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nearest neighbor fp32 align corners

This commit is contained in:
zhaozhenlong 2020-09-11 15:58:19 +08:00
parent 2f14c40934
commit 4744e4459e
4 changed files with 234 additions and 12 deletions
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25
mindspore/lite/nnacl/fp32/resize.c
View File

@ -277,21 +277,36 @@ int ResizeBilinear2(const float *input_data, float *output_data, const int *inpu
return NNACL_OK;
}
int CalcNearestNeighbor(const int out_position, const int in_size, const float scale, const bool align_corners) {
int actual_v;
if (align_corners) {
actual_v = (int)(round((float)out_position * scale));
} else {
actual_v = (int)(floor((float)out_position * scale));
}
int input_position = actual_v < in_size ? actual_v : in_size - 1;
return input_position;
}
int ResizeNearestNeighbor(const float *input_data, float *output_data, const int *input_shape, const int *output_shape,
int tid, int thread_num) {
bool align_corners, int tid, int thread_num) {
int batch, y, x, c;
c = input_shape[3];
float height_scale = (float)(input_shape[1]) / (float)(output_shape[1]);
float width_scale = (float)(input_shape[2]) / (float)(output_shape[2]);
if (align_corners && output_shape[1] > 1) {
height_scale = (float)(input_shape[1] - 1) / (output_shape[1] - 1);
}
if (align_corners && output_shape[2] > 1) {
width_scale = (float)(input_shape[2] - 1) / (output_shape[2] - 1);
}
for (batch = 0; batch < output_shape[0]; batch++) {
for (y = tid; y < output_shape[1]; y += thread_num) {
int actual_y = (int)(floor((float)(y)*height_scale));
int input_y = actual_y < input_shape[1] ? actual_y : input_shape[1] - 1;
int input_y = CalcNearestNeighbor(y, input_shape[1], height_scale, align_corners);
for (x = 0; x < output_shape[2]; x++) {
int actual_x = (int)(floor((float)(x)*width_scale));
int input_x = actual_x < input_shape[2] ? actual_x : input_shape[2] - 1;
int input_x = CalcNearestNeighbor(x, input_shape[2], width_scale, align_corners);
int in_offset = offset(input_shape, batch, input_y, input_x, 0);
int out_offset = offset(output_shape, batch, y, x, 0);
memcpy(output_data + out_offset, input_data + in_offset, c * sizeof(float));

2
mindspore/lite/nnacl/fp32/resize.h
View File

@ -38,7 +38,7 @@ int ResizeBilinear2(const float *input_data, float *output_data, const int *inpu
float *x_left_weights, float *line0, float *line1, int n_h_begin, int n_h_end);
int ResizeNearestNeighbor(const float *input_data, float *output_data, const int *input_shape, const int *output_shape,
int tid, int thread_num);
bool align_corners, int tid, int thread_num);
#ifdef __cplusplus
}
#endif

8
mindspore/lite/src/runtime/kernel/arm/fp32/resize.cc
View File

@ -179,12 +179,8 @@ int ResizeCPUKernel::RunImpl(int task_id) {
break;
}
case static_cast<int>(schema::ResizeMethod_NEAREST_NEIGHBOR): {
if (align_corners_) {
MS_LOG(ERROR) << "ResizeNearestNeighbor not support align_corners.";
return RET_ERROR;
}
ret = ResizeNearestNeighbor(input_data, output_data, input_shape.data(), out_tensors_[0]->shape().data(), task_id,
context_->thread_num_);
ret = ResizeNearestNeighbor(input_data, output_data, input_shape.data(), out_tensors_[0]->shape().data(),
align_corners_, task_id, context_->thread_num_);
break;
}
case schema::ResizeMethod_UNKNOW:

211
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/resize_nearest_neighbor_fp32_tests.cc
View File

@ -336,4 +336,215 @@ TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest14) {
CompareOutputData(output_data, expect.data(), output_size, err_tol);
}
// 4*4 -> 6*6 align_corners True
TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest15) {
float input_data[] = {0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0};
float output_data[36] = {0};
std::vector<int> input_shape = {1, 4, 4, 1};
std::vector<int> output_shape = {1, 6, 6, 1};
std::vector<float> expect = {0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 4.0, 5.0, 5.0, 6.0, 6.0, 7.0,
4.0, 5.0, 5.0, 6.0, 6.0, 7.0, 8.0, 9.0, 9.0, 10.0, 10.0, 11.0,
8.0, 9.0, 9.0, 10.0, 10.0, 11.0, 12.0, 13.0, 13.0, 14.0, 14.0, 15.0};
size_t output_size = 36;
bool align_corners = true;
Prepare(input_shape, output_shape, input_data, output_data, align_corners, 2);
auto ret = kernel_->Run();
EXPECT_EQ(0, ret);
CompareOutputData(output_data, expect.data(), output_size, err_tol);
}
// 2*7*5*8 -> 2*14*10*8 align_corners True
TEST_F(TestResizeNearestNeighborFp32, ResizeNearestNeighborTest16) {
float input_data[] = {
0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0,
16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0,
32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0,
48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,
64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0, 74.0, 75.0, 76.0, 77.0, 78.0, 79.0,
80.0, 81.0, 82.0, 83.0, 84.0, 85.0, 86.0, 87.0, 88.0, 89.0, 90.0, 91.0, 92.0, 93.0, 94.0, 95.0,
96.0, 97.0, 98.0, 99.0, 100.0, 101.0, 102.0, 103.0, 104.0, 105.0, 106.0, 107.0, 108.0, 109.0, 110.0, 111.0,
112.0, 113.0, 114.0, 115.0, 116.0, 117.0, 118.0, 119.0, 120.0, 121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0,
128.0, 129.0, 130.0, 131.0, 132.0, 133.0, 134.0, 135.0, 136.0, 137.0, 138.0, 139.0, 140.0, 141.0, 142.0, 143.0,
144.0, 145.0, 146.0, 147.0, 148.0, 149.0, 150.0, 151.0, 152.0, 153.0, 154.0, 155.0, 156.0, 157.0, 158.0, 159.0,
160.0, 161.0, 162.0, 163.0, 164.0, 165.0, 166.0, 167.0, 168.0, 169.0, 170.0, 171.0, 172.0, 173.0, 174.0, 175.0,
176.0, 177.0, 178.0, 179.0, 180.0, 181.0, 182.0, 183.0, 184.0, 185.0, 186.0, 187.0, 188.0, 189.0, 190.0, 191.0,
192.0, 193.0, 194.0, 195.0, 196.0, 197.0, 198.0, 199.0, 200.0, 201.0, 202.0, 203.0, 204.0, 205.0, 206.0, 207.0,
208.0, 209.0, 210.0, 211.0, 212.0, 213.0, 214.0, 215.0, 216.0, 217.0, 218.0, 219.0, 220.0, 221.0, 222.0, 223.0,
224.0, 225.0, 226.0, 227.0, 228.0, 229.0, 230.0, 231.0, 232.0, 233.0, 234.0, 235.0, 236.0, 237.0, 238.0, 239.0,
240.0, 241.0, 242.0, 243.0, 244.0, 245.0, 246.0, 247.0, 248.0, 249.0, 250.0, 251.0, 252.0, 253.0, 254.0, 255.0,
256.0, 257.0, 258.0, 259.0, 260.0, 261.0, 262.0, 263.0, 264.0, 265.0, 266.0, 267.0, 268.0, 269.0, 270.0, 271.0,
272.0, 273.0, 274.0, 275.0, 276.0, 277.0, 278.0, 279.0, 280.0, 281.0, 282.0, 283.0, 284.0, 285.0, 286.0, 287.0,
288.0, 289.0, 290.0, 291.0, 292.0, 293.0, 294.0, 295.0, 296.0, 297.0, 298.0, 299.0, 300.0, 301.0, 302.0, 303.0,
304.0, 305.0, 306.0, 307.0, 308.0, 309.0, 310.0, 311.0, 312.0, 313.0, 314.0, 315.0, 316.0, 317.0, 318.0, 319.0,
320.0, 321.0, 322.0, 323.0, 324.0, 325.0, 326.0, 327.0, 328.0, 329.0, 330.0, 331.0, 332.0, 333.0, 334.0, 335.0,
336.0, 337.0, 338.0, 339.0, 340.0, 341.0, 342.0, 343.0, 344.0, 345.0, 346.0, 347.0, 348.0, 349.0, 350.0, 351.0,
352.0, 353.0, 354.0, 355.0, 356.0, 357.0, 358.0, 359.0, 360.0, 361.0, 362.0, 363.0, 364.0, 365.0, 366.0, 367.0,
368.0, 369.0, 370.0, 371.0, 372.0, 373.0, 374.0, 375.0, 376.0, 377.0, 378.0, 379.0, 380.0, 381.0, 382.0, 383.0,
384.0, 385.0, 386.0, 387.0, 388.0, 389.0, 390.0, 391.0, 392.0, 393.0, 394.0, 395.0, 396.0, 397.0, 398.0, 399.0,
400.0, 401.0, 402.0, 403.0, 404.0, 405.0, 406.0, 407.0, 408.0, 409.0, 410.0, 411.0, 412.0, 413.0, 414.0, 415.0,
416.0, 417.0, 418.0, 419.0, 420.0, 421.0, 422.0, 423.0, 424.0, 425.0, 426.0, 427.0, 428.0, 429.0, 430.0, 431.0,
432.0, 433.0, 434.0, 435.0, 436.0, 437.0, 438.0, 439.0, 440.0, 441.0, 442.0, 443.0, 444.0, 445.0, 446.0, 447.0,
448.0, 449.0, 450.0, 451.0, 452.0, 453.0, 454.0, 455.0, 456.0, 457.0, 458.0, 459.0, 460.0, 461.0, 462.0, 463.0,
464.0, 465.0, 466.0, 467.0, 468.0, 469.0, 470.0, 471.0, 472.0, 473.0, 474.0, 475.0, 476.0, 477.0, 478.0, 479.0,
480.0, 481.0, 482.0, 483.0, 484.0, 485.0, 486.0, 487.0, 488.0, 489.0, 490.0, 491.0, 492.0, 493.0, 494.0, 495.0,
496.0, 497.0, 498.0, 499.0, 500.0, 501.0, 502.0, 503.0, 504.0, 505.0, 506.0, 507.0, 508.0, 509.0, 510.0, 511.0,
512.0, 513.0, 514.0, 515.0, 516.0, 517.0, 518.0, 519.0, 520.0, 521.0, 522.0, 523.0, 524.0, 525.0, 526.0, 527.0,
528.0, 529.0, 530.0, 531.0, 532.0, 533.0, 534.0, 535.0, 536.0, 537.0, 538.0, 539.0, 540.0, 541.0, 542.0, 543.0,
544.0, 545.0, 546.0, 547.0, 548.0, 549.0, 550.0, 551.0, 552.0, 553.0, 554.0, 555.0, 556.0, 557.0, 558.0, 559.0};
float output_data[2240] = {0};
std::vector<int> input_shape = {2, 7, 5, 8};
std::vector<int> output_shape = {2, 14, 10, 8};
std::vector<float> expect = {
0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0,
8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0,
16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0,
24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0,
32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0,
0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0,
8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0,
16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0,
24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0,
32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0,
40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0,
48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0, 48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0,
56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,
64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0,
72.0, 73.0, 74.0, 75.0, 76.0, 77.0, 78.0, 79.0, 72.0, 73.0, 74.0, 75.0, 76.0, 77.0, 78.0, 79.0,
40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0,
48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0, 48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0,
56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,
64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0,
72.0, 73.0, 74.0, 75.0, 76.0, 77.0, 78.0, 79.0, 72.0, 73.0, 74.0, 75.0, 76.0, 77.0, 78.0, 79.0,
80.0, 81.0, 82.0, 83.0, 84.0, 85.0, 86.0, 87.0, 80.0, 81.0, 82.0, 83.0, 84.0, 85.0, 86.0, 87.0,
88.0, 89.0, 90.0, 91.0, 92.0, 93.0, 94.0, 95.0, 88.0, 89.0, 90.0, 91.0, 92.0, 93.0, 94.0, 95.0,
96.0, 97.0, 98.0, 99.0, 100.0, 101.0, 102.0, 103.0, 96.0, 97.0, 98.0, 99.0, 100.0, 101.0, 102.0, 103.0,
104.0, 105.0, 106.0, 107.0, 108.0, 109.0, 110.0, 111.0, 104.0, 105.0, 106.0, 107.0, 108.0, 109.0, 110.0, 111.0,
112.0, 113.0, 114.0, 115.0, 116.0, 117.0, 118.0, 119.0, 112.0, 113.0, 114.0, 115.0, 116.0, 117.0, 118.0, 119.0,
80.0, 81.0, 82.0, 83.0, 84.0, 85.0, 86.0, 87.0, 80.0, 81.0, 82.0, 83.0, 84.0, 85.0, 86.0, 87.0,
88.0, 89.0, 90.0, 91.0, 92.0, 93.0, 94.0, 95.0, 88.0, 89.0, 90.0, 91.0, 92.0, 93.0, 94.0, 95.0,
96.0, 97.0, 98.0, 99.0, 100.0, 101.0, 102.0, 103.0, 96.0, 97.0, 98.0, 99.0, 100.0, 101.0, 102.0, 103.0,
104.0, 105.0, 106.0, 107.0, 108.0, 109.0, 110.0, 111.0, 104.0, 105.0, 106.0, 107.0, 108.0, 109.0, 110.0, 111.0,
112.0, 113.0, 114.0, 115.0, 116.0, 117.0, 118.0, 119.0, 112.0, 113.0, 114.0, 115.0, 116.0, 117.0, 118.0, 119.0,
120.0, 121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0, 120.0, 121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0,
128.0, 129.0, 130.0, 131.0, 132.0, 133.0, 134.0, 135.0, 128.0, 129.0, 130.0, 131.0, 132.0, 133.0, 134.0, 135.0,
136.0, 137.0, 138.0, 139.0, 140.0, 141.0, 142.0, 143.0, 136.0, 137.0, 138.0, 139.0, 140.0, 141.0, 142.0, 143.0,
144.0, 145.0, 146.0, 147.0, 148.0, 149.0, 150.0, 151.0, 144.0, 145.0, 146.0, 147.0, 148.0, 149.0, 150.0, 151.0,
152.0, 153.0, 154.0, 155.0, 156.0, 157.0, 158.0, 159.0, 152.0, 153.0, 154.0, 155.0, 156.0, 157.0, 158.0, 159.0,
120.0, 121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0, 120.0, 121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0,
128.0, 129.0, 130.0, 131.0, 132.0, 133.0, 134.0, 135.0, 128.0, 129.0, 130.0, 131.0, 132.0, 133.0, 134.0, 135.0,
136.0, 137.0, 138.0, 139.0, 140.0, 141.0, 142.0, 143.0, 136.0, 137.0, 138.0, 139.0, 140.0, 141.0, 142.0, 143.0,
144.0, 145.0, 146.0, 147.0, 148.0, 149.0, 150.0, 151.0, 144.0, 145.0, 146.0, 147.0, 148.0, 149.0, 150.0, 151.0,
152.0, 153.0, 154.0, 155.0, 156.0, 157.0, 158.0, 159.0, 152.0, 153.0, 154.0, 155.0, 156.0, 157.0, 158.0, 159.0,
160.0, 161.0, 162.0, 163.0, 164.0, 165.0, 166.0, 167.0, 160.0, 161.0, 162.0, 163.0, 164.0, 165.0, 166.0, 167.0,
168.0, 169.0, 170.0, 171.0, 172.0, 173.0, 174.0, 175.0, 168.0, 169.0, 170.0, 171.0, 172.0, 173.0, 174.0, 175.0,
176.0, 177.0, 178.0, 179.0, 180.0, 181.0, 182.0, 183.0, 176.0, 177.0, 178.0, 179.0, 180.0, 181.0, 182.0, 183.0,
184.0, 185.0, 186.0, 187.0, 188.0, 189.0, 190.0, 191.0, 184.0, 185.0, 186.0, 187.0, 188.0, 189.0, 190.0, 191.0,
192.0, 193.0, 194.0, 195.0, 196.0, 197.0, 198.0, 199.0, 192.0, 193.0, 194.0, 195.0, 196.0, 197.0, 198.0, 199.0,
160.0, 161.0, 162.0, 163.0, 164.0, 165.0, 166.0, 167.0, 160.0, 161.0, 162.0, 163.0, 164.0, 165.0, 166.0, 167.0,
168.0, 169.0, 170.0, 171.0, 172.0, 173.0, 174.0, 175.0, 168.0, 169.0, 170.0, 171.0, 172.0, 173.0, 174.0, 175.0,
176.0, 177.0, 178.0, 179.0, 180.0, 181.0, 182.0, 183.0, 176.0, 177.0, 178.0, 179.0, 180.0, 181.0, 182.0, 183.0,
184.0, 185.0, 186.0, 187.0, 188.0, 189.0, 190.0, 191.0, 184.0, 185.0, 186.0, 187.0, 188.0, 189.0, 190.0, 191.0,
192.0, 193.0, 194.0, 195.0, 196.0, 197.0, 198.0, 199.0, 192.0, 193.0, 194.0, 195.0, 196.0, 197.0, 198.0, 199.0,
200.0, 201.0, 202.0, 203.0, 204.0, 205.0, 206.0, 207.0, 200.0, 201.0, 202.0, 203.0, 204.0, 205.0, 206.0, 207.0,
208.0, 209.0, 210.0, 211.0, 212.0, 213.0, 214.0, 215.0, 208.0, 209.0, 210.0, 211.0, 212.0, 213.0, 214.0, 215.0,
216.0, 217.0, 218.0, 219.0, 220.0, 221.0, 222.0, 223.0, 216.0, 217.0, 218.0, 219.0, 220.0, 221.0, 222.0, 223.0,
224.0, 225.0, 226.0, 227.0, 228.0, 229.0, 230.0, 231.0, 224.0, 225.0, 226.0, 227.0, 228.0, 229.0, 230.0, 231.0,
232.0, 233.0, 234.0, 235.0, 236.0, 237.0, 238.0, 239.0, 232.0, 233.0, 234.0, 235.0, 236.0, 237.0, 238.0, 239.0,
200.0, 201.0, 202.0, 203.0, 204.0, 205.0, 206.0, 207.0, 200.0, 201.0, 202.0, 203.0, 204.0, 205.0, 206.0, 207.0,
208.0, 209.0, 210.0, 211.0, 212.0, 213.0, 214.0, 215.0, 208.0, 209.0, 210.0, 211.0, 212.0, 213.0, 214.0, 215.0,
216.0, 217.0, 218.0, 219.0, 220.0, 221.0, 222.0, 223.0, 216.0, 217.0, 218.0, 219.0, 220.0, 221.0, 222.0, 223.0,
224.0, 225.0, 226.0, 227.0, 228.0, 229.0, 230.0, 231.0, 224.0, 225.0, 226.0, 227.0, 228.0, 229.0, 230.0, 231.0,
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size_t output_size = 2240;
bool align_corners = true;
Prepare(input_shape, output_shape, input_data, output_data, align_corners, 2);
auto ret = kernel_->Run();
EXPECT_EQ(0, ret);
CompareOutputData(output_data, expect.data(), output_size, err_tol);
}
} // namespace mindspore