xref: /aosp_15_r20/external/XNNPACK/models/fp16-mobilenet-v1.cc (revision 4bdc94577ba0e567308109d787f7fec7b531ce36) 
1 // Copyright 2020 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 #include <xnnpack.h>
7 
8 #include <array>
9 #include <algorithm>
10 #include <functional>
11 #include <iostream>
12 #include <limits>
13 #include <random>
14 
15 #include <xnnpack/cache.h>
16 
17 #include <fp16/fp16.h>
18 
19 #include "models/models.h"
20 
21 namespace models {
22 
FP16MobileNetV1(pthreadpool_t threadpool)23 ExecutionPlan FP16MobileNetV1(pthreadpool_t threadpool) {
24   alignas(16) static std::array<uint16_t, 150528 + XNN_EXTRA_BYTES / sizeof(uint16_t)> v0;
25   alignas(16) static std::array<uint16_t, 401408> v1;
26   alignas(16) static std::array<uint16_t, 401408> v2;
27   alignas(16) static std::array<uint16_t, 802816> v3;
28   alignas(16) static std::array<uint16_t, 200704> v4;
29   alignas(16) static std::array<uint16_t, 401408> v5;
30   alignas(16) static std::array<uint16_t, 401408> v6;
31   alignas(16) static std::array<uint16_t, 401408> v7;
32   alignas(16) static std::array<uint16_t, 100352> v8;
33   alignas(16) static std::array<uint16_t, 200704> v9;
34   alignas(16) static std::array<uint16_t, 200704> v10;
35   alignas(16) static std::array<uint16_t, 200704> v11;
36   alignas(16) static std::array<uint16_t, 50176> v12;
37   alignas(16) static std::array<uint16_t, 100352> v13;
38   alignas(16) static std::array<uint16_t, 100352> v14;
39   alignas(16) static std::array<uint16_t, 100352> v15;
40   alignas(16) static std::array<uint16_t, 100352> v16;
41   alignas(16) static std::array<uint16_t, 100352> v17;
42   alignas(16) static std::array<uint16_t, 100352> v18;
43   alignas(16) static std::array<uint16_t, 100352> v19;
44   alignas(16) static std::array<uint16_t, 100352> v20;
45   alignas(16) static std::array<uint16_t, 100352> v21;
46   alignas(16) static std::array<uint16_t, 100352> v22;
47   alignas(16) static std::array<uint16_t, 100352> v23;
48   alignas(16) static std::array<uint16_t, 25088> v24;
49   alignas(16) static std::array<uint16_t, 50176> v25;
50   alignas(16) static std::array<uint16_t, 50176> v26;
51   alignas(16) static std::array<uint16_t, 50176> v27;
52   alignas(16) static std::array<uint16_t, 1024> v28;
53   alignas(16) static std::array<uint16_t, 1001> v29;
54   alignas(16) static std::array<uint16_t, 864> w30;
55   alignas(16) static std::array<uint16_t, 32> w31;
56   alignas(16) static std::array<uint16_t, 288> w32;
57   alignas(16) static std::array<uint16_t, 32> w33;
58   alignas(16) static std::array<uint16_t, 2048> w34;
59   alignas(16) static std::array<uint16_t, 64> w35;
60   alignas(16) static std::array<uint16_t, 576> w36;
61   alignas(16) static std::array<uint16_t, 64> w37;
62   alignas(16) static std::array<uint16_t, 8192> w38;
63   alignas(16) static std::array<uint16_t, 128> w39;
64   alignas(16) static std::array<uint16_t, 1152> w40;
65   alignas(16) static std::array<uint16_t, 128> w41;
66   alignas(16) static std::array<uint16_t, 16384> w42;
67   alignas(16) static std::array<uint16_t, 128> w43;
68   alignas(16) static std::array<uint16_t, 1152> w44;
69   alignas(16) static std::array<uint16_t, 128> w45;
70   alignas(16) static std::array<uint16_t, 32768> w46;
71   alignas(16) static std::array<uint16_t, 256> w47;
72   alignas(16) static std::array<uint16_t, 2304> w48;
73   alignas(16) static std::array<uint16_t, 256> w49;
74   alignas(16) static std::array<uint16_t, 65536> w50;
75   alignas(16) static std::array<uint16_t, 256> w51;
76   alignas(16) static std::array<uint16_t, 2304> w52;
77   alignas(16) static std::array<uint16_t, 256> w53;
78   alignas(16) static std::array<uint16_t, 131072> w54;
79   alignas(16) static std::array<uint16_t, 512> w55;
80   alignas(16) static std::array<uint16_t, 4608> w56;
81   alignas(16) static std::array<uint16_t, 512> w57;
82   alignas(16) static std::array<uint16_t, 262144> w58;
83   alignas(16) static std::array<uint16_t, 512> w59;
84   alignas(16) static std::array<uint16_t, 4608> w60;
85   alignas(16) static std::array<uint16_t, 512> w61;
86   alignas(16) static std::array<uint16_t, 262144> w62;
87   alignas(16) static std::array<uint16_t, 512> w63;
88   alignas(16) static std::array<uint16_t, 4608> w64;
89   alignas(16) static std::array<uint16_t, 512> w65;
90   alignas(16) static std::array<uint16_t, 262144> w66;
91   alignas(16) static std::array<uint16_t, 512> w67;
92   alignas(16) static std::array<uint16_t, 4608> w68;
93   alignas(16) static std::array<uint16_t, 512> w69;
94   alignas(16) static std::array<uint16_t, 262144> w70;
95   alignas(16) static std::array<uint16_t, 512> w71;
96   alignas(16) static std::array<uint16_t, 4608> w72;
97   alignas(16) static std::array<uint16_t, 512> w73;
98   alignas(16) static std::array<uint16_t, 262144> w74;
99   alignas(16) static std::array<uint16_t, 512> w75;
100   alignas(16) static std::array<uint16_t, 4608> w76;
101   alignas(16) static std::array<uint16_t, 512> w77;
102   alignas(16) static std::array<uint16_t, 524288> w78;
103   alignas(16) static std::array<uint16_t, 1024> w79;
104   alignas(16) static std::array<uint16_t, 9216> w80;
105   alignas(16) static std::array<uint16_t, 1024> w81;
106   alignas(16) static std::array<uint16_t, 1048576> w82;
107   alignas(16) static std::array<uint16_t, 1024> w83;
108   alignas(16) static std::array<uint16_t, 1025024> w84;
109   alignas(16) static std::array<uint16_t, 1001> w85;
110 
111   std::random_device random_device;
112   auto rng = std::mt19937(random_device());
113   auto f32rng = std::bind(std::uniform_real_distribution<float>(-1.0f, +1.0f), std::ref(rng));
114   auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng);
115   std::generate(v0.begin(), v0.end(), std::ref(f16rng));
116   std::generate(v1.begin(), v1.end(), std::ref(f16rng));
117   std::generate(v2.begin(), v2.end(), std::ref(f16rng));
118   std::generate(v3.begin(), v3.end(), std::ref(f16rng));
119   std::generate(v4.begin(), v4.end(), std::ref(f16rng));
120   std::generate(v5.begin(), v5.end(), std::ref(f16rng));
121   std::generate(v6.begin(), v6.end(), std::ref(f16rng));
122   std::generate(v7.begin(), v7.end(), std::ref(f16rng));
123   std::generate(v8.begin(), v8.end(), std::ref(f16rng));
124   std::generate(v9.begin(), v9.end(), std::ref(f16rng));
125   std::generate(v10.begin(), v10.end(), std::ref(f16rng));
126   std::generate(v11.begin(), v11.end(), std::ref(f16rng));
127   std::generate(v12.begin(), v12.end(), std::ref(f16rng));
128   std::generate(v13.begin(), v13.end(), std::ref(f16rng));
129   std::generate(v14.begin(), v14.end(), std::ref(f16rng));
130   std::generate(v15.begin(), v15.end(), std::ref(f16rng));
131   std::generate(v16.begin(), v16.end(), std::ref(f16rng));
132   std::generate(v17.begin(), v17.end(), std::ref(f16rng));
133   std::generate(v18.begin(), v18.end(), std::ref(f16rng));
134   std::generate(v19.begin(), v19.end(), std::ref(f16rng));
135   std::generate(v20.begin(), v20.end(), std::ref(f16rng));
136   std::generate(v21.begin(), v21.end(), std::ref(f16rng));
137   std::generate(v22.begin(), v22.end(), std::ref(f16rng));
138   std::generate(v23.begin(), v23.end(), std::ref(f16rng));
139   std::generate(v24.begin(), v24.end(), std::ref(f16rng));
140   std::generate(v25.begin(), v25.end(), std::ref(f16rng));
141   std::generate(v26.begin(), v26.end(), std::ref(f16rng));
142   std::generate(v27.begin(), v27.end(), std::ref(f16rng));
143   std::generate(v28.begin(), v28.end(), std::ref(f16rng));
144   std::generate(v29.begin(), v29.end(), std::ref(f16rng));
145   std::generate(w30.begin(), w30.end(), std::ref(f16rng));
146   std::generate(w31.begin(), w31.end(), std::ref(f16rng));
147   std::generate(w32.begin(), w32.end(), std::ref(f16rng));
148   std::generate(w33.begin(), w33.end(), std::ref(f16rng));
149   std::generate(w34.begin(), w34.end(), std::ref(f16rng));
150   std::generate(w35.begin(), w35.end(), std::ref(f16rng));
151   std::generate(w36.begin(), w36.end(), std::ref(f16rng));
152   std::generate(w37.begin(), w37.end(), std::ref(f16rng));
153   std::generate(w38.begin(), w38.end(), std::ref(f16rng));
154   std::generate(w39.begin(), w39.end(), std::ref(f16rng));
155   std::generate(w40.begin(), w40.end(), std::ref(f16rng));
156   std::generate(w41.begin(), w41.end(), std::ref(f16rng));
157   std::generate(w42.begin(), w42.end(), std::ref(f16rng));
158   std::generate(w43.begin(), w43.end(), std::ref(f16rng));
159   std::generate(w44.begin(), w44.end(), std::ref(f16rng));
160   std::generate(w45.begin(), w45.end(), std::ref(f16rng));
161   std::generate(w46.begin(), w46.end(), std::ref(f16rng));
162   std::generate(w47.begin(), w47.end(), std::ref(f16rng));
163   std::generate(w48.begin(), w48.end(), std::ref(f16rng));
164   std::generate(w49.begin(), w49.end(), std::ref(f16rng));
165   std::generate(w50.begin(), w50.end(), std::ref(f16rng));
166   std::generate(w51.begin(), w51.end(), std::ref(f16rng));
167   std::generate(w52.begin(), w52.end(), std::ref(f16rng));
168   std::generate(w53.begin(), w53.end(), std::ref(f16rng));
169   std::generate(w54.begin(), w54.end(), std::ref(f16rng));
170   std::generate(w55.begin(), w55.end(), std::ref(f16rng));
171   std::generate(w56.begin(), w56.end(), std::ref(f16rng));
172   std::generate(w57.begin(), w57.end(), std::ref(f16rng));
173   std::generate(w58.begin(), w58.end(), std::ref(f16rng));
174   std::generate(w59.begin(), w59.end(), std::ref(f16rng));
175   std::generate(w60.begin(), w60.end(), std::ref(f16rng));
176   std::generate(w61.begin(), w61.end(), std::ref(f16rng));
177   std::generate(w62.begin(), w62.end(), std::ref(f16rng));
178   std::generate(w63.begin(), w63.end(), std::ref(f16rng));
179   std::generate(w64.begin(), w64.end(), std::ref(f16rng));
180   std::generate(w65.begin(), w65.end(), std::ref(f16rng));
181   std::generate(w66.begin(), w66.end(), std::ref(f16rng));
182   std::generate(w67.begin(), w67.end(), std::ref(f16rng));
183   std::generate(w68.begin(), w68.end(), std::ref(f16rng));
184   std::generate(w69.begin(), w69.end(), std::ref(f16rng));
185   std::generate(w70.begin(), w70.end(), std::ref(f16rng));
186   std::generate(w71.begin(), w71.end(), std::ref(f16rng));
187   std::generate(w72.begin(), w72.end(), std::ref(f16rng));
188   std::generate(w73.begin(), w73.end(), std::ref(f16rng));
189   std::generate(w74.begin(), w74.end(), std::ref(f16rng));
190   std::generate(w75.begin(), w75.end(), std::ref(f16rng));
191   std::generate(w76.begin(), w76.end(), std::ref(f16rng));
192   std::generate(w77.begin(), w77.end(), std::ref(f16rng));
193   std::generate(w78.begin(), w78.end(), std::ref(f16rng));
194   std::generate(w79.begin(), w79.end(), std::ref(f16rng));
195   std::generate(w80.begin(), w80.end(), std::ref(f16rng));
196   std::generate(w81.begin(), w81.end(), std::ref(f16rng));
197   std::generate(w82.begin(), w82.end(), std::ref(f16rng));
198   std::generate(w83.begin(), w83.end(), std::ref(f16rng));
199   std::generate(w84.begin(), w84.end(), std::ref(f16rng));
200   std::generate(w85.begin(), w85.end(), std::ref(f16rng));
201 
202   ExecutionPlan operators;
203   xnn_status status;
204   xnn_code_cache code_cache;
205 #if XNN_PLATFORM_JIT
206   xnn_init_code_cache(&code_cache);
207 #endif
208   xnn_caches caches = { 0 };
209   caches.code_cache = &code_cache;
210 
211   xnn_operator_t op0 = nullptr;
212   status = xnn_create_convolution2d_nhwc_f16(
213     0 /* top padding */, 1 /* right padding */,
214     1 /* bottom padding */, 0 /* left padding */,
215     3 /* kernel height */, 3 /* kernel width */,
216     2 /* subsampling height */, 2 /* subsampling width */,
217     1 /* dilation_height */, 1 /* dilation_width */,
218     1 /* groups */,
219     3 /* input channels per group */,
220     32 /* output_channels_per_group */,
221     3 /* input pixel stride */,
222     32 /* output pixel stride */,
223     w30.data(), w31.data(),
224     0.0f /* output min */, 6.0f /* output max */,
225     0 /* flags */,
226     &caches,
227     &op0);
228   if (status != xnn_status_success) {
229     std::cerr << "failed to create operation #0" << std::endl;
230     return ExecutionPlan();
231   }
232   operators.emplace_back(op0, xnn_delete_operator);
233 
234   xnn_operator_t op1 = nullptr;
235   status = xnn_create_convolution2d_nhwc_f16(
236     1 /* top padding */, 1 /* right padding */,
237     1 /* bottom padding */, 1 /* left padding */,
238     3 /* kernel height */, 3 /* kernel width */,
239     1 /* subsampling height */, 1 /* subsampling width */,
240     1 /* dilation_height */, 1 /* dilation_width */,
241     32 /* groups */,
242     1 /* input channels per group */,
243     1 /* output_channels_per_group */,
244     32 /* input pixel stride */,
245     32 /* output pixel stride */,
246     w32.data(), w33.data(),
247     0.0f /* output min */, 6.0f /* output max */,
248     0 /* flags */,
249     &caches,
250     &op1);
251   if (status != xnn_status_success) {
252     std::cerr << "failed to create operation #1" << std::endl;
253     return ExecutionPlan();
254   }
255   operators.emplace_back(op1, xnn_delete_operator);
256 
257   xnn_operator_t op2 = nullptr;
258   status = xnn_create_convolution2d_nhwc_f16(
259     0 /* top padding */, 0 /* right padding */,
260     0 /* bottom padding */, 0 /* left padding */,
261     1 /* kernel height */, 1 /* kernel width */,
262     1 /* subsampling height */, 1 /* subsampling width */,
263     1 /* dilation_height */, 1 /* dilation_width */,
264     1 /* groups */,
265     32 /* input channels per group */,
266     64 /* output_channels_per_group */,
267     32 /* input pixel stride */,
268     64 /* output pixel stride */,
269     w34.data(), w35.data(),
270     0.0f /* output min */, 6.0f /* output max */,
271     0 /* flags */,
272     &caches,
273     &op2);
274   if (status != xnn_status_success) {
275     std::cerr << "failed to create operation #2" << std::endl;
276     return ExecutionPlan();
277   }
278   operators.emplace_back(op2, xnn_delete_operator);
279 
280   xnn_operator_t op3 = nullptr;
281   status = xnn_create_convolution2d_nhwc_f16(
282     0 /* top padding */, 1 /* right padding */,
283     1 /* bottom padding */, 0 /* left padding */,
284     3 /* kernel height */, 3 /* kernel width */,
285     2 /* subsampling height */, 2 /* subsampling width */,
286     1 /* dilation_height */, 1 /* dilation_width */,
287     64 /* groups */,
288     1 /* input channels per group */,
289     1 /* output_channels_per_group */,
290     64 /* input pixel stride */,
291     64 /* output pixel stride */,
292     w36.data(), w37.data(),
293     0.0f /* output min */, 6.0f /* output max */,
294     0 /* flags */,
295     &caches,
296     &op3);
297   if (status != xnn_status_success) {
298     std::cerr << "failed to create operation #3" << std::endl;
299     return ExecutionPlan();
300   }
301   operators.emplace_back(op3, xnn_delete_operator);
302 
303   xnn_operator_t op4 = nullptr;
304   status = xnn_create_convolution2d_nhwc_f16(
305     0 /* top padding */, 0 /* right padding */,
306     0 /* bottom padding */, 0 /* left padding */,
307     1 /* kernel height */, 1 /* kernel width */,
308     1 /* subsampling height */, 1 /* subsampling width */,
309     1 /* dilation_height */, 1 /* dilation_width */,
310     1 /* groups */,
311     64 /* input channels per group */,
312     128 /* output_channels_per_group */,
313     64 /* input pixel stride */,
314     128 /* output pixel stride */,
315     w38.data(), w39.data(),
316     0.0f /* output min */, 6.0f /* output max */,
317     0 /* flags */,
318     &caches,
319     &op4);
320   if (status != xnn_status_success) {
321     std::cerr << "failed to create operation #4" << std::endl;
322     return ExecutionPlan();
323   }
324   operators.emplace_back(op4, xnn_delete_operator);
325 
326   xnn_operator_t op5 = nullptr;
327   status = xnn_create_convolution2d_nhwc_f16(
328     1 /* top padding */, 1 /* right padding */,
329     1 /* bottom padding */, 1 /* left padding */,
330     3 /* kernel height */, 3 /* kernel width */,
331     1 /* subsampling height */, 1 /* subsampling width */,
332     1 /* dilation_height */, 1 /* dilation_width */,
333     128 /* groups */,
334     1 /* input channels per group */,
335     1 /* output_channels_per_group */,
336     128 /* input pixel stride */,
337     128 /* output pixel stride */,
338     w40.data(), w41.data(),
339     0.0f /* output min */, 6.0f /* output max */,
340     0 /* flags */,
341     &caches,
342     &op5);
343   if (status != xnn_status_success) {
344     std::cerr << "failed to create operation #5" << std::endl;
345     return ExecutionPlan();
346   }
347   operators.emplace_back(op5, xnn_delete_operator);
348 
349   xnn_operator_t op6 = nullptr;
350   status = xnn_create_convolution2d_nhwc_f16(
351     0 /* top padding */, 0 /* right padding */,
352     0 /* bottom padding */, 0 /* left padding */,
353     1 /* kernel height */, 1 /* kernel width */,
354     1 /* subsampling height */, 1 /* subsampling width */,
355     1 /* dilation_height */, 1 /* dilation_width */,
356     1 /* groups */,
357     128 /* input channels per group */,
358     128 /* output_channels_per_group */,
359     128 /* input pixel stride */,
360     128 /* output pixel stride */,
361     w42.data(), w43.data(),
362     0.0f /* output min */, 6.0f /* output max */,
363     0 /* flags */,
364     &caches,
365     &op6);
366   if (status != xnn_status_success) {
367     std::cerr << "failed to create operation #6" << std::endl;
368     return ExecutionPlan();
369   }
370   operators.emplace_back(op6, xnn_delete_operator);
371 
372   xnn_operator_t op7 = nullptr;
373   status = xnn_create_convolution2d_nhwc_f16(
374     0 /* top padding */, 1 /* right padding */,
375     1 /* bottom padding */, 0 /* left padding */,
376     3 /* kernel height */, 3 /* kernel width */,
377     2 /* subsampling height */, 2 /* subsampling width */,
378     1 /* dilation_height */, 1 /* dilation_width */,
379     128 /* groups */,
380     1 /* input channels per group */,
381     1 /* output_channels_per_group */,
382     128 /* input pixel stride */,
383     128 /* output pixel stride */,
384     w44.data(), w45.data(),
385     0.0f /* output min */, 6.0f /* output max */,
386     0 /* flags */,
387     &caches,
388     &op7);
389   if (status != xnn_status_success) {
390     std::cerr << "failed to create operation #7" << std::endl;
391     return ExecutionPlan();
392   }
393   operators.emplace_back(op7, xnn_delete_operator);
394 
395   xnn_operator_t op8 = nullptr;
396   status = xnn_create_convolution2d_nhwc_f16(
397     0 /* top padding */, 0 /* right padding */,
398     0 /* bottom padding */, 0 /* left padding */,
399     1 /* kernel height */, 1 /* kernel width */,
400     1 /* subsampling height */, 1 /* subsampling width */,
401     1 /* dilation_height */, 1 /* dilation_width */,
402     1 /* groups */,
403     128 /* input channels per group */,
404     256 /* output_channels_per_group */,
405     128 /* input pixel stride */,
406     256 /* output pixel stride */,
407     w46.data(), w47.data(),
408     0.0f /* output min */, 6.0f /* output max */,
409     0 /* flags */,
410     &caches,
411     &op8);
412   if (status != xnn_status_success) {
413     std::cerr << "failed to create operation #8" << std::endl;
414     return ExecutionPlan();
415   }
416   operators.emplace_back(op8, xnn_delete_operator);
417 
418   xnn_operator_t op9 = nullptr;
419   status = xnn_create_convolution2d_nhwc_f16(
420     1 /* top padding */, 1 /* right padding */,
421     1 /* bottom padding */, 1 /* left padding */,
422     3 /* kernel height */, 3 /* kernel width */,
423     1 /* subsampling height */, 1 /* subsampling width */,
424     1 /* dilation_height */, 1 /* dilation_width */,
425     256 /* groups */,
426     1 /* input channels per group */,
427     1 /* output_channels_per_group */,
428     256 /* input pixel stride */,
429     256 /* output pixel stride */,
430     w48.data(), w49.data(),
431     0.0f /* output min */, 6.0f /* output max */,
432     0 /* flags */,
433     &caches,
434     &op9);
435   if (status != xnn_status_success) {
436     std::cerr << "failed to create operation #9" << std::endl;
437     return ExecutionPlan();
438   }
439   operators.emplace_back(op9, xnn_delete_operator);
440 
441   xnn_operator_t op10 = nullptr;
442   status = xnn_create_convolution2d_nhwc_f16(
443     0 /* top padding */, 0 /* right padding */,
444     0 /* bottom padding */, 0 /* left padding */,
445     1 /* kernel height */, 1 /* kernel width */,
446     1 /* subsampling height */, 1 /* subsampling width */,
447     1 /* dilation_height */, 1 /* dilation_width */,
448     1 /* groups */,
449     256 /* input channels per group */,
450     256 /* output_channels_per_group */,
451     256 /* input pixel stride */,
452     256 /* output pixel stride */,
453     w50.data(), w51.data(),
454     0.0f /* output min */, 6.0f /* output max */,
455     0 /* flags */,
456     &caches,
457     &op10);
458   if (status != xnn_status_success) {
459     std::cerr << "failed to create operation #10" << std::endl;
460     return ExecutionPlan();
461   }
462   operators.emplace_back(op10, xnn_delete_operator);
463 
464   xnn_operator_t op11 = nullptr;
465   status = xnn_create_convolution2d_nhwc_f16(
466     0 /* top padding */, 1 /* right padding */,
467     1 /* bottom padding */, 0 /* left padding */,
468     3 /* kernel height */, 3 /* kernel width */,
469     2 /* subsampling height */, 2 /* subsampling width */,
470     1 /* dilation_height */, 1 /* dilation_width */,
471     256 /* groups */,
472     1 /* input channels per group */,
473     1 /* output_channels_per_group */,
474     256 /* input pixel stride */,
475     256 /* output pixel stride */,
476     w52.data(), w53.data(),
477     0.0f /* output min */, 6.0f /* output max */,
478     0 /* flags */,
479     &caches,
480     &op11);
481   if (status != xnn_status_success) {
482     std::cerr << "failed to create operation #11" << std::endl;
483     return ExecutionPlan();
484   }
485   operators.emplace_back(op11, xnn_delete_operator);
486 
487   xnn_operator_t op12 = nullptr;
488   status = xnn_create_convolution2d_nhwc_f16(
489     0 /* top padding */, 0 /* right padding */,
490     0 /* bottom padding */, 0 /* left padding */,
491     1 /* kernel height */, 1 /* kernel width */,
492     1 /* subsampling height */, 1 /* subsampling width */,
493     1 /* dilation_height */, 1 /* dilation_width */,
494     1 /* groups */,
495     256 /* input channels per group */,
496     512 /* output_channels_per_group */,
497     256 /* input pixel stride */,
498     512 /* output pixel stride */,
499     w54.data(), w55.data(),
500     0.0f /* output min */, 6.0f /* output max */,
501     0 /* flags */,
502     &caches,
503     &op12);
504   if (status != xnn_status_success) {
505     std::cerr << "failed to create operation #12" << std::endl;
506     return ExecutionPlan();
507   }
508   operators.emplace_back(op12, xnn_delete_operator);
509 
510   xnn_operator_t op13 = nullptr;
511   status = xnn_create_convolution2d_nhwc_f16(
512     1 /* top padding */, 1 /* right padding */,
513     1 /* bottom padding */, 1 /* left padding */,
514     3 /* kernel height */, 3 /* kernel width */,
515     1 /* subsampling height */, 1 /* subsampling width */,
516     1 /* dilation_height */, 1 /* dilation_width */,
517     512 /* groups */,
518     1 /* input channels per group */,
519     1 /* output_channels_per_group */,
520     512 /* input pixel stride */,
521     512 /* output pixel stride */,
522     w56.data(), w57.data(),
523     0.0f /* output min */, 6.0f /* output max */,
524     0 /* flags */,
525     &caches,
526     &op13);
527   if (status != xnn_status_success) {
528     std::cerr << "failed to create operation #13" << std::endl;
529     return ExecutionPlan();
530   }
531   operators.emplace_back(op13, xnn_delete_operator);
532 
533   xnn_operator_t op14 = nullptr;
534   status = xnn_create_convolution2d_nhwc_f16(
535     0 /* top padding */, 0 /* right padding */,
536     0 /* bottom padding */, 0 /* left padding */,
537     1 /* kernel height */, 1 /* kernel width */,
538     1 /* subsampling height */, 1 /* subsampling width */,
539     1 /* dilation_height */, 1 /* dilation_width */,
540     1 /* groups */,
541     512 /* input channels per group */,
542     512 /* output_channels_per_group */,
543     512 /* input pixel stride */,
544     512 /* output pixel stride */,
545     w58.data(), w59.data(),
546     0.0f /* output min */, 6.0f /* output max */,
547     0 /* flags */,
548     &caches,
549     &op14);
550   if (status != xnn_status_success) {
551     std::cerr << "failed to create operation #14" << std::endl;
552     return ExecutionPlan();
553   }
554   operators.emplace_back(op14, xnn_delete_operator);
555 
556   xnn_operator_t op15 = nullptr;
557   status = xnn_create_convolution2d_nhwc_f16(
558     1 /* top padding */, 1 /* right padding */,
559     1 /* bottom padding */, 1 /* left padding */,
560     3 /* kernel height */, 3 /* kernel width */,
561     1 /* subsampling height */, 1 /* subsampling width */,
562     1 /* dilation_height */, 1 /* dilation_width */,
563     512 /* groups */,
564     1 /* input channels per group */,
565     1 /* output_channels_per_group */,
566     512 /* input pixel stride */,
567     512 /* output pixel stride */,
568     w60.data(), w61.data(),
569     0.0f /* output min */, 6.0f /* output max */,
570     0 /* flags */,
571     &caches,
572     &op15);
573   if (status != xnn_status_success) {
574     std::cerr << "failed to create operation #15" << std::endl;
575     return ExecutionPlan();
576   }
577   operators.emplace_back(op15, xnn_delete_operator);
578 
579   xnn_operator_t op16 = nullptr;
580   status = xnn_create_convolution2d_nhwc_f16(
581     0 /* top padding */, 0 /* right padding */,
582     0 /* bottom padding */, 0 /* left padding */,
583     1 /* kernel height */, 1 /* kernel width */,
584     1 /* subsampling height */, 1 /* subsampling width */,
585     1 /* dilation_height */, 1 /* dilation_width */,
586     1 /* groups */,
587     512 /* input channels per group */,
588     512 /* output_channels_per_group */,
589     512 /* input pixel stride */,
590     512 /* output pixel stride */,
591     w62.data(), w63.data(),
592     0.0f /* output min */, 6.0f /* output max */,
593     0 /* flags */,
594     &caches,
595     &op16);
596   if (status != xnn_status_success) {
597     std::cerr << "failed to create operation #16" << std::endl;
598     return ExecutionPlan();
599   }
600   operators.emplace_back(op16, xnn_delete_operator);
601 
602   xnn_operator_t op17 = nullptr;
603   status = xnn_create_convolution2d_nhwc_f16(
604     1 /* top padding */, 1 /* right padding */,
605     1 /* bottom padding */, 1 /* left padding */,
606     3 /* kernel height */, 3 /* kernel width */,
607     1 /* subsampling height */, 1 /* subsampling width */,
608     1 /* dilation_height */, 1 /* dilation_width */,
609     512 /* groups */,
610     1 /* input channels per group */,
611     1 /* output_channels_per_group */,
612     512 /* input pixel stride */,
613     512 /* output pixel stride */,
614     w64.data(), w65.data(),
615     0.0f /* output min */, 6.0f /* output max */,
616     0 /* flags */,
617     &caches,
618     &op17);
619   if (status != xnn_status_success) {
620     std::cerr << "failed to create operation #17" << std::endl;
621     return ExecutionPlan();
622   }
623   operators.emplace_back(op17, xnn_delete_operator);
624 
625   xnn_operator_t op18 = nullptr;
626   status = xnn_create_convolution2d_nhwc_f16(
627     0 /* top padding */, 0 /* right padding */,
628     0 /* bottom padding */, 0 /* left padding */,
629     1 /* kernel height */, 1 /* kernel width */,
630     1 /* subsampling height */, 1 /* subsampling width */,
631     1 /* dilation_height */, 1 /* dilation_width */,
632     1 /* groups */,
633     512 /* input channels per group */,
634     512 /* output_channels_per_group */,
635     512 /* input pixel stride */,
636     512 /* output pixel stride */,
637     w66.data(), w67.data(),
638     0.0f /* output min */, 6.0f /* output max */,
639     0 /* flags */,
640     &caches,
641     &op18);
642   if (status != xnn_status_success) {
643     std::cerr << "failed to create operation #18" << std::endl;
644     return ExecutionPlan();
645   }
646   operators.emplace_back(op18, xnn_delete_operator);
647 
648   xnn_operator_t op19 = nullptr;
649   status = xnn_create_convolution2d_nhwc_f16(
650     1 /* top padding */, 1 /* right padding */,
651     1 /* bottom padding */, 1 /* left padding */,
652     3 /* kernel height */, 3 /* kernel width */,
653     1 /* subsampling height */, 1 /* subsampling width */,
654     1 /* dilation_height */, 1 /* dilation_width */,
655     512 /* groups */,
656     1 /* input channels per group */,
657     1 /* output_channels_per_group */,
658     512 /* input pixel stride */,
659     512 /* output pixel stride */,
660     w68.data(), w69.data(),
661     0.0f /* output min */, 6.0f /* output max */,
662     0 /* flags */,
663     &caches,
664     &op19);
665   if (status != xnn_status_success) {
666     std::cerr << "failed to create operation #19" << std::endl;
667     return ExecutionPlan();
668   }
669   operators.emplace_back(op19, xnn_delete_operator);
670 
671   xnn_operator_t op20 = nullptr;
672   status = xnn_create_convolution2d_nhwc_f16(
673     0 /* top padding */, 0 /* right padding */,
674     0 /* bottom padding */, 0 /* left padding */,
675     1 /* kernel height */, 1 /* kernel width */,
676     1 /* subsampling height */, 1 /* subsampling width */,
677     1 /* dilation_height */, 1 /* dilation_width */,
678     1 /* groups */,
679     512 /* input channels per group */,
680     512 /* output_channels_per_group */,
681     512 /* input pixel stride */,
682     512 /* output pixel stride */,
683     w70.data(), w71.data(),
684     0.0f /* output min */, 6.0f /* output max */,
685     0 /* flags */,
686     &caches,
687     &op20);
688   if (status != xnn_status_success) {
689     std::cerr << "failed to create operation #20" << std::endl;
690     return ExecutionPlan();
691   }
692   operators.emplace_back(op20, xnn_delete_operator);
693 
694   xnn_operator_t op21 = nullptr;
695   status = xnn_create_convolution2d_nhwc_f16(
696     1 /* top padding */, 1 /* right padding */,
697     1 /* bottom padding */, 1 /* left padding */,
698     3 /* kernel height */, 3 /* kernel width */,
699     1 /* subsampling height */, 1 /* subsampling width */,
700     1 /* dilation_height */, 1 /* dilation_width */,
701     512 /* groups */,
702     1 /* input channels per group */,
703     1 /* output_channels_per_group */,
704     512 /* input pixel stride */,
705     512 /* output pixel stride */,
706     w72.data(), w73.data(),
707     0.0f /* output min */, 6.0f /* output max */,
708     0 /* flags */,
709     &caches,
710     &op21);
711   if (status != xnn_status_success) {
712     std::cerr << "failed to create operation #21" << std::endl;
713     return ExecutionPlan();
714   }
715   operators.emplace_back(op21, xnn_delete_operator);
716 
717   xnn_operator_t op22 = nullptr;
718   status = xnn_create_convolution2d_nhwc_f16(
719     0 /* top padding */, 0 /* right padding */,
720     0 /* bottom padding */, 0 /* left padding */,
721     1 /* kernel height */, 1 /* kernel width */,
722     1 /* subsampling height */, 1 /* subsampling width */,
723     1 /* dilation_height */, 1 /* dilation_width */,
724     1 /* groups */,
725     512 /* input channels per group */,
726     512 /* output_channels_per_group */,
727     512 /* input pixel stride */,
728     512 /* output pixel stride */,
729     w74.data(), w75.data(),
730     0.0f /* output min */, 6.0f /* output max */,
731     0 /* flags */,
732     &caches,
733     &op22);
734   if (status != xnn_status_success) {
735     std::cerr << "failed to create operation #22" << std::endl;
736     return ExecutionPlan();
737   }
738   operators.emplace_back(op22, xnn_delete_operator);
739 
740   xnn_operator_t op23 = nullptr;
741   status = xnn_create_convolution2d_nhwc_f16(
742     0 /* top padding */, 1 /* right padding */,
743     1 /* bottom padding */, 0 /* left padding */,
744     3 /* kernel height */, 3 /* kernel width */,
745     2 /* subsampling height */, 2 /* subsampling width */,
746     1 /* dilation_height */, 1 /* dilation_width */,
747     512 /* groups */,
748     1 /* input channels per group */,
749     1 /* output_channels_per_group */,
750     512 /* input pixel stride */,
751     512 /* output pixel stride */,
752     w76.data(), w77.data(),
753     0.0f /* output min */, 6.0f /* output max */,
754     0 /* flags */,
755     &caches,
756     &op23);
757   if (status != xnn_status_success) {
758     std::cerr << "failed to create operation #23" << std::endl;
759     return ExecutionPlan();
760   }
761   operators.emplace_back(op23, xnn_delete_operator);
762 
763   xnn_operator_t op24 = nullptr;
764   status = xnn_create_convolution2d_nhwc_f16(
765     0 /* top padding */, 0 /* right padding */,
766     0 /* bottom padding */, 0 /* left padding */,
767     1 /* kernel height */, 1 /* kernel width */,
768     1 /* subsampling height */, 1 /* subsampling width */,
769     1 /* dilation_height */, 1 /* dilation_width */,
770     1 /* groups */,
771     512 /* input channels per group */,
772     1024 /* output_channels_per_group */,
773     512 /* input pixel stride */,
774     1024 /* output pixel stride */,
775     w78.data(), w79.data(),
776     0.0f /* output min */, 6.0f /* output max */,
777     0 /* flags */,
778     &caches,
779     &op24);
780   if (status != xnn_status_success) {
781     std::cerr << "failed to create operation #24" << std::endl;
782     return ExecutionPlan();
783   }
784   operators.emplace_back(op24, xnn_delete_operator);
785 
786   xnn_operator_t op25 = nullptr;
787   status = xnn_create_convolution2d_nhwc_f16(
788     1 /* top padding */, 1 /* right padding */,
789     1 /* bottom padding */, 1 /* left padding */,
790     3 /* kernel height */, 3 /* kernel width */,
791     1 /* subsampling height */, 1 /* subsampling width */,
792     1 /* dilation_height */, 1 /* dilation_width */,
793     1024 /* groups */,
794     1 /* input channels per group */,
795     1 /* output_channels_per_group */,
796     1024 /* input pixel stride */,
797     1024 /* output pixel stride */,
798     w80.data(), w81.data(),
799     0.0f /* output min */, 6.0f /* output max */,
800     0 /* flags */,
801     &caches,
802     &op25);
803   if (status != xnn_status_success) {
804     std::cerr << "failed to create operation #25" << std::endl;
805     return ExecutionPlan();
806   }
807   operators.emplace_back(op25, xnn_delete_operator);
808 
809   xnn_operator_t op26 = nullptr;
810   status = xnn_create_convolution2d_nhwc_f16(
811     0 /* top padding */, 0 /* right padding */,
812     0 /* bottom padding */, 0 /* left padding */,
813     1 /* kernel height */, 1 /* kernel width */,
814     1 /* subsampling height */, 1 /* subsampling width */,
815     1 /* dilation_height */, 1 /* dilation_width */,
816     1 /* groups */,
817     1024 /* input channels per group */,
818     1024 /* output_channels_per_group */,
819     1024 /* input pixel stride */,
820     1024 /* output pixel stride */,
821     w82.data(), w83.data(),
822     0.0f /* output min */, 6.0f /* output max */,
823     0 /* flags */,
824     &caches,
825     &op26);
826   if (status != xnn_status_success) {
827     std::cerr << "failed to create operation #26" << std::endl;
828     return ExecutionPlan();
829   }
830   operators.emplace_back(op26, xnn_delete_operator);
831 
832   xnn_operator_t op27 = nullptr;
833   status = xnn_create_global_average_pooling_nwc_f16(
834     1024 /* channels */, 1024 /* input stride */, 1024 /* output stride */,
835     -std::numeric_limits<float>::infinity(), std::numeric_limits<float>::infinity(),
836     0 /* flags */,
837     &op27);
838   if (status != xnn_status_success) {
839     std::cerr << "failed to create operation #27" << std::endl;
840     return ExecutionPlan();
841   }
842   operators.emplace_back(op27, xnn_delete_operator);
843 
844   xnn_operator_t op28 = nullptr;
845   status = xnn_create_convolution2d_nhwc_f16(
846     0 /* top padding */, 0 /* right padding */,
847     0 /* bottom padding */, 0 /* left padding */,
848     1 /* kernel height */, 1 /* kernel width */,
849     1 /* subsampling height */, 1 /* subsampling width */,
850     1 /* dilation_height */, 1 /* dilation_width */,
851     1 /* groups */,
852     1024 /* input channels per group */,
853     1001 /* output_channels_per_group */,
854     1024 /* input pixel stride */,
855     1001 /* output pixel stride */,
856     w84.data(), w85.data(),
857     -std::numeric_limits<float>::infinity() /* output min */, std::numeric_limits<float>::infinity() /* output max */,
858     0 /* flags */,
859     &caches,
860     &op28);
861   if (status != xnn_status_success) {
862     std::cerr << "failed to create operation #28" << std::endl;
863     return ExecutionPlan();
864   }
865   operators.emplace_back(op28, xnn_delete_operator);
866 
867 #if XNN_PLATFORM_JIT
868   xnn_finalize_code_memory(&code_cache.cache.code);
869 #endif
870 
871   status = xnn_setup_convolution2d_nhwc_f16(
872     op0,
873     1 /* batch size */, 224 /* input height */, 224 /* input width */,
874     v0.data() /* input */, v1.data() /* output */,
875     threadpool /* threadpool */);
876   if (status != xnn_status_success) {
877     std::cerr << "failed to setup operation #0" << std::endl;
878     return ExecutionPlan();
879   }
880 
881   status = xnn_setup_convolution2d_nhwc_f16(
882     op1,
883     1 /* batch size */, 112 /* input height */, 112 /* input width */,
884     v1.data() /* input */, v2.data() /* output */,
885     threadpool /* threadpool */);
886   if (status != xnn_status_success) {
887     std::cerr << "failed to setup operation #1" << std::endl;
888     return ExecutionPlan();
889   }
890 
891   status = xnn_setup_convolution2d_nhwc_f16(
892     op2,
893     1 /* batch size */, 112 /* input height */, 112 /* input width */,
894     v2.data() /* input */, v3.data() /* output */,
895     threadpool /* threadpool */);
896   if (status != xnn_status_success) {
897     std::cerr << "failed to setup operation #2" << std::endl;
898     return ExecutionPlan();
899   }
900 
901   status = xnn_setup_convolution2d_nhwc_f16(
902     op3,
903     1 /* batch size */, 112 /* input height */, 112 /* input width */,
904     v3.data() /* input */, v4.data() /* output */,
905     threadpool /* threadpool */);
906   if (status != xnn_status_success) {
907     std::cerr << "failed to setup operation #3" << std::endl;
908     return ExecutionPlan();
909   }
910 
911   status = xnn_setup_convolution2d_nhwc_f16(
912     op4,
913     1 /* batch size */, 56 /* input height */, 56 /* input width */,
914     v4.data() /* input */, v5.data() /* output */,
915     threadpool /* threadpool */);
916   if (status != xnn_status_success) {
917     std::cerr << "failed to setup operation #4" << std::endl;
918     return ExecutionPlan();
919   }
920 
921   status = xnn_setup_convolution2d_nhwc_f16(
922     op5,
923     1 /* batch size */, 56 /* input height */, 56 /* input width */,
924     v5.data() /* input */, v6.data() /* output */,
925     threadpool /* threadpool */);
926   if (status != xnn_status_success) {
927     std::cerr << "failed to setup operation #5" << std::endl;
928     return ExecutionPlan();
929   }
930 
931   status = xnn_setup_convolution2d_nhwc_f16(
932     op6,
933     1 /* batch size */, 56 /* input height */, 56 /* input width */,
934     v6.data() /* input */, v7.data() /* output */,
935     threadpool /* threadpool */);
936   if (status != xnn_status_success) {
937     std::cerr << "failed to setup operation #6" << std::endl;
938     return ExecutionPlan();
939   }
940 
941   status = xnn_setup_convolution2d_nhwc_f16(
942     op7,
943     1 /* batch size */, 56 /* input height */, 56 /* input width */,
944     v7.data() /* input */, v8.data() /* output */,
945     threadpool /* threadpool */);
946   if (status != xnn_status_success) {
947     std::cerr << "failed to setup operation #7" << std::endl;
948     return ExecutionPlan();
949   }
950 
951   status = xnn_setup_convolution2d_nhwc_f16(
952     op8,
953     1 /* batch size */, 28 /* input height */, 28 /* input width */,
954     v8.data() /* input */, v9.data() /* output */,
955     threadpool /* threadpool */);
956   if (status != xnn_status_success) {
957     std::cerr << "failed to setup operation #8" << std::endl;
958     return ExecutionPlan();
959   }
960 
961   status = xnn_setup_convolution2d_nhwc_f16(
962     op9,
963     1 /* batch size */, 28 /* input height */, 28 /* input width */,
964     v9.data() /* input */, v10.data() /* output */,
965     threadpool /* threadpool */);
966   if (status != xnn_status_success) {
967     std::cerr << "failed to setup operation #9" << std::endl;
968     return ExecutionPlan();
969   }
970 
971   status = xnn_setup_convolution2d_nhwc_f16(
972     op10,
973     1 /* batch size */, 28 /* input height */, 28 /* input width */,
974     v10.data() /* input */, v11.data() /* output */,
975     threadpool /* threadpool */);
976   if (status != xnn_status_success) {
977     std::cerr << "failed to setup operation #10" << std::endl;
978     return ExecutionPlan();
979   }
980 
981   status = xnn_setup_convolution2d_nhwc_f16(
982     op11,
983     1 /* batch size */, 28 /* input height */, 28 /* input width */,
984     v11.data() /* input */, v12.data() /* output */,
985     threadpool /* threadpool */);
986   if (status != xnn_status_success) {
987     std::cerr << "failed to setup operation #11" << std::endl;
988     return ExecutionPlan();
989   }
990 
991   status = xnn_setup_convolution2d_nhwc_f16(
992     op12,
993     1 /* batch size */, 14 /* input height */, 14 /* input width */,
994     v12.data() /* input */, v13.data() /* output */,
995     threadpool /* threadpool */);
996   if (status != xnn_status_success) {
997     std::cerr << "failed to setup operation #12" << std::endl;
998     return ExecutionPlan();
999   }
1000 
1001   status = xnn_setup_convolution2d_nhwc_f16(
1002     op13,
1003     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1004     v13.data() /* input */, v14.data() /* output */,
1005     threadpool /* threadpool */);
1006   if (status != xnn_status_success) {
1007     std::cerr << "failed to setup operation #13" << std::endl;
1008     return ExecutionPlan();
1009   }
1010 
1011   status = xnn_setup_convolution2d_nhwc_f16(
1012     op14,
1013     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1014     v14.data() /* input */, v15.data() /* output */,
1015     threadpool /* threadpool */);
1016   if (status != xnn_status_success) {
1017     std::cerr << "failed to setup operation #14" << std::endl;
1018     return ExecutionPlan();
1019   }
1020 
1021   status = xnn_setup_convolution2d_nhwc_f16(
1022     op15,
1023     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1024     v15.data() /* input */, v16.data() /* output */,
1025     threadpool /* threadpool */);
1026   if (status != xnn_status_success) {
1027     std::cerr << "failed to setup operation #15" << std::endl;
1028     return ExecutionPlan();
1029   }
1030 
1031   status = xnn_setup_convolution2d_nhwc_f16(
1032     op16,
1033     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1034     v16.data() /* input */, v17.data() /* output */,
1035     threadpool /* threadpool */);
1036   if (status != xnn_status_success) {
1037     std::cerr << "failed to setup operation #16" << std::endl;
1038     return ExecutionPlan();
1039   }
1040 
1041   status = xnn_setup_convolution2d_nhwc_f16(
1042     op17,
1043     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1044     v17.data() /* input */, v18.data() /* output */,
1045     threadpool /* threadpool */);
1046   if (status != xnn_status_success) {
1047     std::cerr << "failed to setup operation #17" << std::endl;
1048     return ExecutionPlan();
1049   }
1050 
1051   status = xnn_setup_convolution2d_nhwc_f16(
1052     op18,
1053     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1054     v18.data() /* input */, v19.data() /* output */,
1055     threadpool /* threadpool */);
1056   if (status != xnn_status_success) {
1057     std::cerr << "failed to setup operation #18" << std::endl;
1058     return ExecutionPlan();
1059   }
1060 
1061   status = xnn_setup_convolution2d_nhwc_f16(
1062     op19,
1063     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1064     v19.data() /* input */, v20.data() /* output */,
1065     threadpool /* threadpool */);
1066   if (status != xnn_status_success) {
1067     std::cerr << "failed to setup operation #19" << std::endl;
1068     return ExecutionPlan();
1069   }
1070 
1071   status = xnn_setup_convolution2d_nhwc_f16(
1072     op20,
1073     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1074     v20.data() /* input */, v21.data() /* output */,
1075     threadpool /* threadpool */);
1076   if (status != xnn_status_success) {
1077     std::cerr << "failed to setup operation #20" << std::endl;
1078     return ExecutionPlan();
1079   }
1080 
1081   status = xnn_setup_convolution2d_nhwc_f16(
1082     op21,
1083     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1084     v21.data() /* input */, v22.data() /* output */,
1085     threadpool /* threadpool */);
1086   if (status != xnn_status_success) {
1087     std::cerr << "failed to setup operation #21" << std::endl;
1088     return ExecutionPlan();
1089   }
1090 
1091   status = xnn_setup_convolution2d_nhwc_f16(
1092     op22,
1093     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1094     v22.data() /* input */, v23.data() /* output */,
1095     threadpool /* threadpool */);
1096   if (status != xnn_status_success) {
1097     std::cerr << "failed to setup operation #22" << std::endl;
1098     return ExecutionPlan();
1099   }
1100 
1101   status = xnn_setup_convolution2d_nhwc_f16(
1102     op23,
1103     1 /* batch size */, 14 /* input height */, 14 /* input width */,
1104     v23.data() /* input */, v24.data() /* output */,
1105     threadpool /* threadpool */);
1106   if (status != xnn_status_success) {
1107     std::cerr << "failed to setup operation #23" << std::endl;
1108     return ExecutionPlan();
1109   }
1110 
1111   status = xnn_setup_convolution2d_nhwc_f16(
1112     op24,
1113     1 /* batch size */, 7 /* input height */, 7 /* input width */,
1114     v24.data() /* input */, v25.data() /* output */,
1115     threadpool /* threadpool */);
1116   if (status != xnn_status_success) {
1117     std::cerr << "failed to setup operation #24" << std::endl;
1118     return ExecutionPlan();
1119   }
1120 
1121   status = xnn_setup_convolution2d_nhwc_f16(
1122     op25,
1123     1 /* batch size */, 7 /* input height */, 7 /* input width */,
1124     v25.data() /* input */, v26.data() /* output */,
1125     threadpool /* threadpool */);
1126   if (status != xnn_status_success) {
1127     std::cerr << "failed to setup operation #25" << std::endl;
1128     return ExecutionPlan();
1129   }
1130 
1131   status = xnn_setup_convolution2d_nhwc_f16(
1132     op26,
1133     1 /* batch size */, 7 /* input height */, 7 /* input width */,
1134     v26.data() /* input */, v27.data() /* output */,
1135     threadpool /* threadpool */);
1136   if (status != xnn_status_success) {
1137     std::cerr << "failed to setup operation #26" << std::endl;
1138     return ExecutionPlan();
1139   }
1140 
1141   status = xnn_setup_global_average_pooling_nwc_f16(
1142     op27,
1143     1 /* batch size */, 49 /* width */,
1144     v27.data() /* input */, v28.data() /* output */,
1145     threadpool /* threadpool */);
1146   if (status != xnn_status_success) {
1147     std::cerr << "failed to setup operation #27" << std::endl;
1148     return ExecutionPlan();
1149   }
1150 
1151   status = xnn_setup_convolution2d_nhwc_f16(
1152     op28,
1153     1 /* batch size */, 1 /* input height */, 1 /* input width */,
1154     v28.data() /* input */, v29.data() /* output */,
1155     threadpool /* threadpool */);
1156   if (status != xnn_status_success) {
1157     std::cerr << "failed to setup operation #28" << std::endl;
1158     return ExecutionPlan();
1159   }
1160 
1161   #pragma clang diagnostic push
1162   #pragma clang diagnostic ignored "-Wpessimizing-move"
1163   return operators;
1164   #pragma clang diagnostic pop
1165 }
1166 
1167 }  // namespace models
1168