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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 <limits>
17 #include <random>
18 #include <vector>
19 
20 #include <xnnpack/AlignedAllocator.h>
21 #include <xnnpack/pack.h>
22 #include <xnnpack/params-init.h>
23 #include <xnnpack/params.h>
24 #include <xnnpack.h>
25 
26 
27 class ConvHWC2CHWMicrokernelTester {
28 public:
29   enum class Variant {
30     Native,
31     Scalar,
32   };
33 
output_channels_tile(uint32_t output_channels_tile)34   inline ConvHWC2CHWMicrokernelTester& output_channels_tile(uint32_t output_channels_tile) {
35     this->output_channels_tile_ = output_channels_tile;
36     return *this;
37   }
38 
output_channels_tile()39   inline uint32_t output_channels_tile() const {
40     return this->output_channels_tile_;
41   }
42 
padding(uint32_t padding)43   inline ConvHWC2CHWMicrokernelTester& padding(uint32_t padding) {
44     this->padding_top_ = padding;
45     this->padding_right_ = padding;
46     this->padding_bottom_ = padding;
47     this->padding_left_ = padding;
48     return *this;
49   }
50 
padding_height(uint32_t padding_height)51   inline ConvHWC2CHWMicrokernelTester& padding_height(uint32_t padding_height) {
52     this->padding_top_ = padding_height;
53     this->padding_bottom_ = padding_height;
54     return *this;
55   }
56 
padding_width(uint32_t padding_width)57   inline ConvHWC2CHWMicrokernelTester& padding_width(uint32_t padding_width) {
58     this->padding_right_ = padding_width;
59     this->padding_left_ = padding_width;
60     return *this;
61   }
62 
padding_top(uint32_t padding_top)63   inline ConvHWC2CHWMicrokernelTester& padding_top(uint32_t padding_top) {
64     this->padding_top_ = padding_top;
65     return *this;
66   }
67 
padding_top()68   inline uint32_t padding_top() const {
69     return this->padding_top_;
70   }
71 
padding_right(uint32_t padding_right)72   inline ConvHWC2CHWMicrokernelTester& padding_right(uint32_t padding_right) {
73     this->padding_right_ = padding_right;
74     return *this;
75   }
76 
padding_right()77   inline uint32_t padding_right() const {
78     return this->padding_right_;
79   }
80 
padding_bottom(uint32_t padding_bottom)81   inline ConvHWC2CHWMicrokernelTester& padding_bottom(uint32_t padding_bottom) {
82     this->padding_bottom_ = padding_bottom;
83     return *this;
84   }
85 
padding_bottom()86   inline uint32_t padding_bottom() const {
87     return this->padding_bottom_;
88   }
89 
padding_left(uint32_t padding_left)90   inline ConvHWC2CHWMicrokernelTester& padding_left(uint32_t padding_left) {
91     this->padding_left_ = padding_left;
92     return *this;
93   }
94 
padding_left()95   inline uint32_t padding_left() const {
96     return this->padding_left_;
97   }
98 
input_size(uint32_t input_height,uint32_t input_width)99   inline ConvHWC2CHWMicrokernelTester& input_size(uint32_t input_height, uint32_t input_width) {
100     assert(input_height >= 1);
101     assert(input_width >= 1);
102     this->input_height_ = input_height;
103     this->input_width_ = input_width;
104     return *this;
105   }
106 
input_height(uint32_t input_height)107   inline ConvHWC2CHWMicrokernelTester& input_height(uint32_t input_height) {
108     assert(input_height >= 1);
109     this->input_height_ = input_height;
110     return *this;
111   }
112 
input_height()113   inline uint32_t input_height() const {
114     return this->input_height_;
115   }
116 
input_width(uint32_t input_width)117   inline ConvHWC2CHWMicrokernelTester& input_width(uint32_t input_width) {
118     assert(input_width >= 1);
119     this->input_width_ = input_width;
120     return *this;
121   }
122 
input_width()123   inline uint32_t input_width() const {
124     return this->input_width_;
125   }
126 
input_channels(size_t input_channels)127   inline ConvHWC2CHWMicrokernelTester& input_channels(size_t input_channels) {
128     assert(input_channels >= 1);
129     this->input_channels_ = input_channels;
130     return *this;
131   }
132 
input_channels()133   inline size_t input_channels() const {
134     return this->input_channels_;
135   }
136 
output_channels(size_t output_channels)137   inline ConvHWC2CHWMicrokernelTester& output_channels(size_t output_channels) {
138     assert(output_channels >= 1);
139     this->output_channels_ = output_channels;
140     return *this;
141   }
142 
output_channels()143   inline size_t output_channels() const {
144     return this->output_channels_;
145   }
146 
packed_output_channels()147   inline size_t packed_output_channels() const {
148     return output_channels() % output_channels_tile() == 0 ? output_channels() : output_channels() / output_channels_tile() * output_channels_tile() + output_channels_tile();
149   }
150 
batch_size(size_t batch_size)151   inline ConvHWC2CHWMicrokernelTester& batch_size(size_t batch_size) {
152     assert(batch_size >= 1);
153     this->batch_size_ = batch_size;
154     return *this;
155   }
156 
batch_size()157   inline size_t batch_size() const {
158     return this->batch_size_;
159   }
160 
kernel_size(uint32_t kernel_size)161   inline ConvHWC2CHWMicrokernelTester& kernel_size(uint32_t kernel_size) {
162     assert(kernel_size >= 1);
163     this->kernel_height_ = kernel_size;
164     this->kernel_width_ = kernel_size;
165     return *this;
166   }
167 
kernel_height(uint32_t kernel_height)168   inline ConvHWC2CHWMicrokernelTester& kernel_height(uint32_t kernel_height) {
169     assert(kernel_height >= 1);
170     this->kernel_height_ = kernel_height;
171     return *this;
172   }
173 
kernel_height()174   inline uint32_t kernel_height() const {
175     return this->kernel_height_;
176   }
177 
kernel_width(uint32_t kernel_width)178   inline ConvHWC2CHWMicrokernelTester& kernel_width(uint32_t kernel_width) {
179     assert(kernel_width >= 1);
180     this->kernel_width_ = kernel_width;
181     return *this;
182   }
183 
kernel_width()184   inline uint32_t kernel_width() const {
185     return this->kernel_width_;
186   }
187 
subsampling(uint32_t subsampling)188   inline ConvHWC2CHWMicrokernelTester& subsampling(uint32_t subsampling) {
189     assert(subsampling >= 1);
190     this->subsampling_height_ = subsampling;
191     this->subsampling_width_ = subsampling;
192     return *this;
193   }
194 
subsampling_height(uint32_t subsampling_height)195   inline ConvHWC2CHWMicrokernelTester& subsampling_height(uint32_t subsampling_height) {
196     assert(subsampling_height >= 1);
197     this->subsampling_height_ = subsampling_height;
198     return *this;
199   }
200 
subsampling_height()201   inline uint32_t subsampling_height() const {
202     return this->subsampling_height_;
203   }
204 
subsampling_width(uint32_t subsampling_width)205   inline ConvHWC2CHWMicrokernelTester& subsampling_width(uint32_t subsampling_width) {
206     assert(subsampling_width >= 1);
207     this->subsampling_width_ = subsampling_width;
208     return *this;
209   }
210 
subsampling_width()211   inline uint32_t subsampling_width() const {
212     return this->subsampling_width_;
213   }
214 
output_y_start(uint32_t output_y_start)215   inline ConvHWC2CHWMicrokernelTester& output_y_start(uint32_t output_y_start) {
216     this->output_y_start_ = output_y_start;
217     return *this;
218   }
219 
output_y_start()220   inline uint32_t output_y_start() const {
221     return this->output_y_start_;
222   }
223 
output_y_end(uint32_t output_y_end)224   inline ConvHWC2CHWMicrokernelTester& output_y_end(uint32_t output_y_end) {
225     this->output_y_end_ = output_y_end;
226     return *this;
227   }
228 
output_y_end()229   inline uint32_t output_y_end() const {
230     if (this->output_y_end_ == std::numeric_limits<uint32_t>::max()) {
231       return output_height();
232     } else {
233       return this->output_y_end_;
234     }
235   }
236 
input_pixel_stride()237   inline size_t input_pixel_stride() const {
238     return input_channels();
239   }
240 
output_pixel_stride()241   inline size_t output_pixel_stride() const {
242     return output_channels();
243   }
244 
output_height()245   inline size_t output_height() const {
246     const size_t padded_input_height = padding_top() + input_height() + padding_bottom();
247     if (padded_input_height < kernel_height()) {
248       return 0;
249     } else {
250       return (padded_input_height - kernel_height()) / subsampling_height() + 1;
251     }
252   }
253 
output_width()254   inline size_t output_width() const {
255     const size_t padded_input_width = padding_left() + input_width() + padding_right();
256     if (padded_input_width < kernel_width()) {
257       return 0;
258     } else {
259       return (padded_input_width - kernel_width()) / subsampling_width() + 1;
260     }
261   }
262 
qmin(uint8_t qmin)263   inline ConvHWC2CHWMicrokernelTester& qmin(uint8_t qmin) {
264     this->qmin_ = qmin;
265     return *this;
266   }
267 
qmin()268   inline uint8_t qmin() const {
269     return this->qmin_;
270   }
271 
qmax(uint8_t qmax)272   inline ConvHWC2CHWMicrokernelTester& qmax(uint8_t qmax) {
273     this->qmax_ = qmax;
274     return *this;
275   }
276 
qmax()277   inline uint8_t qmax() const {
278     return this->qmax_;
279   }
280 
iterations(size_t iterations)281   inline ConvHWC2CHWMicrokernelTester& iterations(size_t iterations) {
282     this->iterations_ = iterations;
283     return *this;
284   }
285 
iterations()286   inline size_t iterations() const {
287     return this->iterations_;
288   }
289 
290   void Test(xnn_f32_conv_hwc2chw_ukernel_function conv, Variant variant = Variant::Native) const {
291     ASSERT_LT(output_y_start(), output_height());
292     ASSERT_LE(output_y_end(), output_height());
293     ASSERT_GT(output_y_end(), output_y_start());
294     ASSERT_GE(output_width(), 1);
295     ASSERT_GE(output_height(), 1);
296 
297     std::random_device random_device;
298     auto rng = std::mt19937(random_device());
299     auto f32rng = std::bind(std::uniform_real_distribution<float>(0.1f, 1.0f), rng);
300 
301     std::vector<float> input(XNN_EXTRA_BYTES / sizeof(float) +
302       batch_size() * ((input_height() * input_width() - 1) * input_pixel_stride() + input_channels()));
303     std::vector<float> zero(XNN_EXTRA_BYTES / sizeof(float) + input_width() * input_channels());
304     std::vector<float> kernel(output_channels() * kernel_height() * kernel_width() * input_channels());
305     std::vector<float> bias(output_channels());
306     std::vector<float> output(batch_size() * output_channels() * output_height() * output_width());
307     std::vector<float> output_ref(batch_size() * output_channels() * output_height() * output_width());
308     std::vector<float, AlignedAllocator<float, 64>> packed_weights((input_channels() * kernel_height() * kernel_width() + 1) * packed_output_channels());
309 
310     for (size_t iteration = 0; iteration < iterations(); iteration++) {
311       std::generate(input.begin(), input.end(), std::ref(f32rng));
312       std::generate(kernel.begin(), kernel.end(), std::ref(f32rng));
313       std::generate(bias.begin(), bias.end(), std::ref(f32rng));
314       std::fill(output.begin(), output.end(), nanf(""));
315       std::fill(packed_weights.begin(), packed_weights.end(), 0.0f);
316 
317       xnn_pack_f32_dconv_oki_w(
318         output_channels(),
319         input_channels(),
320         output_channels_tile(),
321         kernel_height(), kernel_width(),
322         kernel.data(), bias.data(), packed_weights.data(), nullptr);
323 
324       // Compute reference results, without clamping.
325       for (size_t i = 0; i < batch_size(); i++) {
326         for (size_t oy = 0; oy < output_height(); oy++) {
327           for (size_t ox = 0; ox < output_width(); ox++) {
328             for (size_t oc = 0; oc < output_channels(); oc++) {
329               float acc = bias[oc];
330               for (size_t ky = 0; ky < kernel_height(); ky++) {
331                 const size_t iy = oy * subsampling_height() + ky - padding_top();
332                 if (iy < input_height()) {
333                   for (size_t kx = 0; kx < kernel_width(); kx++) {
334                     const size_t ix = ox * subsampling_width() + kx - padding_left();
335                     if (ix < input_width()) {
336                       for (size_t ic = 0; ic < input_channels(); ic++) {
337                         acc +=
338                           input[((i * input_height() + iy) * input_width() + ix) * input_pixel_stride() + ic] *
339                           kernel[((oc * kernel_height() + ky) * kernel_width() + kx) * input_channels() + ic];
340                       }
341                     }
342                   }
343                 }
344               }
345               output_ref[((i * output_channels() + oc) * output_height() + oy) * output_width() + ox] = acc;
346             }
347           }
348         }
349       }
350 
351       // Compute clamping parameters.
352       const float accumulated_min = *std::min_element(output_ref.cbegin(), output_ref.cend());
353       const float accumulated_max = *std::max_element(output_ref.cbegin(), output_ref.cend());
354 
355       const float output_min = accumulated_min + (accumulated_max - accumulated_min) / 255.0f * float(qmin());
356       const float output_max = accumulated_max - (accumulated_max - accumulated_min) / 255.0f * float(255 - qmax());
357 
358       // Clamp reference results.
359       for (float& value : output_ref) {
360         value = std::max(std::min(value, output_max), output_min);
361       }
362 
363       // Prepare parameters.
364       xnn_f32_minmax_params params;
365       switch (variant) {
366         case Variant::Native:
367           xnn_init_f32_minmax_params(&params, output_min, output_max);
368           break;
369         case Variant::Scalar:
370           xnn_init_f32_minmax_scalar_params(&params, output_min, output_max);
371           break;
372       }
373 
374       // Call optimized micro-kernel.
375       conv(
376         input_height(), input_width(),
377         output_y_start(), output_y_end(),
378         input.data(), zero.data(), packed_weights.data(), output.data(),
379         padding_top(), output_channels(),
380         output_width() * sizeof(float),
381         output_height() * output_width() * sizeof(float),
382         &params);
383 
384       // Verify results.
385       for (size_t i = 0; i < batch_size(); i++) {
386         for (size_t y = output_y_start(); y < output_y_end(); y++) {
387           for (size_t x = 0; x < output_width(); x++) {
388             for (size_t c = 0; c < output_channels(); c++) {
389               ASSERT_GE(output[((i * output_channels() + c) * output_height() + y) * output_width() + x], output_min)
390                 << "(x, y) = (" << x << ", " << y << "), channel = " << c;
391               ASSERT_LE(output[((i * output_channels() + c) * output_height() + y) * output_width() + x], output_max)
392                 << "(x, y) = (" << x << ", " << y << "), channel = " << c;
393               ASSERT_NEAR(
394                   output_ref[((i * output_channels() + c) * output_height() + y) * output_width() + x],
395                   output[((i * output_channels() + c) * output_height() + y) * output_width() + x],
396                   1.0e-4 * std::abs(output_ref[((i * output_channels() + c) * output_height() + y) * output_width() + x]))
397                 << "(x, y) = (" << x << ", " << y << "), channel = " << c;
398             }
399           }
400         }
401       }
402     }
403   }
404 
405  private:
406   uint32_t padding_top_{0};
407   uint32_t padding_right_{0};
408   uint32_t padding_bottom_{0};
409   uint32_t padding_left_{0};
410   size_t input_height_{1};
411   size_t input_width_{1};
412   size_t input_channels_{1};
413   size_t output_channels_{1};
414   uint32_t output_channels_tile_{1};
415   size_t batch_size_{1};
416   uint32_t kernel_height_{1};
417   uint32_t kernel_width_{1};
418   uint32_t subsampling_height_{1};
419   uint32_t subsampling_width_{1};
420   uint32_t output_y_start_{0};
421   uint32_t output_y_end_{std::numeric_limits<uint32_t>::max()};
422   uint8_t qmin_{0};
423   uint8_t qmax_{255};
424   size_t iterations_{1};
425 };
426