stride(size_t output_stride) { |
| 85 | assert(output_stride != 0); |
| 86 | this->output_stride_ = output_stride; |
| 87 | return *this; |
| 88 | } |
| 89 | |
| 90 | inline size_t output_stride() const { |
| 91 | if (this->output_stride_ == 0) { |
| 92 | return m(); |
| 93 | } else { |
| 94 | assert(this->output_stride_ >= m()); |
| 95 | return this->output_stride_; |
| 96 | } |
| 97 | } |
| 98 | |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 99 | inline SpMMMicrokernelTester& sparsity(float sparsity) { |
| 100 | this->sparsity_ = sparsity; |
| 101 | return *this; |
| 102 | } |
| 103 | |
| 104 | inline float sparsity() const { |
| 105 | return this->sparsity_; |
| 106 | } |
| 107 | |
| 108 | inline SpMMMicrokernelTester& qmin(uint8_t qmin) { |
| 109 | this->qmin_ = qmin; |
| 110 | return *this; |
| 111 | } |
| 112 | |
| 113 | inline uint8_t qmin() const { |
| 114 | return this->qmin_; |
| 115 | } |
| 116 | |
| 117 | inline SpMMMicrokernelTester& qmax(uint8_t qmax) { |
| 118 | this->qmax_ = qmax; |
| 119 | return *this; |
| 120 | } |
| 121 | |
| 122 | inline uint8_t qmax() const { |
| 123 | return this->qmax_; |
| 124 | } |
| 125 | |
| 126 | inline SpMMMicrokernelTester& iterations(size_t iterations) { |
| 127 | this->iterations_ = iterations; |
| 128 | return *this; |
| 129 | } |
| 130 | |
| 131 | inline size_t iterations() const { |
| 132 | return this->iterations_; |
| 133 | } |
| 134 | |
Marat Dukhan | 355ab43 | 2020-04-09 19:01:52 -0700 | [diff] [blame] | 135 | void Test(xnn_f32_spmm_minmax_ukernel_function spmm, Variant variant = Variant::Native) const { |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 136 | ASSERT_GE(m(), 1); |
| 137 | ASSERT_GE(n(), 1); |
| 138 | ASSERT_GE(k(), 1); |
| 139 | |
| 140 | std::random_device random_device; |
| 141 | auto rng = std::mt19937(random_device()); |
| 142 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), rng); |
| 143 | auto prng = std::bind(std::uniform_real_distribution<float>(), rng); |
| 144 | |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 145 | std::vector<float, AlignedAllocator<float, 64>> input(k() * m()); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 146 | // Think of b as (n/nr + n % nr) x k, expansion happens later. |
| 147 | const size_t ncols = n() / nr() + n() % nr(); |
| 148 | std::vector<float> b(ncols * k()); |
| 149 | std::vector<float> bias(n()); |
| 150 | // Number of non-zero weights per N (output channel). |
| 151 | std::vector<uint32_t> nmap(n()); |
| 152 | // Mapping from index of non-zero weight to increment of K (input channel) following this index. |
| 153 | std::vector<int32_t> dmap(n() * k()); |
| 154 | std::vector<float> w(n() * k() + n()); |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 155 | std::vector<float> output((n() - 1) * output_stride() + m()); |
| 156 | std::vector<float> output_ref(n() * m()); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 157 | |
| 158 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 159 | std::generate(input.begin(), input.end(), std::ref(f32rng)); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 160 | std::generate(b.begin(), b.end(), std::ref(f32rng)); |
| 161 | std::generate(bias.begin(), bias.end(), std::ref(f32rng)); |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 162 | std::fill(output.begin(), output.end(), nanf("")); |
| 163 | std::fill(output_ref.begin(), output_ref.end(), 0.0f); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 164 | std::fill(nmap.begin(), nmap.end(), 0); |
| 165 | std::fill(dmap.begin(), dmap.end(), 0); |
| 166 | std::fill(w.begin(), w.end(), 0.0f); |
| 167 | |
| 168 | for (float& b_value : b) { |
| 169 | if (prng() <= sparsity()) { |
| 170 | b_value = 0.0f; |
| 171 | } |
| 172 | } |
| 173 | |
| 174 | uint32_t nnz = 0; |
| 175 | uint32_t wcnt = 0; |
| 176 | size_t last_kk = 0; |
| 177 | bool first_nzz = true; |
| 178 | size_t first_kk = 0; |
| 179 | for (size_t nn = 0; nn < n() / nr(); nn++) { |
| 180 | for (size_t i = 0; i < nr(); ++i) |
| 181 | w[wcnt++] = bias[nr() * nn + i]; |
| 182 | for (size_t kk = 0; kk < k(); kk++) { |
| 183 | if (b[nn * k() + kk] != 0.0f) { |
| 184 | // Every non-zero actually corresponds to nr adjacent non-zeros. |
| 185 | for (size_t i = 0; i < nr(); ++i) |
| 186 | w[wcnt++] = b[nn * k() + kk] + static_cast<float>(i); |
| 187 | // Skip the very first non-zero weight as we record only the difference. |
| 188 | if (first_nzz) { |
| 189 | first_kk = kk; |
| 190 | } else { |
| 191 | const int32_t increment = int32_t(kk - last_kk) * int32_t(m() * sizeof(float)); |
| 192 | dmap[nnz++] = increment; |
| 193 | } |
| 194 | last_kk = kk; |
| 195 | first_nzz = false; |
| 196 | nmap[nn] += 1; |
| 197 | } |
| 198 | } |
| 199 | } |
| 200 | |
| 201 | // now we've constructed the matrix for the blocked part and switch to the |
| 202 | // leftovers, which we do as nr=1 always. |
| 203 | for (size_t nn = n() / nr(); nn < ncols; nn++) { |
| 204 | w[wcnt++] = bias[(n() / nr()) * nr() + (nn - n() / nr())]; |
| 205 | for (size_t kk = 0; kk < k(); kk++) { |
| 206 | if (b[nn * k() + kk] != 0.0f) { |
| 207 | // Every non-zero actually corresponds to nr adjacent non-zeros. |
| 208 | w[wcnt++] = b[nn * k() + kk]; |
| 209 | // Skip the very first non-zero weight as we record only the difference. |
| 210 | if (first_nzz) { |
| 211 | first_kk = kk; |
| 212 | } else { |
| 213 | const int32_t increment = int32_t(kk - last_kk) * int32_t(m() * sizeof(float)); |
| 214 | dmap[nnz++] = increment; |
| 215 | } |
| 216 | last_kk = kk; |
| 217 | first_nzz = false; |
| 218 | nmap[nn] += 1; |
| 219 | } |
| 220 | } |
| 221 | } |
| 222 | // In the end, we must return input pointer to the initial value. |
| 223 | const int64_t increment = int32_t(first_kk - last_kk) * int32_t(m() * sizeof(float)); |
| 224 | dmap[nnz++] = increment; |
| 225 | |
| 226 | // Generate expanded b which will be used in reference calculation. |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 227 | // Everywhere there is input non-zero in the original we copy it and add an |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 228 | // adjacent non-zero with incremented weight value. |
| 229 | std::vector<float> b_full(n() * k()); |
| 230 | if (nr() == 1) { |
| 231 | b_full = b; |
| 232 | } |
| 233 | else { |
| 234 | for (size_t nn = 0; nn < n() / nr(); nn++) { |
| 235 | for (size_t kk = 0; kk < k(); kk++) { |
| 236 | if (b[nn * k() + kk] != 0.0f) { |
| 237 | for (size_t i = 0; i < nr(); ++i) |
| 238 | b_full[nr() * nn * k() + i * k() + kk] = b[nn * k() + kk] + static_cast<float>(i); |
| 239 | } |
| 240 | } |
| 241 | } |
| 242 | for (size_t nn = n() / nr(); nn < ncols; nn++) { |
| 243 | for (size_t kk = 0; kk < k(); kk++) { |
| 244 | if (b[nn * k() + kk] != 0.0f) { |
| 245 | b_full[nr() * (n() / nr()) * k() + (nn - n() / nr()) * k() + kk] = b[nn * k() + kk]; |
| 246 | } |
| 247 | } |
| 248 | } |
| 249 | } |
| 250 | |
| 251 | for (size_t oc = 0; oc < n(); oc++) { |
| 252 | for (size_t pxb = 0; pxb < m(); pxb++) { |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 253 | output_ref[oc * m() + pxb] = bias[oc]; |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 254 | for (size_t ic = 0; ic < k(); ic++) { |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 255 | output_ref[oc * m() + pxb] += input[ic * m() + pxb] * b_full[oc * k() + ic]; |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 256 | } |
| 257 | } |
| 258 | } |
| 259 | |
| 260 | // Micro-kernel can access one element beyond w and dmap for software pipelining. |
| 261 | w.resize(wcnt + 1); |
| 262 | dmap.resize(nnz + 1); |
| 263 | |
| 264 | // Compute clamping parameters. |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 265 | const float accumulated_min = *std::min_element(output_ref.cbegin(), output_ref.cend()); |
| 266 | const float accumulated_max = *std::max_element(output_ref.cbegin(), output_ref.cend()); |
| 267 | const float output_min = accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()); |
| 268 | const float output_max = accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 269 | |
| 270 | // Clamp reference results. |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 271 | for (float& output_value : output_ref) { |
| 272 | output_value = std::min(std::max(output_value, output_min), output_max); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 273 | } |
| 274 | |
Frank Barchard | 9f3a843 | 2020-06-02 13:59:35 -0700 | [diff] [blame] | 275 | // Prepare parameters. |
Frank Barchard | 77acbf2 | 2020-05-01 10:08:26 -0700 | [diff] [blame] | 276 | xnn_f32_minmax_params params = { }; |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 277 | switch (variant) { |
| 278 | case Variant::Native: |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 279 | params = xnn_init_f32_minmax_params(output_min, output_max); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 280 | break; |
| 281 | case Variant::Scalar: |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 282 | params = xnn_init_scalar_f32_minmax_params(output_min, output_max); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 283 | break; |
| 284 | } |
| 285 | |
Marat Dukhan | e278a55 | 2020-11-14 16:14:58 -0800 | [diff] [blame] | 286 | spmm(m() * sizeof(float), n(), |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 287 | input.data() + first_kk * m(), |
| 288 | w.data(), dmap.data(), nmap.data(), |
| 289 | output.data(), output_stride() * sizeof(float), |
Frank Barchard | 77acbf2 | 2020-05-01 10:08:26 -0700 | [diff] [blame] | 290 | ¶ms); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 291 | |
Frank Barchard | e70dbeb | 2020-05-01 15:46:41 -0700 | [diff] [blame] | 292 | // Validate micro-kernel outputs. |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 293 | for (size_t i = 0; i < m(); i++) { |
| 294 | for (size_t j = 0; j < n(); j++) { |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 295 | ASSERT_NEAR( |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 296 | output[j * output_stride() + i], |
| 297 | output_ref[j * m() + i], |
| 298 | std::abs(output_ref[j * m() + i]) * 1.0e-6f) |
| 299 | << "at M index " << i << " / " << m() << " (tile " << mr() << ")" |
| 300 | << ", N index " << j << " / " << n() << " (tile " << nr() << ")" |
| 301 | << ", K = " << k(); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 302 | } |
| 303 | } |
| 304 | } |
| 305 | } |
| 306 | |
Marat Dukhan | 355ab43 | 2020-04-09 19:01:52 -0700 | [diff] [blame] | 307 | void Test(xnn_f16_spmm_minmax_ukernel_function spmm) const { |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 308 | ASSERT_GE(m(), 1); |
| 309 | ASSERT_GE(n(), 1); |
| 310 | ASSERT_GE(k(), 1); |
| 311 | |
| 312 | std::random_device random_device; |
| 313 | auto rng = std::mt19937(random_device()); |
| 314 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), rng); |
| 315 | auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng); |
| 316 | auto prng = std::bind(std::uniform_real_distribution<float>(), rng); |
| 317 | |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 318 | std::vector<uint16_t, AlignedAllocator<uint16_t, 64>> input(k() * m()); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 319 | // Think of b as (n/nr + n % nr) x k, expansion happens later. |
| 320 | const size_t ncols = n() / nr() + n() % nr(); |
| 321 | std::vector<uint16_t> b(ncols * k()); |
| 322 | std::vector<uint16_t> bias(n()); |
| 323 | // Number of non-zero weights per N (output channel). |
| 324 | std::vector<uint32_t> nmap(n()); |
| 325 | // Mapping from index of non-zero weight to increment of K (input channel) following this index. |
| 326 | std::vector<int32_t> dmap(n() * k()); |
| 327 | std::vector<uint16_t> w(n() * k() + n()); |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 328 | std::vector<uint16_t> output((n() - 1) * output_stride() + m()); |
| 329 | std::vector<float> output_ref(n() * m()); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 330 | |
| 331 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 332 | std::generate(input.begin(), input.end(), std::ref(f16rng)); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 333 | std::generate(b.begin(), b.end(), std::ref(f16rng)); |
| 334 | std::generate(bias.begin(), bias.end(), std::ref(f16rng)); |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 335 | std::fill(output.begin(), output.end(), 0xC000); |
| 336 | std::fill(output_ref.begin(), output_ref.end(), 0.0f); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 337 | std::fill(nmap.begin(), nmap.end(), 0); |
| 338 | std::fill(dmap.begin(), dmap.end(), 0); |
| 339 | std::fill(w.begin(), w.end(), 0); |
| 340 | |
| 341 | for (uint16_t& b_value : b) { |
| 342 | if (prng() <= sparsity()) { |
| 343 | b_value = 0; |
| 344 | } |
| 345 | } |
| 346 | |
| 347 | uint32_t nnz = 0; |
| 348 | uint32_t wcnt = 0; |
| 349 | size_t last_kk = 0; |
| 350 | bool first_nzz = true; |
| 351 | size_t first_kk = 0; |
| 352 | for (size_t nn = 0; nn < n() / nr(); nn++) { |
| 353 | for (size_t i = 0; i < nr(); ++i) |
| 354 | w[wcnt++] = bias[nr() * nn + i]; |
| 355 | for (size_t kk = 0; kk < k(); kk++) { |
| 356 | if (!is_fp16_zero(b[nn * k() + kk])) { |
| 357 | // Every non-zero actually corresponds to nr adjacent non-zeros. |
| 358 | for (size_t i = 0; i < nr(); ++i) |
| 359 | w[wcnt++] = fp16_ieee_from_fp32_value(fp16_ieee_to_fp32_value(b[nn * k() + kk]) + static_cast<float>(i)); |
| 360 | // Skip the very first non-zero weight as we record only the difference. |
| 361 | if (first_nzz) { |
| 362 | first_kk = kk; |
| 363 | } else { |
| 364 | const int32_t increment = int32_t(kk - last_kk) * int32_t(m() * sizeof(uint16_t)); |
| 365 | dmap[nnz++] = increment; |
| 366 | } |
| 367 | last_kk = kk; |
| 368 | first_nzz = false; |
| 369 | nmap[nn] += 1; |
| 370 | } |
| 371 | } |
| 372 | } |
| 373 | |
| 374 | // now we've constructed the matrix for the blocked part and switch to the |
| 375 | // leftovers, which we do as nr=1 always. |
| 376 | for (size_t nn = n() / nr(); nn < ncols; nn++) { |
| 377 | w[wcnt++] = bias[(n() / nr()) * nr() + (nn - n() / nr())]; |
| 378 | for (size_t kk = 0; kk < k(); kk++) { |
| 379 | if (!is_fp16_zero(b[nn * k() + kk])) { |
| 380 | // Every non-zero actually corresponds to nr adjacent non-zeros. |
| 381 | w[wcnt++] = b[nn * k() + kk]; |
| 382 | // Skip the very first non-zero weight as we record only the difference. |
| 383 | if (first_nzz) { |
| 384 | first_kk = kk; |
| 385 | } else { |
| 386 | const int32_t increment = int32_t(kk - last_kk) * int32_t(m() * sizeof(uint16_t)); |
| 387 | dmap[nnz++] = increment; |
| 388 | } |
| 389 | last_kk = kk; |
| 390 | first_nzz = false; |
| 391 | nmap[nn] += 1; |
| 392 | } |
| 393 | } |
| 394 | } |
| 395 | // In the end, we must return input pointer to the initial value. |
| 396 | const int64_t increment = int32_t(first_kk - last_kk) * int32_t(m() * sizeof(uint16_t)); |
| 397 | dmap[nnz++] = increment; |
| 398 | |
| 399 | // Generate expanded b which will be used in reference calculation. |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 400 | // Everywhere there is input non-zero in the original we copy it and add an |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 401 | // adjacent non-zero with incremented weight value. |
| 402 | std::vector<uint16_t> b_full(n() * k()); |
| 403 | if (nr() == 1) { |
| 404 | b_full = b; |
| 405 | } |
| 406 | else { |
| 407 | for (size_t nn = 0; nn < n() / nr(); nn++) { |
| 408 | for (size_t kk = 0; kk < k(); kk++) { |
| 409 | if (b[nn * k() + kk] != 0.0f) { |
| 410 | for (size_t i = 0; i < nr(); ++i) |
| 411 | b_full[nr() * nn * k() + i * k() + kk] = fp16_ieee_from_fp32_value( |
| 412 | fp16_ieee_to_fp32_value(b[nn * k() + kk]) + static_cast<float>(i)); |
| 413 | } |
| 414 | } |
| 415 | } |
| 416 | for (size_t nn = n() / nr(); nn < ncols; nn++) { |
| 417 | for (size_t kk = 0; kk < k(); kk++) { |
| 418 | if (b[nn * k() + kk] != 0.0f) { |
| 419 | b_full[nr() * (n() / nr()) * k() + (nn - n() / nr()) * k() + kk] = b[nn * k() + kk]; |
| 420 | } |
| 421 | } |
| 422 | } |
| 423 | } |
| 424 | |
| 425 | for (size_t oc = 0; oc < n(); oc++) { |
| 426 | for (size_t pxb = 0; pxb < m(); pxb++) { |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 427 | output_ref[oc * m() + pxb] = fp16_ieee_to_fp32_value(bias[oc]); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 428 | for (size_t ic = 0; ic < k(); ic++) { |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 429 | output_ref[oc * m() + pxb] += fp16_ieee_to_fp32_value(input[ic * m() + pxb]) * fp16_ieee_to_fp32_value(b_full[oc * k() + ic]); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 430 | } |
| 431 | } |
| 432 | } |
| 433 | |
| 434 | // Micro-kernel can access one element beyond w and dmap for software pipelining. |
| 435 | w.resize(wcnt + 1); |
| 436 | dmap.resize(nnz + 1); |
| 437 | |
| 438 | // Compute clamping parameters. |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 439 | const float accumulated_min = *std::min_element(output_ref.cbegin(), output_ref.cend()); |
| 440 | const float accumulated_max = *std::max_element(output_ref.cbegin(), output_ref.cend()); |
| 441 | const float output_min = accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin()); |
| 442 | const float output_max = accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax()); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 443 | |
| 444 | // Clamp reference results. |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 445 | for (float& output_value : output_ref) { |
| 446 | output_value = std::min(std::max(output_value, output_min), output_max); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 447 | } |
| 448 | |
Frank Barchard | 9f3a843 | 2020-06-02 13:59:35 -0700 | [diff] [blame] | 449 | // Prepare parameters. |
Frank Barchard | 77acbf2 | 2020-05-01 10:08:26 -0700 | [diff] [blame] | 450 | xnn_f16_scaleminmax_params params; |
| 451 | params.scale = UINT16_C(0x3C00) /* 1.0 */; |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 452 | params.max = fp16_ieee_from_fp32_value(output_max); |
| 453 | params.min = fp16_ieee_from_fp32_value(output_min); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 454 | |
Marat Dukhan | e278a55 | 2020-11-14 16:14:58 -0800 | [diff] [blame] | 455 | spmm(m() * sizeof(uint16_t), n(), |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 456 | input.data() + first_kk * m(), |
| 457 | w.data(), dmap.data(), nmap.data(), |
| 458 | output.data(), output_stride() * sizeof(uint16_t), |
Frank Barchard | 77acbf2 | 2020-05-01 10:08:26 -0700 | [diff] [blame] | 459 | ¶ms); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 460 | |
| 461 | // Validate micro-kernel outputs. |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 462 | for (size_t i = 0; i < m(); i++) { |
| 463 | for (size_t j = 0; j < n(); j++) { |
| 464 | ASSERT_NEAR( |
| 465 | fp16_ieee_to_fp32_value(output[j * output_stride() + i]), |
| 466 | output_ref[j * m() + i], |
| 467 | std::max(1.0e-4f, std::abs(output_ref[j * m() + i]) * 1.0e-2f)) |
| 468 | << "at M index " << i << " / " << m() << " (tile " << mr() << ")" |
| 469 | << ", N index " << j << " / " << n() << " (tile " << nr() << ")" |
| 470 | << ", K = " << k(); |
Marat Dukhan | bdb56f5 | 2020-02-05 21:42:49 -0800 | [diff] [blame] | 471 | } |
| 472 | } |
| 473 | } |
| 474 | } |
| 475 | |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 476 | private: |
| 477 | size_t mr_{1}; |
| 478 | size_t nr_{1}; |
| 479 | size_t m_{1}; |
| 480 | size_t n_{1}; |
| 481 | size_t k_{1}; |
Marat Dukhan | e8bfcc8 | 2020-11-16 12:28:13 -0800 | [diff] [blame] | 482 | size_t output_stride_{0}; |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 483 | float sparsity_{0.5f}; |
| 484 | uint8_t qmin_{0}; |
| 485 | uint8_t qmax_{255}; |
| 486 | size_t iterations_{1}; |
| 487 | }; |