GPU NMS kernel and refactor of NMS operator

[CharlieL7]

Motivation

• Adds Non-Maximum Supression (NMS) GPU operator for better performance.
• Changes handling of NMS to better express the dynamic output in the MIGraphX IR.
• There will be followup PR after this one to remove the MIGRAPHX_USE_DYNAMIC_NMS environment variable and have the dynamic slice be the default parsing. There will then be an additional matcher in simplify_dyn_ops to figure out if the dynamic slice can be removed or rewritten.

Technical Details

• Adds GPU NMS split into 3 kernels: nms_sort, nms_filter, and nms_compact
  • nms_sort and nms_filter could be fused into the same kernel if an improved sorting kernel is used. These two use the same number of blocks and can use compatible number of threads. Currently the sort is limited to a power of 2 number of elements.
• Lowering will replace NMS with the GPU IR instructions for static input boxes and scores.
  • Will fallback to ref for dynamic input boxes and scores.
• NMS kernel mechanics:
  1. For each (batch, class) set of scores, sort the boxes by descending score.
  2. Calculate the IoU matrix between each box to every other box. Only need the upper triangular part of the matrix. Fully parallel calculation.
  3. Filter out boxes below the score threshold and then again for each (batch, class) sequentially by their IoU with a selected box. Able to do this step in parallel for each (batch, class). Copy selected box indices to a specified (batch, class) part of output memory.
  4. Selected boxes will be segmented into different parts of the output memory (because of doing the filtering in parallel per (batch, class)). Need to move selected box indices to be packed into the beginning of the output buffer. Have a 1 block kernel that runs after the filter kernel that does a prefix scan and copies selected box indices to the correct part of final output memory.
• Refactored op/nonmaxsuppression.hpp to always output a tuple of the whole output tensor and the number of selected boxes. The dynamic output shape is handled by a dynamic slice now.
• Added GPU tests and removed NMS verify tests:
  • Verify tests with random data do not make sense for NMS.
  • Added GPU tests have inputs and expected outputs generated using onnxruntime.

Changelog Category

Add a CHANGELOG.md entry for any option other than Not Applicable

• • Added: New functionality.
• • Changed: Changes to existing functionality.
• • Removed: Functionality or support that has been removed. (Compared to a previous release)
• • Optimized: Component performance that has been optimized or improved.
• • Resolved Issues: Known issues from a previous version that have been resolved.
• • Not Applicable: This PR is not to be included in the changelog.

[github-actions]

Remaining comments which cannot be posted as a review comment to avoid GitHub Rate Limit

format.py

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 322 in 5ca611f

static_assert(NumBatchClass <= 16000, "nms_compact: NumBatchClass exceeds the LDS budget for offsets[]");

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 339 in 5ca611f

num_selected[0] = offsets[NumBatchClass-1] + bc_counts[NumBatchClass-1];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 343 in 5ca611f

constexpr index_int index_size = 3;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 347 in 5ca611f

const index_int box_idx = i & NumBoxes;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 353 in 5ca611f

indices[batch_class_idx * NumBoxes + box_idx * index_size + k] ;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 67 in 5ca611f

const auto num_boxes = boxes_s.lens()[1];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 71 in 5ca611f

return shape{shape::uint8_type, {num_batches * num_classes * aligned_b * nms_bytes_per_data}};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 146 in 5ca611f

const auto num_boxes = boxes_s.lens()[1];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 148 in 5ca611f

const auto iou_packed = (num_boxes * (num_boxes - 1) / 2);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Lines 170 to 187 in 5ca611f

	auto sorted = m.insert_instruction(
	ins,
	make_op("gpu::nms_sort", {{"center_point_box", center_point_box}}),
	inputs[0],
	inputs[1]);
	auto filter = m.insert_instruction(
	ins,
	make_op("gpu::nms_filter",
	{{"num_batches", num_batches}, {"num_classes", num_classes}, {"num_boxes", num_boxes}}),
	sorted,
	inputs[2],
	inputs[3],
	inputs[4],
	mask_alloc);
	auto output =
	m.insert_instruction(ins, make_op("get_tuple_elem", {{"index", 0}}), filter);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Lines 191 to 192 in 5ca611f

	auto compact =
	m.insert_instruction(ins, make_op("gpu::nms_compact"), bc_counts, output);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/verify/test_nms.cpp

Lines 54 to 57 in 5ca611f

	//auto indices = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), nms);
	auto num_selected = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), nms);
	//auto slice_ins = mm->add_instruction(migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}}), indices, num_selected);
	//mm->add_return({slice_ins});

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/verify/test_nms.cpp

Line 201 in 5ca611f

[github-actions]

Remaining comments which cannot be posted as a review comment to avoid GitHub Rate Limit

format.py

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 220 in c2ddb73

int64_t max_out_val = 4;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 299 to 302 in c2ddb73

	std::vector<float> boxes_vec = {0.5, 0.5, 1.0, 1.0, 0.5, 0.6, 1.0, 1.0, 0.5, 0.4, 1.0, 1.0,
	0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0,
	0.5, 0.5, 1.0, 1.0, 0.5, 0.6, 1.0, 1.0, 0.5, 0.4, 1.0, 1.0,
	0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 346 to 348 in c2ddb73

	std::vector<float> boxes_vec = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1,
	0.0, -0.1, 1.0, 0.9, 0.0, 10.0, 1.0, 11.0,
	0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 378 to 384 in c2ddb73

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 388 to 397 in c2ddb73

	32.7256f, 35.1377f, 43.0832f, 42.2579f, 13.9286f, 15.6152f, 21.5240f, 28.2727f, 44.0782f, 37.5280f, 52.9916f, 48.3318f,
	38.8011f, 32.1818f, 50.5110f, 37.5550f, 33.9761f, -1.6170f, 43.8622f, 11.0347f, 5.3569f, 42.6478f, 14.1070f, 54.9145f,
	18.9216f, 34.8446f, 27.7505f, 41.2693f, -0.4375f, 36.7849f, 4.8178f, 41.8215f, 6.9987f, 1.1282f, 8.4302f, 11.6832f,
	30.5954f, 21.0410f, 37.7095f, 23.9976f, 35.2360f, 16.6405f, 39.2402f, 20.4393f, 45.0158f, 45.7867f, 51.7352f, 46.8898f,
	9.8174f, 26.1848f, 22.7651f, 38.2017f, 16.3854f, 35.9841f, 20.6606f, 46.2920f, 22.5697f, 16.7346f, 24.3859f, 27.6069f,
	7.0039f, 5.3968f, 11.9433f, 17.3270f, 3.9409f, 24.0168f, 9.0512f, 31.4417f, 18.6518f, -1.2903f, 28.9187f, 7.6721f,
	6.9462f, 39.9030f, 15.7447f, 42.8601f, 27.5034f, 30.2815f, 39.4780f, 32.8849f};
	std::vector<float> scores_vec = {
	0.6979f, 0.4657f, 0.8326f, 0.2503f, 0.1204f, 0.1810f, 0.7501f, 0.5157f, 0.2451f, 0.5509f, 0.2371f, 0.7267f,
	0.5015f, 0.4429f, 0.3714f, 0.6673f, 0.4256f, 0.1789f, 0.2062f, 0.9657f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 405 in c2ddb73

std::vector<int64_t> gold = {0, 0, 19, 0, 0, 2, 0, 0, 6, 0, 0, 11, 0, 0, 0, 0, 0, 15, 0, 0, 9, 0, 0, 7, 0, 0, 12, 0, 0, 1};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 433 to 449 in c2ddb73

	90.8581f, 82.6292f, 23.5447f, 19.9060f, 69.9707f, 89.6161f, 29.1830f, 26.1572f, 26.5870f, 14.0249f, 15.5215f, 14.1630f,
	96.9176f, 55.4036f, 5.1730f, 8.1873f, 77.8751f, 10.8576f, 1.4042f, 7.8632f, 71.6890f, 67.2240f, 7.6600f, 22.6344f,
	44.9361f, 28.1234f, 4.8228f, 24.6805f, 27.2242f, 65.9423f, 20.6521f, 4.0531f, 9.6391f, 72.6995f, 4.5331f, 2.9302f,
	90.2602f, 76.8647f, 15.6836f, 18.2386f, 45.5776f, 10.7741f, 21.1336f, 5.2390f, 20.2363f, 91.6012f, 17.8524f, 24.9153f,
	30.5957f, 23.0214f, 6.7935f, 9.9997f, 57.9220f, 3.7413f, 24.3196f, 5.1723f, 17.6773f, 55.4852f, 21.7468f, 27.7081f,
	85.6614f, 37.0922f, 22.4305f, 5.8004f, 75.8520f, 82.9790f, 4.8007f, 9.2569f, 71.9463f, 80.8251f, 4.5889f, 5.4548f,
	43.2093f, 31.7139f, 27.8993f, 4.3492f, 62.7309f, 95.2899f, 12.5298f, 1.6133f, 58.4098f, 29.0918f, 9.7275f, 2.6065f,
	64.9847f, 51.5057f, 15.1689f, 6.0646f, 8.4444f, 25.5965f, 20.2231f, 2.5481f, 41.5807f, 93.6044f, 28.7131f, 18.1432f,
	4.1614f, 16.4608f, 9.3069f, 20.7407f, 49.3991f, 4.4911f, 27.8194f, 12.4153f, 32.9861f, 43.5097f, 1.7209f, 10.2217f,
	14.4524f, 99.2376f, 17.1007f, 15.6313f, 10.3403f, 89.1677f, 19.3853f, 26.3751f, 58.7645f, 74.8608f, 4.0710f, 25.6828f,
	17.0593f, 89.0792f, 5.0698f, 2.2608f, 92.5120f, 89.3447f, 13.1543f, 6.2635f, 58.1061f, 51.8858f, 29.0207f, 7.8656f,
	34.6870f, 31.5929f, 18.2852f, 8.2322f, 59.0915f, 77.2012f, 28.0577f, 17.5657f, 2.2804f, 66.1661f, 24.3265f, 13.0716f,
	95.8559f, 37.3658f, 14.5541f, 2.4284f, 48.2303f, 9.4467f, 23.7581f, 11.8348f, 78.2735f, 74.6790f, 1.5173f, 16.1888f,
	8.2730f, 26.2461f, 4.1652f, 3.9485f, 48.6658f, 93.6813f, 25.0534f, 25.1703f, 49.0707f, 24.0971f, 24.1077f, 2.5069f,
	93.7826f, 12.2758f, 7.7466f, 27.8204f, 57.1728f, 83.1113f, 16.3923f, 3.8743f, 47.3489f, 15.3284f, 18.5745f, 25.4637f,
	26.6976f, 17.9268f, 26.1644f, 27.1769f, 33.1569f, 59.9383f, 18.4901f, 29.4075f, 52.0672f, 87.4562f, 12.9646f, 24.2588f,
	43.8911f, 19.6435f, 11.8513f, 23.6048f, 2.1612f, 31.0324f, 13.3506f, 19.6320f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 451 to 455 in c2ddb73

	0.8011f, 0.2211f, 0.5825f, 0.5628f, 0.8718f, 0.5165f, 0.4466f, 0.6756f, 0.3398f, 0.2258f, 0.5301f, 0.4752f,
	0.3093f, 0.4308f, 0.4298f, 0.3947f, 0.4415f, 0.7172f, 0.3672f, 0.9540f, 0.9247f, 0.5328f, 0.3955f, 0.5819f,
	0.8637f, 0.6873f, 0.8240f, 0.5795f, 0.6696f, 0.3593f, 0.7614f, 0.2822f, 0.7253f, 0.8746f, 0.2189f, 0.6529f,
	0.1856f, 0.7531f, 0.1760f, 0.9423f, 0.2237f, 0.9630f, 0.8208f, 0.6343f, 0.8044f, 0.8156f, 0.9514f, 0.3280f,
	0.6311f, 0.1855f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 463 in c2ddb73

std::vector<int64_t> gold = {0, 0, 41, 0, 0, 19, 0, 0, 46, 0, 0, 39, 0, 0, 20, 0, 0, 33, 0, 0, 4, 0, 0, 24, 0, 0, 26, 0, 0, 42, 0, 0, 45, 0, 0, 44, 0, 0, 0, 0, 0, 30, 0, 0, 32, 0, 0, 17, 0, 0, 25, 0, 0, 7, 0, 0, 28, 0, 0, 35};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 481 to 487 in c2ddb73

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 491 to 557 in c2ddb73

	-3.8699f, 108.8880f, 20.8101f, 137.5783f, 149.9079f, 29.3134f, 203.7504f, 39.2031f, 121.6031f, 107.1528f, 162.2282f, 118.8275f,
	27.1146f, 87.2265f, 42.1365f, 141.7457f, -7.3128f, 91.3799f, 44.0012f, 95.0142f, 25.9397f, 97.1572f, 47.4736f, 111.8955f,
	170.3318f, 143.6689f, 221.6791f, 161.9004f, 82.3933f, 144.8881f, 101.0310f, 174.8098f, 138.9017f, 80.6305f, 174.7306f, 116.2308f,
	115.0719f, 104.8666f, 139.4914f, 134.9707f, 105.8753f, 183.2658f, 123.0900f, 189.2287f, 2.3726f, 16.2585f, 55.6795f, 31.6349f,
	183.1709f, -1.9651f, 195.2389f, 48.8066f, 57.2666f, -1.7671f, 63.2705f, 36.8507f, 105.0166f, 111.9228f, 126.1903f, 151.2225f,
	118.2848f, 63.4507f, 161.6255f, 103.9927f, 105.5274f, 131.8586f, 154.1659f, 177.8699f, 158.1560f, 132.0321f, 218.0818f, 136.4605f,
	20.4451f, 55.4126f, 38.9305f, 78.0425f, 89.1363f, 163.2572f, 114.2048f, 196.0894f, 76.2707f, 142.0220f, 85.3431f, 162.9909f,
	77.3750f, 28.6949f, 112.2925f, 79.5191f, -6.0851f, 58.1025f, 53.7721f, 87.5743f, 5.6429f, 39.7135f, 47.9949f, 86.0625f,
	37.5563f, 5.8879f, 73.6739f, 57.1568f, 48.8660f, 14.1653f, 73.0158f, 44.9480f, 58.0793f, 159.8937f, 113.0820f, 214.5573f,
	107.0385f, 69.7607f, 137.3566f, 105.4010f, 122.4620f, 51.0809f, 131.3896f, 102.2471f, 71.0835f, 135.3897f, 93.6408f, 156.4846f,
	79.2752f, 95.3835f, 84.2380f, 125.8137f, 37.0673f, 171.0514f, 49.9841f, 203.4046f, 116.6400f, 152.4634f, 118.6825f, 159.6572f,
	49.5364f, 83.6166f, 77.2799f, 108.1312f, -12.0070f, 47.7104f, 26.4309f, 102.8334f, 73.0529f, 178.2168f, 94.3071f, 216.4359f,
	81.9253f, 137.8156f, 107.7278f, 149.2885f, 16.3219f, 179.7427f, 73.9152f, 200.7352f, 91.8087f, 17.5434f, 137.1745f, 29.8480f,
	96.6991f, 168.8745f, 129.6096f, 171.3390f, 131.5065f, 99.5547f, 149.2944f, 155.2749f, 102.6283f, 10.6622f, 156.5511f, 38.1065f,
	123.0512f, 108.0793f, 137.9220f, 127.2239f, 53.1452f, 119.0642f, 73.3404f, 155.3743f, 130.1690f, 1.7448f, 184.8039f, 3.1763f,
	93.7074f, 82.1619f, 125.9504f, 99.5652f, 63.8853f, 143.8404f, 108.6820f, 186.3194f, 107.2755f, 39.8756f, 143.1295f, 78.2680f,
	52.3550f, 62.2463f, 91.9079f, 121.1729f, 93.2160f, 69.6623f, 111.8797f, 107.2634f, 139.7207f, 45.7991f, 154.9616f, 74.9719f,
	167.2671f, 160.7261f, 187.2941f, 206.6506f, 179.1259f, 129.1106f, 189.2970f, 183.4070f, 74.4343f, 0.3572f, 127.0189f, 43.8782f,
	95.1992f, 170.4922f, 112.9108f, 228.3217f, 142.9101f, 152.2709f, 177.0380f, 199.4092f, 39.0269f, 30.7110f, 86.7534f, 82.8523f,
	143.8537f, 163.5132f, 191.0993f, 171.2454f, 85.3959f, -0.8223f, 112.2607f, 43.3901f, 8.6218f, 186.3383f, 37.7209f, 213.3036f,
	-15.4319f, 116.3204f, 44.2555f, 149.9535f, 147.9980f, 110.2290f, 188.7993f, 149.8210f, -13.4183f, -11.0214f, 35.6454f, 47.1977f,
	28.9969f, 149.8616f, 83.2476f, 208.9517f, 43.0921f, -3.2028f, 90.5599f, 14.8026f, 28.6361f, 26.0199f, 40.5617f, 70.3113f,
	45.6946f, 5.9799f, 79.8627f, 51.2289f, 145.0326f, 144.6320f, 152.0444f, 166.0751f, -16.8246f, 35.4867f, 22.6978f, 43.7950f,
	136.7519f, 180.4197f, 194.1175f, 183.8356f, 155.6840f, 107.8222f, 186.9352f, 154.6854f, 61.1796f, -7.7136f, 87.7250f, 22.1787f,
	29.1652f, -28.4875f, 32.2799f, 30.6594f, 91.3547f, -3.8851f, 148.9814f, 24.5483f, 20.3959f, 91.8365f, 27.4731f, 150.5336f,
	71.2720f, 147.6549f, 74.6957f, 172.9379f, 183.9269f, 23.7969f, 199.4448f, 71.6242f, 196.6597f, 166.8796f, 201.5260f, 172.8839f,
	140.4950f, -5.4397f, 168.3470f, 28.3325f, 46.4677f, 136.0320f, 77.9169f, 184.3535f, 127.8122f, 157.7804f, 147.2538f, 213.3378f,
	139.0779f, 129.6555f, 143.0846f, 179.1879f, 73.7761f, 138.0335f, 81.3605f, 141.2148f, 116.3348f, 156.1013f, 140.0206f, 179.0908f,
	-0.1401f, 6.0937f, 4.4311f, 9.9669f, 20.7149f, 36.6326f, 62.9081f, 44.0802f, 98.4106f, 4.5632f, 111.6248f, 45.4062f,
	23.3391f, 79.3651f, 42.1614f, 122.4473f, 21.0547f, 125.7129f, 45.3081f, 172.3624f, 154.4709f, 99.9714f, 180.0508f, 152.0333f,
	197.2776f, 147.9130f, 198.3756f, 192.5394f, 107.3878f, 6.9169f, 115.0000f, 55.1683f, 141.8624f, 144.9798f, 193.7655f, 148.8687f,
	197.5280f, 31.1895f, 198.6007f, 46.0271f, 12.8282f, 35.3058f, 43.8101f, 72.9977f, 74.7088f, 116.1662f, 104.5894f, 167.7956f,
	68.1883f, 195.4082f, 88.8408f, 196.6737f, 2.7857f, 106.6272f, 29.2340f, 137.9903f, 127.5389f, -9.5799f, 174.5932f, 31.3800f,
	61.4403f, 121.8884f, 112.0713f, 124.6352f, 15.4868f, 35.9096f, 55.8899f, 68.2298f, 35.5922f, 56.6701f, 44.2246f, 72.3261f,
	163.1796f, 40.7751f, 180.4136f, 56.2181f, 177.9262f, 90.7157f, 187.1069f, 101.2297f, 33.5656f, 108.4211f, 51.2933f, 164.8822f,
	73.5555f, 18.9549f, 114.3649f, 72.3462f, 119.3443f, 42.7151f, 174.0536f, 89.5792f, 169.1987f, 170.3059f, 182.1476f, 201.8479f,
	59.3192f, -5.2591f, 92.3019f, 24.6868f, 82.2129f, 76.0264f, 124.5949f, 108.2814f, 119.7321f, 125.9828f, 176.9545f, 158.6404f,
	127.7304f, 16.7712f, 164.7240f, 43.4104f, 148.5664f, 5.0880f, 164.6177f, 13.8616f, 95.0352f, 23.4340f, 132.9384f, 31.8482f,
	10.9685f, 155.1733f, 30.8775f, 212.3560f, 151.4989f, -12.8680f, 210.0904f, 16.5719f, 160.8241f, 9.0448f, 185.4050f, 66.2840f,
	138.8994f, 0.9312f, 180.3396f, 11.5822f, 18.7873f, 5.2706f, 21.1577f, 38.9812f, 28.5777f, 117.4022f, 53.1813f, 130.6575f,
	122.4044f, 40.3588f, 175.0358f, 56.2967f, -13.8737f, 112.4558f, 23.1297f, 115.2290f, 182.2486f, 114.0300f, 209.4412f, 122.0482f,
	47.3188f, 142.3400f, 103.5391f, 197.4341f, 118.1700f, -9.0369f, 169.5550f, 10.9335f, 167.5089f, 152.2341f, 187.5196f, 189.1137f,
	62.3618f, 109.6059f, 95.4902f, 138.0417f, 48.8767f, 20.2354f, 78.7763f, 44.8620f, 102.5983f, 138.3968f, 140.8982f, 170.7781f,
	105.8416f, 165.0748f, 126.5542f, 177.1219f, 74.1239f, 21.1889f, 89.5320f, 80.5165f, 92.9311f, 159.1187f, 147.7788f, 208.3988f,
	159.3220f, 68.5139f, 214.8306f, 113.2691f, 68.1500f, 106.3565f, 118.9061f, 135.0133f, 9.9914f, 191.9200f, 68.7055f, 201.9398f,
	52.9639f, 44.6476f, 97.9184f, 99.9669f, 55.7637f, 152.0609f, 101.8791f, 173.2028f, 3.2253f, 61.7017f, 49.2181f, 65.6580f,
	17.8964f, 149.2418f, 47.2522f, 170.4436f, 122.9471f, 96.2103f, 150.8778f, 144.0833f, 60.3089f, 24.4012f, 75.4822f, 62.1410f,
	171.4575f, 60.1555f, 210.5018f, 105.4550f, 39.6844f, 39.6149f, 57.7543f, 87.4394f, 11.6796f, 8.8690f, 27.8902f, 22.3743f,
	132.9151f, -21.7847f, 168.4868f, 33.7186f, 163.6127f, 55.8750f, 188.8017f, 82.7164f, 48.6664f, -15.5441f, 62.5789f, 23.1577f,
	15.8440f, 32.5294f, 64.9913f, 33.6657f, 11.2664f, 115.2323f, 63.0400f, 174.8410f, 98.9553f, 132.8318f, 109.8496f, 150.4047f,
	92.9619f, 145.3852f, 94.4048f, 150.0469f, 41.4721f, 49.4119f, 62.3038f, 77.4494f, -14.9919f, 173.6975f, 33.0612f, 182.3103f,
	71.0426f, 113.7725f, 121.5539f, 123.7598f, 187.2858f, 6.0529f, 196.4472f, 44.3576f, 107.1609f, 16.6524f, 153.8468f, 40.8351f,
	95.1880f, 110.9244f, 103.0146f, 166.3137f, 10.1316f, 24.6737f, 34.1453f, 44.5039f, 20.5283f, 79.5362f, 80.4462f, 123.3809f,
	52.7734f, 184.2525f, 65.1362f, 212.4573f, 147.9188f, -19.1670f, 158.0026f, 20.7701f, 162.3696f, -14.8751f, 188.3148f, 21.5070f,
	161.5482f, 184.1698f, 199.1086f, 213.0640f, 168.8931f, 88.4010f, 224.9343f, 145.4546f, 167.0391f, 14.7719f, 225.9076f, 35.9920f,
	188.0454f, 173.7320f, 193.1542f, 185.1889f, 9.7935f, 155.5723f, 18.9354f, 196.5798f, 3.7319f, 81.7829f, 51.3855f, 132.6973f,
	52.4097f, 122.6709f, 69.3770f, 126.0459f, 83.9766f, 40.8733f, 137.1827f, 68.4016f, -0.6763f, -16.7244f, 39.4674f, 36.9323f,
	165.3600f, 96.2998f, 172.9588f, 141.5273f, 98.2916f, 29.1927f, 148.4108f, 88.7094f, 102.7704f, 116.5475f, 114.1754f, 148.9009f,
	20.0692f, 147.2792f, 46.0554f, 187.2189f, 33.8616f, -5.7911f, 67.4406f, 13.0553f, 16.7898f, 90.6905f, 47.3350f, 147.5951f,
	149.6448f, 34.9492f, 191.1284f, 57.5630f, 97.0913f, 152.4916f, 136.5998f, 197.0638f, 117.2606f, 38.3403f, 176.7911f, 63.1255f,
	29.2236f, 105.0804f, 89.1895f, 139.2277f, 58.5150f, 88.9746f, 89.9861f, 132.4418f, 77.6626f, 63.7197f, 84.2794f, 94.7469f,
	130.0316f, 108.2651f, 173.9744f, 162.7832f, 125.1590f, 132.2845f, 183.7822f, 158.0233f, 31.4721f, 93.7989f, 51.2533f, 132.9762f,
	174.2021f, 141.0848f, 202.4134f, 162.2841f, 11.1001f, 184.1428f, 37.1620f, 209.2240f, 177.2076f, 70.3730f, 181.2413f, 97.3360f,
	-0.2527f, 98.7053f, 40.4109f, 107.1279f, 41.9845f, -0.7119f, 63.8314f, 5.6998f, 145.5655f, 139.0148f, 193.0259f, 179.3967f,
	10.8509f, 84.2082f, 60.9460f, 123.8838f, 57.9873f, 61.5364f, 107.4399f, 101.6481f, 77.1802f, 17.7313f, 102.7635f, 19.8975f,
	39.0662f, 167.7982f, 59.0374f, 188.0644f, 119.4588f, 72.6661f, 164.6393f, 85.3368f, 146.1259f, 113.0609f, 194.4079f, 159.9718f,
	159.9229f, 3.9862f, 189.9071f, 55.7634f, 41.0200f, 184.5329f, 94.7088f, 200.0870f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 559 to 575 in c2ddb73

	0.1439f, 0.8791f, 0.0961f, 0.1535f, 0.5338f, 0.0675f, 0.0528f, 0.0005f, 0.4363f, 0.7746f, 0.0348f, 0.6523f,
	0.8231f, 0.1680f, 0.1469f, 0.8608f, 0.8231f, 0.5389f, 0.8192f, 0.0928f, 0.3945f, 0.7378f, 0.2575f, 0.7523f,
	0.5042f, 0.7503f, 0.4647f, 0.3679f, 0.2192f, 0.2084f, 0.7515f, 0.1189f, 0.0860f, 0.1763f, 0.1753f, 0.8231f,
	0.3985f, 0.9904f, 0.1372f, 0.6535f, 0.4487f, 0.3929f, 0.8751f, 0.9756f, 0.8729f, 0.1923f, 0.2208f, 0.6561f,
	0.2891f, 0.7347f, 0.5664f, 0.5509f, 0.8285f, 0.7105f, 0.0266f, 0.0495f, 0.6016f, 0.4862f, 0.2602f, 0.4187f,
	0.7579f, 0.8266f, 0.5612f, 0.3854f, 0.2707f, 0.5219f, 0.3147f, 0.5641f, 0.6767f, 0.0661f, 0.0011f, 0.2123f,
	0.8945f, 0.6463f, 0.1720f, 0.8903f, 0.4700f, 0.4761f, 0.9355f, 0.0595f, 0.2152f, 0.5858f, 0.1955f, 0.6795f,
	0.2141f, 0.0992f, 0.2070f, 0.4227f, 0.1761f, 0.1347f, 0.8603f, 0.3204f, 0.3608f, 0.0553f, 0.3574f, 0.2648f,
	0.6105f, 0.2054f, 0.8884f, 0.9297f, 0.0998f, 0.1074f, 0.1153f, 0.6196f, 0.1220f, 0.8524f, 0.7543f, 0.8198f,
	0.5261f, 0.9967f, 0.0442f, 0.4013f, 0.3239f, 0.9486f, 0.5769f, 0.8062f, 0.1703f, 0.9786f, 0.4986f, 0.4937f,
	0.9709f, 0.3807f, 0.3975f, 0.5848f, 0.1281f, 0.3211f, 0.1932f, 0.1033f, 0.8661f, 0.5893f, 0.3587f, 0.4087f,
	0.4315f, 0.6331f, 0.9268f, 0.9328f, 0.3915f, 0.3293f, 0.4510f, 0.5679f, 0.4618f, 0.6588f, 0.5544f, 0.3207f,
	0.3457f, 0.3786f, 0.0946f, 0.1661f, 0.7231f, 0.3891f, 0.2145f, 0.5627f, 0.7555f, 0.2574f, 0.8268f, 0.9275f,
	0.5974f, 0.6689f, 0.0526f, 0.9455f, 0.3925f, 0.9239f, 0.5790f, 0.0046f, 0.0385f, 0.6804f, 0.5627f, 0.0265f,
	0.7435f, 0.8521f, 0.4964f, 0.4658f, 0.0055f, 0.7866f, 0.3307f, 0.8788f, 0.3731f, 0.5651f, 0.2703f, 0.1606f,
	0.7749f, 0.4966f, 0.5365f, 0.9654f, 0.9636f, 0.8556f, 0.1876f, 0.5943f, 0.8781f, 0.3745f, 0.1011f, 0.8110f,
	0.4818f, 0.5644f, 0.9821f, 0.6072f, 0.4250f, 0.3700f, 0.4176f, 0.1184f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 583 in c2ddb73

std::vector<int64_t> gold = {0, 0, 37, 0, 0, 43, 0, 0, 78, 0, 0, 99, 0, 0, 72, 0, 0, 75, 0, 0, 98, 0, 0, 1, 0, 0, 42, 0, 0, 44, 0, 0, 15, 0, 0, 90, 0, 0, 52, 0, 0, 61, 0, 0, 12, 1, 0, 9, 1, 0, 94, 1, 0, 17, 1, 0, 20, 1, 0, 83, 1, 0, 84, 1, 0, 13, 1, 0, 59, 1, 0, 35, 1, 0, 55, 1, 0, 34, 1, 0, 61, 1, 0, 75, 1, 0, 88, 1, 0, 28};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 601 to 607 in c2ddb73

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 611 to 620 in c2ddb73

	31.2680f, 53.5348f, 37.7043f, 73.6253f, 1.8071f, 55.2945f, 3.9368f, 78.7402f, 40.5016f, 12.5670f, 45.0345f, 32.9366f,
	78.2552f, 12.9548f, 80.7117f, 35.6526f, 73.9527f, 67.9870f, 79.4405f, 71.9065f, -3.8066f, -7.7339f, 10.2705f, 11.5692f,
	45.4706f, 34.8613f, 67.4569f, 48.4119f, 17.4632f, 30.3439f, 30.8192f, 43.8443f, 64.5403f, 44.3725f, 79.9380f, 66.0477f,
	0.7877f, 1.3956f, 6.4307f, 24.7471f, 65.1632f, 44.8608f, 84.5766f, 62.0721f, 59.3935f, 24.0849f, 74.6026f, 36.1925f,
	-1.0372f, 43.7485f, 19.8379f, 55.2458f, -6.6257f, -1.7353f, 16.1976f, 8.1505f, 62.2758f, 32.2798f, 71.2775f, 41.5966f,
	10.9190f, 36.7777f, 14.0023f, 46.7824f, 39.6937f, 15.6139f, 45.8900f, 18.6783f, 67.7244f, 9.7794f, 78.7948f, 12.5604f,
	34.0204f, 5.6094f, 56.7713f, 24.5464f, 26.9281f, 21.9014f, 36.6292f, 33.1611f, 26.2374f, -3.4581f, 44.9652f, 18.9477f,
	-1.6661f, 68.2450f, 11.7649f, 83.3261f, 74.8979f, 31.4950f, 80.1025f, 33.3041f, 20.6639f, 62.4061f, 29.0408f, 67.0291f,
	7.1374f, 75.0864f, 23.1608f, 80.8203f, 14.6460f, -5.2621f, 31.1216f, 18.1798f, 71.6501f, 49.1185f, 82.6496f, 55.1487f,
	4.4135f, 63.2815f, 10.6723f, 76.1439f, 60.5823f, 39.4727f, 78.1862f, 62.0048f, 54.1855f, 22.5844f, 59.0696f, 46.0598f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 622 to 629 in c2ddb73

	0.9367f, 0.1879f, 0.1073f, 0.4976f, 0.5195f, 0.5082f, 0.4367f, 0.9948f, 0.4863f, 0.4779f, 0.4218f, 0.0668f,
	0.5930f, 0.2280f, 0.6376f, 0.0508f, 0.9814f, 0.4690f, 0.8968f, 0.4756f, 0.0603f, 0.8222f, 0.6482f, 0.7818f,
	0.4282f, 0.6379f, 0.8562f, 0.6311f, 0.3477f, 0.6625f, 0.6719f, 0.9606f, 0.3709f, 0.4251f, 0.8121f, 0.5058f,
	0.7366f, 0.4597f, 0.2155f, 0.7452f, 0.1312f, 0.1986f, 0.6268f, 0.7473f, 0.8947f, 0.2726f, 0.1107f, 0.9560f,
	0.1544f, 0.1977f, 0.2913f, 0.5294f, 0.8828f, 0.7605f, 0.7082f, 0.1752f, 0.3577f, 0.4784f, 0.1474f, 0.2734f,
	0.3083f, 0.1273f, 0.5502f, 0.7050f, 0.0699f, 0.4811f, 0.7822f, 0.7480f, 0.8151f, 0.4482f, 0.8206f, 0.2408f,
	0.3608f, 0.1764f, 0.4675f, 0.3921f, 0.2409f, 0.7518f, 0.3138f, 0.2728f, 0.1309f, 0.4388f, 0.3030f, 0.3693f,
	0.2360f, 0.7632f, 0.9300f, 0.4979f, 0.6430f, 0.8672f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 637 in c2ddb73

std::vector<int64_t> gold = {0, 0, 7, 0, 0, 16, 0, 0, 0, 0, 0, 18, 0, 0, 26, 0, 1, 1, 0, 1, 17, 0, 1, 14, 0, 1, 22, 0, 1, 4, 0, 2, 26, 0, 2, 29, 0, 2, 10, 0, 2, 6, 0, 2, 25};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 655 to 661 in c2ddb73

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 665 to 798 in c2ddb73

	132.1894f, 453.1169f, 199.9736f, 545.7127f, 64.3090f, 275.1729f, 104.8258f, 338.3436f, 76.1273f, 401.7875f, 135.6448f, 487.9920f,
	12.8305f, 442.3624f, 77.1708f, 466.2458f, -5.9609f, 340.1129f, 126.0715f, 451.3386f, 15.0119f, 224.3769f, 56.2927f, 236.5545f,
	427.8277f, -14.2917f, 561.9954f, 95.4457f, 4.7940f, -55.8461f, 69.2637f, 71.6517f, 41.3494f, 202.9014f, 91.1927f, 274.2992f,
	375.6902f, 208.6749f, 451.5645f, 285.6396f, 258.4982f, 179.9212f, 321.7420f, 227.4412f, 367.5344f, 211.3590f, 406.8828f, 356.8083f,
	277.5064f, 220.9636f, 353.4056f, 331.1991f, 429.2783f, 390.3169f, 452.8968f, 446.2962f, 292.5150f, 40.8054f, 345.9525f, 67.8517f,
	218.4112f, 95.7302f, 303.7139f, 129.4475f, 325.0759f, 361.4403f, 387.6738f, 431.5647f, 161.8149f, 353.1971f, 285.5779f, 494.6398f,
	153.4061f, 442.2182f, 192.6577f, 552.6060f, 161.0782f, 419.9203f, 306.5742f, 452.9917f, 25.8953f, 380.4122f, 143.8188f, 509.4868f,
	325.7002f, 128.4980f, 470.8716f, 185.8499f, 67.4107f, 136.8775f, 193.2931f, 264.7841f, 65.6790f, 115.5359f, 87.8525f, 152.5492f,
	83.4548f, 256.5595f, 162.8974f, 349.7399f, 407.8717f, 399.8657f, 434.1985f, 538.9396f, 103.6427f, 152.6073f, 226.5586f, 192.0336f,
	299.0049f, 226.3779f, 387.0450f, 330.6239f, 408.0779f, 74.0950f, 448.3318f, 222.2046f, -30.8828f, 73.1804f, 108.6275f, 96.6196f,
	373.4308f, 90.5068f, 391.5936f, 104.6787f, 111.3250f, -21.7549f, 196.3405f, 79.7002f, 54.0937f, 448.8364f, 162.5287f, 500.4571f,
	339.5665f, 195.6321f, 349.3349f, 207.2475f, 409.8580f, 381.1502f, 499.9386f, 452.9707f, 86.2250f, 284.0088f, 208.7943f, 397.3206f,
	278.8861f, 74.2190f, 289.9477f, 117.7022f, 106.2550f, 62.2701f, 183.5792f, 113.1921f, 257.3803f, 342.4895f, 296.9053f, 469.4987f,
	261.0432f, 93.1105f, 360.8189f, 171.6012f, 295.8262f, 393.3591f, 314.5092f, 519.9261f, 241.4629f, 36.2717f, 382.0835f, 103.7837f,
	0.3826f, 267.3577f, 134.6972f, 410.3510f, 332.4151f, 358.2527f, 361.1253f, 456.2211f, 312.7919f, 108.4937f, 361.9585f, 126.7627f,
	297.0153f, 71.6643f, 385.5729f, 204.5431f, -16.9604f, 445.3092f, 91.0309f, 519.2097f, 189.9415f, 121.2467f, 256.8973f, 143.3509f,
	192.3739f, 203.1031f, 216.6613f, 226.8539f, 35.0965f, 164.5365f, 51.6150f, 267.9791f, 36.2014f, 122.4881f, 186.1665f, 130.5466f,
	186.0576f, 366.0443f, 254.9050f, 409.7468f, 305.9496f, 375.0105f, 436.9568f, 396.8388f, 82.0940f, 155.7987f, 154.9680f, 222.5193f,
	345.6593f, 386.1935f, 484.0906f, 448.9323f, 265.8611f, 67.1577f, 279.9372f, 145.9173f, 371.2164f, -19.1800f, 389.2053f, 23.4858f,
	166.5204f, 282.6964f, 306.0356f, 288.4709f, 178.5089f, 450.7671f, 320.6853f, 543.3107f, 285.9132f, -9.0198f, 333.8062f, 47.6641f,
	437.0255f, 54.9746f, 490.9451f, 153.0235f, 211.6987f, 250.8616f, 280.1138f, 268.0530f, 232.8247f, 403.4440f, 295.8328f, 406.4968f,
	286.3401f, 25.5231f, 315.6569f, 63.5189f, 301.3286f, 163.1046f, 436.1865f, 232.1301f, 16.5538f, 343.6795f, 55.2966f, 403.3963f,
	204.8009f, 124.9041f, 310.8865f, 246.6391f, 235.2927f, 65.7693f, 246.2989f, 123.0671f, 457.4555f, 57.7300f, 464.2295f, 137.7658f,
	197.5504f, 160.3075f, 295.9562f, 249.7413f, 208.4036f, 237.5821f, 259.9170f, 241.8350f, 431.7683f, 392.0298f, 530.4317f, 469.7846f,
	217.7836f, 294.9363f, 232.7928f, 347.3161f, 19.1783f, 313.3156f, 161.7061f, 377.0863f, 52.1937f, 483.5222f, 164.7224f, 499.4650f,
	-18.1881f, 147.1016f, 113.3757f, 264.7419f, -10.3830f, 130.9681f, 10.9511f, 272.3863f, 191.6208f, 459.5145f, 240.3248f, 463.8325f,
	356.6797f, 77.6355f, 412.5629f, 168.2401f, 326.2139f, 307.5013f, 407.2526f, 422.3140f, -6.5422f, 355.5684f, 38.6912f, 399.0047f,
	279.9745f, -10.2789f, 290.0085f, 108.0669f, 49.1601f, 186.5052f, 105.1230f, 281.7262f, 451.0742f, 30.5586f, 490.0021f, 170.0038f,
	54.4314f, 19.1028f, 112.9336f, 166.2725f, 298.1461f, 228.2593f, 328.4931f, 235.5688f, 143.1079f, 111.0670f, 183.1305f, 178.3627f,
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---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 800 to 866 in c2ddb73

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	0.3281f, 0.8216f, 0.6919f, 0.5592f, 0.0010f, 0.0351f, 0.9909f, 0.7823f, 0.9376f, 0.9023f, 0.0204f, 0.7918f,
	0.4511f, 0.7896f, 0.0067f, 0.2882f, 0.7513f, 0.7930f, 0.6197f, 0.3013f, 0.3104f, 0.9668f, 0.4392f, 0.4471f,
	0.5523f, 0.4095f, 0.5527f, 0.4323f, 0.8267f, 0.9091f, 0.9321f, 0.5643f, 0.4421f, 0.7052f, 0.8383f, 0.5630f,
	0.7000f, 0.7497f, 0.6764f, 0.7461f, 0.2086f, 0.4984f, 0.5883f, 0.0025f, 0.8560f, 0.6100f, 0.1291f, 0.8164f,
	0.7171f, 0.7583f, 0.3920f, 0.8542f, 0.4140f, 0.5705f, 0.0006f, 0.6449f, 0.7182f, 0.5671f, 0.4966f, 0.8099f,
	0.6814f, 0.2781f, 0.9591f, 0.7073f, 0.9879f, 0.9713f, 0.9189f, 0.7554f, 0.6094f, 0.1722f, 0.5434f, 0.7654f,
	0.5209f, 0.8682f, 0.1097f, 0.3809f, 0.5060f, 0.4323f, 0.1086f, 0.1535f, 0.8376f, 0.4844f, 0.0487f, 0.0165f,
	0.4735f, 0.1644f, 0.7051f, 0.7953f, 0.2283f, 0.5922f, 0.1544f, 0.3036f, 0.8888f, 0.5441f, 0.8859f, 0.2252f,
	0.3300f, 0.4710f, 0.4801f, 0.9976f, 0.1144f, 0.8520f, 0.8637f, 0.5532f, 0.3440f, 0.5192f, 0.2925f, 0.7991f,
	0.4983f, 0.9258f, 0.6227f, 0.5143f, 0.7111f, 0.5039f, 0.9045f, 0.1844f, 0.9733f, 0.8122f, 0.8607f, 0.4829f,
	0.8372f, 0.3068f, 0.7619f, 0.1405f, 0.3071f, 0.4457f, 0.3223f, 0.3870f, 0.8201f, 0.2567f, 0.7453f, 0.0737f,
	0.7657f, 0.7920f, 0.4017f, 0.7225f, 0.9151f, 0.8007f, 0.3904f, 0.4842f, 0.7794f, 0.2926f, 0.8039f, 0.3281f,
	0.8060f, 0.0868f, 0.0444f, 0.9977f, 0.8695f, 0.8828f, 0.9513f, 0.4383f, 0.2868f, 0.1300f, 0.5012f, 0.2200f,
	0.9356f, 0.0040f, 0.1432f, 0.2465f, 0.1990f, 0.2258f, 0.6560f, 0.3275f, 0.6150f, 0.8903f, 0.6026f, 0.6945f,
	0.3655f, 0.1597f, 0.3206f, 0.9643f, 0.6218f, 0.2775f, 0.4509f, 0.8355f, 0.6684f, 0.5607f, 0.8852f, 0.6724f,
	0.6427f, 0.1898f, 0.1064f, 0.9651f, 0.5989f, 0.4157f, 0.5890f, 0.0618f, 0.8221f, 0.2166f, 0.8045f, 0.5344f,
	0.2766f, 0.0302f, 0.8158f, 0.1765f, 0.0518f, 0.7559f, 0.3500f, 0.3893f, 0.2471f, 0.8592f, 0.2973f, 0.2102f,
	0.3092f, 0.2031f, 0.3177f, 0.0829f, 0.1585f, 0.4171f, 0.8795f, 0.0573f, 0.2127f, 0.9083f, 0.8900f, 0.6795f,
	0.2405f, 0.4198f, 0.2112f, 0.1286f, 0.3800f, 0.5758f, 0.3599f, 0.6108f, 0.2963f, 0.3459f, 0.7907f, 0.8783f,
	0.3220f, 0.5715f, 0.2782f, 0.0533f, 0.7379f, 0.1710f, 0.4257f, 0.4870f, 0.1845f, 0.0946f, 0.3480f, 0.9523f,
	0.6151f, 0.3814f, 0.0389f, 0.6003f, 0.0923f, 0.5425f, 0.7520f, 0.4236f, 0.2994f, 0.0474f, 0.0248f, 0.4300f,
	0.8833f, 0.2441f, 0.5741f, 0.6843f, 0.0608f, 0.1531f, 0.3313f, 0.6701f, 0.4390f, 0.7342f, 0.8676f, 0.7584f,
	0.9922f, 0.7544f, 0.8522f, 0.8324f, 0.7303f, 0.8018f, 0.9347f, 0.4752f, 0.6383f, 0.5149f, 0.8510f, 0.4314f,
	0.8197f, 0.7994f, 0.9619f, 0.2489f, 0.7096f, 0.7569f, 0.9363f, 0.9069f, 0.5735f, 0.5792f, 0.1673f, 0.9750f,
	0.2550f, 0.7247f, 0.7958f, 0.4412f, 0.2112f, 0.1890f, 0.8565f, 0.5108f, 0.0901f, 0.7170f, 0.2502f, 0.8764f,
	0.3096f, 0.2003f, 0.0849f, 0.5115f, 0.4507f, 0.7513f, 0.4646f, 0.3438f, 0.2617f, 0.2781f, 0.9278f, 0.1651f,
	0.9882f, 0.3269f, 0.0884f, 0.2487f, 0.0584f, 0.7900f, 0.5126f, 0.3370f, 0.6620f, 0.6306f, 0.9399f, 0.9613f,
	0.6807f, 0.8178f, 0.7924f, 0.4913f, 0.7045f, 0.0783f, 0.7580f, 0.9618f, 0.0850f, 0.8361f, 0.9330f, 0.2262f,
	0.5248f, 0.9279f, 0.9602f, 0.1279f, 0.3490f, 0.6981f, 0.2216f, 0.3248f, 0.0233f, 0.1535f, 0.5623f, 0.6531f,
	0.6489f, 0.7784f, 0.4153f, 0.2735f, 0.0156f, 0.2066f, 0.3124f, 0.1782f, 0.0201f, 0.1574f, 0.6661f, 0.6296f,
	0.9357f, 0.7982f, 0.5678f, 0.1376f, 0.5641f, 0.0616f, 0.4309f, 0.3903f, 0.4278f, 0.2798f, 0.6858f, 0.8409f,
	0.7685f, 0.6278f, 0.5383f, 0.0311f, 0.7229f, 0.5450f, 0.2707f, 0.3278f, 0.9356f, 0.6244f, 0.4759f, 0.6209f,
	0.4137f, 0.4702f, 0.2903f, 0.4399f, 0.6856f, 0.0399f, 0.7950f, 0.2830f, 0.6826f, 0.6427f, 0.6526f, 0.6081f,
	0.9591f, 0.5083f, 0.7323f, 0.7054f, 0.2363f, 0.2833f, 0.4240f, 0.2777f, 0.3667f, 0.3910f, 0.6039f, 0.2199f,
	0.8043f, 0.4375f, 0.7062f, 0.0814f, 0.4700f, 0.0282f, 0.6759f, 0.3437f, 0.9493f, 0.3241f, 0.5638f, 0.2574f,
	0.6201f, 0.4670f, 0.3706f, 0.2037f, 0.1115f, 0.1199f, 0.9990f, 0.4123f, 0.0019f, 0.9529f, 0.0200f, 0.4186f,
	0.7175f, 0.9146f, 0.7129f, 0.4636f, 0.9744f, 0.0393f, 0.9869f, 0.8494f, 0.9289f, 0.2548f, 0.1425f, 0.6633f,
	0.5159f, 0.5232f, 0.9246f, 0.6201f, 0.3111f, 0.4001f, 0.1335f, 0.1923f, 0.1434f, 0.8103f, 0.7049f, 0.5303f,
	0.3744f, 0.6685f, 0.8129f, 0.8812f, 0.5470f, 0.8199f, 0.5113f, 0.4745f, 0.8654f, 0.3864f, 0.3959f, 0.3049f,
	0.5187f, 0.5449f, 0.6605f, 0.4305f, 0.2178f, 0.8668f, 0.3460f, 0.9229f, 0.2074f, 0.5601f, 0.5366f, 0.8286f,
	0.1389f, 0.9099f, 0.5314f, 0.5861f, 0.5102f, 0.0360f, 0.4971f, 0.2635f, 0.3427f, 0.6491f, 0.4977f, 0.0932f,
	0.0730f, 0.1857f, 0.1909f, 0.6083f, 0.1778f, 0.8817f, 0.2098f, 0.0911f, 0.8757f, 0.2953f, 0.4254f, 0.9590f,
	0.9444f, 0.7149f, 0.0689f, 0.5933f, 0.9891f, 0.9469f, 0.1060f, 0.3960f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 874 in c2ddb73

std::vector<int64_t> gold = {0, 0, 143, 0, 0, 10, 0, 0, 13, 0, 0, 0, 0, 0, 90, 0, 0, 135, 0, 0, 1, 0, 0, 76, 0, 0, 108, 0, 0, 170, 0, 0, 140, 0, 0, 20, 0, 0, 151, 0, 0, 150, 0, 0, 39, 0, 0, 44, 0, 0, 41, 0, 0, 82, 0, 0, 80, 0, 0, 88, 0, 0, 16, 0, 0, 27, 0, 0, 167, 0, 0, 165, 0, 0, 181, 0, 1, 187, 0, 1, 94, 0, 1, 152, 0, 1, 72, 0, 1, 32, 0, 1, 153, 0, 1, 109, 0, 1, 150, 0, 1, 19, 0, 1, 27, 0, 1, 96, 0, 1, 35, 0, 1, 197, 0, 1, 68, 0, 1, 22, 0, 1, 154, 0, 1, 17, 0, 1, 117, 0, 1, 43, 0, 1, 97, 0, 1, 10, 0, 1, 180, 0, 1, 182, 0, 1, 67, 0, 1, 44, 1, 0, 35, 1, 0, 152, 1, 0, 175, 1, 0, 4, 1, 0, 71, 1, 0, 166, 1, 0, 127, 1, 0, 38, 1, 0, 170, 1, 0, 44, 1, 0, 158, 1, 0, 198, 1, 0, 24, 1, 0, 101, 1, 0, 171, 1, 0, 2, 1, 0, 53, 1, 0, 102, 1, 0, 66, 1, 0, 140, 1, 0, 37, 1, 0, 98, 1, 0, 115, 1, 0, 150, 1, 0, 6, 1, 1, 114, 1, 1, 196, 1, 1, 0, 1, 1, 126, 1, 1, 124, 1, 1, 19, 1, 1, 11, 1, 1, 26, 1, 1, 84, 1, 1, 191, 1, 1, 117, 1, 1, 104, 1, 1, 197, 1, 1, 192, 1, 1, 10, 1, 1, 48, 1, 1, 68, 1, 1, 22, 1, 1, 128, 1, 1, 25, 1, 1, 134, 1, 1, 163, 1, 1, 121, 1, 1, 169, 1, 1, 185};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 879 in c2ddb73

[github-actions]

Remaining comments which cannot be posted as a review comment to avoid GitHub Rate Limit

format.py

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 323 in b5c1e77

auto boxes_iter = my_sorted_boxes.begin_at(array<index_int, 3>{0, i, 0});

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 328 in b5c1e77

auto my_mask = slice_tensor(mask, array<index_int, 2>{block_idx, 0}, slice_axes<1>());

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Lines 333 to 334 in b5c1e77

	const float iou_thr_val = iou_thr_p[0];
	const float score_thr_val = score_thr_p[0];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Lines 340 to 347 in b5c1e77

	nms_filter_per_block<NumBoxes, NumClasses>(
	idx,
	block_nms_data,
	my_mask,
	max_output_boxes_per_class,
	score_thr_val,
	my_output,
	bc_counts);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 350 in b5c1e77

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Lines 362 to 365 in b5c1e77

	__device__ void nonmaxsuppression_compact(const Counts bc_counts,
	const Idx indices,
	Out output,
	Num num_selected)

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 369 in b5c1e77

static_assert(NumBatchClass <= 16000, "nms_compact: NumBatchClass exceeds the LDS budget for offsets[]");

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 374 in b5c1e77

// TODO: there's probably a better way to get the exclusive prefix sum rather than doing the minus each time.

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 387 in b5c1e77

num_selected[0] = offsets[NumBatchClass-1] + bc_counts[NumBatchClass-1];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 392 in b5c1e77

constexpr index_int index_size = 3;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 396 in b5c1e77

const index_int box_idx = i % NumBoxes;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp

Line 402 in b5c1e77

indices[(batch_class_idx * NumBoxes + box_idx) * index_size + k] ;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 62 in b5c1e77

const auto num_boxes = boxes_s.lens()[1];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 64 in b5c1e77

const auto aligned_b = static_cast<std::size_t>(bit_ceil(static_cast<std::uint32_t>(num_boxes)));

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 143 in b5c1e77

const auto num_boxes = boxes_s.lens()[1];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 145 in b5c1e77

const auto iou_packed = (num_boxes * (num_boxes - 1) / 2);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Lines 168 to 182 in b5c1e77

	auto sorted = m.insert_instruction(
	ins,
	make_op("gpu::nms_sort", {{"center_point_box", center_point_box}}),
	inputs[0],
	inputs[1]);
	auto filter = m.insert_instruction(
	ins,
	make_op("gpu::nms_filter",
	{{"num_batches", num_batches}, {"num_classes", num_classes}, {"num_boxes", num_boxes}}),
	sorted,
	inputs[2],
	inputs[3],
	inputs[4],
	mask_alloc);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 220 in b5c1e77

int64_t max_out_val = 4;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 299 to 302 in b5c1e77

	std::vector<float> boxes_vec = {0.5, 0.5, 1.0, 1.0, 0.5, 0.6, 1.0, 1.0, 0.5, 0.4, 1.0, 1.0,
	0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0,
	0.5, 0.5, 1.0, 1.0, 0.5, 0.6, 1.0, 1.0, 0.5, 0.4, 1.0, 1.0,
	0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 346 to 348 in b5c1e77

	std::vector<float> boxes_vec = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1,
	0.0, -0.1, 1.0, 0.9, 0.0, 10.0, 1.0, 11.0,
	0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 379 to 385 in b5c1e77

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 389 to 398 in b5c1e77

	32.7256f, 35.1377f, 43.0832f, 42.2579f, 13.9286f, 15.6152f, 21.5240f, 28.2727f, 44.0782f, 37.5280f, 52.9916f, 48.3318f,
	38.8011f, 32.1818f, 50.5110f, 37.5550f, 33.9761f, -1.6170f, 43.8622f, 11.0347f, 5.3569f, 42.6478f, 14.1070f, 54.9145f,
	18.9216f, 34.8446f, 27.7505f, 41.2693f, -0.4375f, 36.7849f, 4.8178f, 41.8215f, 6.9987f, 1.1282f, 8.4302f, 11.6832f,
	30.5954f, 21.0410f, 37.7095f, 23.9976f, 35.2360f, 16.6405f, 39.2402f, 20.4393f, 45.0158f, 45.7867f, 51.7352f, 46.8898f,
	9.8174f, 26.1848f, 22.7651f, 38.2017f, 16.3854f, 35.9841f, 20.6606f, 46.2920f, 22.5697f, 16.7346f, 24.3859f, 27.6069f,
	7.0039f, 5.3968f, 11.9433f, 17.3270f, 3.9409f, 24.0168f, 9.0512f, 31.4417f, 18.6518f, -1.2903f, 28.9187f, 7.6721f,
	6.9462f, 39.9030f, 15.7447f, 42.8601f, 27.5034f, 30.2815f, 39.4780f, 32.8849f};
	std::vector<float> scores_vec = {
	0.6979f, 0.4657f, 0.8326f, 0.2503f, 0.1204f, 0.1810f, 0.7501f, 0.5157f, 0.2451f, 0.5509f, 0.2371f, 0.7267f,
	0.5015f, 0.4429f, 0.3714f, 0.6673f, 0.4256f, 0.1789f, 0.2062f, 0.9657f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 406 in b5c1e77

std::vector<int64_t> gold = {0, 0, 19, 0, 0, 2, 0, 0, 6, 0, 0, 11, 0, 0, 0, 0, 0, 15, 0, 0, 9, 0, 0, 7, 0, 0, 12, 0, 0, 1};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 435 to 451 in b5c1e77

	90.8581f, 82.6292f, 23.5447f, 19.9060f, 69.9707f, 89.6161f, 29.1830f, 26.1572f, 26.5870f, 14.0249f, 15.5215f, 14.1630f,
	96.9176f, 55.4036f, 5.1730f, 8.1873f, 77.8751f, 10.8576f, 1.4042f, 7.8632f, 71.6890f, 67.2240f, 7.6600f, 22.6344f,
	44.9361f, 28.1234f, 4.8228f, 24.6805f, 27.2242f, 65.9423f, 20.6521f, 4.0531f, 9.6391f, 72.6995f, 4.5331f, 2.9302f,
	90.2602f, 76.8647f, 15.6836f, 18.2386f, 45.5776f, 10.7741f, 21.1336f, 5.2390f, 20.2363f, 91.6012f, 17.8524f, 24.9153f,
	30.5957f, 23.0214f, 6.7935f, 9.9997f, 57.9220f, 3.7413f, 24.3196f, 5.1723f, 17.6773f, 55.4852f, 21.7468f, 27.7081f,
	85.6614f, 37.0922f, 22.4305f, 5.8004f, 75.8520f, 82.9790f, 4.8007f, 9.2569f, 71.9463f, 80.8251f, 4.5889f, 5.4548f,
	43.2093f, 31.7139f, 27.8993f, 4.3492f, 62.7309f, 95.2899f, 12.5298f, 1.6133f, 58.4098f, 29.0918f, 9.7275f, 2.6065f,
	64.9847f, 51.5057f, 15.1689f, 6.0646f, 8.4444f, 25.5965f, 20.2231f, 2.5481f, 41.5807f, 93.6044f, 28.7131f, 18.1432f,
	4.1614f, 16.4608f, 9.3069f, 20.7407f, 49.3991f, 4.4911f, 27.8194f, 12.4153f, 32.9861f, 43.5097f, 1.7209f, 10.2217f,
	14.4524f, 99.2376f, 17.1007f, 15.6313f, 10.3403f, 89.1677f, 19.3853f, 26.3751f, 58.7645f, 74.8608f, 4.0710f, 25.6828f,
	17.0593f, 89.0792f, 5.0698f, 2.2608f, 92.5120f, 89.3447f, 13.1543f, 6.2635f, 58.1061f, 51.8858f, 29.0207f, 7.8656f,
	34.6870f, 31.5929f, 18.2852f, 8.2322f, 59.0915f, 77.2012f, 28.0577f, 17.5657f, 2.2804f, 66.1661f, 24.3265f, 13.0716f,
	95.8559f, 37.3658f, 14.5541f, 2.4284f, 48.2303f, 9.4467f, 23.7581f, 11.8348f, 78.2735f, 74.6790f, 1.5173f, 16.1888f,
	8.2730f, 26.2461f, 4.1652f, 3.9485f, 48.6658f, 93.6813f, 25.0534f, 25.1703f, 49.0707f, 24.0971f, 24.1077f, 2.5069f,
	93.7826f, 12.2758f, 7.7466f, 27.8204f, 57.1728f, 83.1113f, 16.3923f, 3.8743f, 47.3489f, 15.3284f, 18.5745f, 25.4637f,
	26.6976f, 17.9268f, 26.1644f, 27.1769f, 33.1569f, 59.9383f, 18.4901f, 29.4075f, 52.0672f, 87.4562f, 12.9646f, 24.2588f,
	43.8911f, 19.6435f, 11.8513f, 23.6048f, 2.1612f, 31.0324f, 13.3506f, 19.6320f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 453 to 457 in b5c1e77

	0.8011f, 0.2211f, 0.5825f, 0.5628f, 0.8718f, 0.5165f, 0.4466f, 0.6756f, 0.3398f, 0.2258f, 0.5301f, 0.4752f,
	0.3093f, 0.4308f, 0.4298f, 0.3947f, 0.4415f, 0.7172f, 0.3672f, 0.9540f, 0.9247f, 0.5328f, 0.3955f, 0.5819f,
	0.8637f, 0.6873f, 0.8240f, 0.5795f, 0.6696f, 0.3593f, 0.7614f, 0.2822f, 0.7253f, 0.8746f, 0.2189f, 0.6529f,
	0.1856f, 0.7531f, 0.1760f, 0.9423f, 0.2237f, 0.9630f, 0.8208f, 0.6343f, 0.8044f, 0.8156f, 0.9514f, 0.3280f,
	0.6311f, 0.1855f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 465 in b5c1e77

std::vector<int64_t> gold = {0, 0, 41, 0, 0, 19, 0, 0, 46, 0, 0, 39, 0, 0, 20, 0, 0, 33, 0, 0, 4, 0, 0, 24, 0, 0, 26, 0, 0, 42, 0, 0, 45, 0, 0, 44, 0, 0, 0, 0, 0, 30, 0, 0, 32, 0, 0, 17, 0, 0, 25, 0, 0, 7, 0, 0, 28, 0, 0, 35};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 484 to 490 in b5c1e77

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 494 to 560 in b5c1e77

	-3.8699f, 108.8880f, 20.8101f, 137.5783f, 149.9079f, 29.3134f, 203.7504f, 39.2031f, 121.6031f, 107.1528f, 162.2282f, 118.8275f,
	27.1146f, 87.2265f, 42.1365f, 141.7457f, -7.3128f, 91.3799f, 44.0012f, 95.0142f, 25.9397f, 97.1572f, 47.4736f, 111.8955f,
	170.3318f, 143.6689f, 221.6791f, 161.9004f, 82.3933f, 144.8881f, 101.0310f, 174.8098f, 138.9017f, 80.6305f, 174.7306f, 116.2308f,
	115.0719f, 104.8666f, 139.4914f, 134.9707f, 105.8753f, 183.2658f, 123.0900f, 189.2287f, 2.3726f, 16.2585f, 55.6795f, 31.6349f,
	183.1709f, -1.9651f, 195.2389f, 48.8066f, 57.2666f, -1.7671f, 63.2705f, 36.8507f, 105.0166f, 111.9228f, 126.1903f, 151.2225f,
	118.2848f, 63.4507f, 161.6255f, 103.9927f, 105.5274f, 131.8586f, 154.1659f, 177.8699f, 158.1560f, 132.0321f, 218.0818f, 136.4605f,
	20.4451f, 55.4126f, 38.9305f, 78.0425f, 89.1363f, 163.2572f, 114.2048f, 196.0894f, 76.2707f, 142.0220f, 85.3431f, 162.9909f,
	77.3750f, 28.6949f, 112.2925f, 79.5191f, -6.0851f, 58.1025f, 53.7721f, 87.5743f, 5.6429f, 39.7135f, 47.9949f, 86.0625f,
	37.5563f, 5.8879f, 73.6739f, 57.1568f, 48.8660f, 14.1653f, 73.0158f, 44.9480f, 58.0793f, 159.8937f, 113.0820f, 214.5573f,
	107.0385f, 69.7607f, 137.3566f, 105.4010f, 122.4620f, 51.0809f, 131.3896f, 102.2471f, 71.0835f, 135.3897f, 93.6408f, 156.4846f,
	79.2752f, 95.3835f, 84.2380f, 125.8137f, 37.0673f, 171.0514f, 49.9841f, 203.4046f, 116.6400f, 152.4634f, 118.6825f, 159.6572f,
	49.5364f, 83.6166f, 77.2799f, 108.1312f, -12.0070f, 47.7104f, 26.4309f, 102.8334f, 73.0529f, 178.2168f, 94.3071f, 216.4359f,
	81.9253f, 137.8156f, 107.7278f, 149.2885f, 16.3219f, 179.7427f, 73.9152f, 200.7352f, 91.8087f, 17.5434f, 137.1745f, 29.8480f,
	96.6991f, 168.8745f, 129.6096f, 171.3390f, 131.5065f, 99.5547f, 149.2944f, 155.2749f, 102.6283f, 10.6622f, 156.5511f, 38.1065f,
	123.0512f, 108.0793f, 137.9220f, 127.2239f, 53.1452f, 119.0642f, 73.3404f, 155.3743f, 130.1690f, 1.7448f, 184.8039f, 3.1763f,
	93.7074f, 82.1619f, 125.9504f, 99.5652f, 63.8853f, 143.8404f, 108.6820f, 186.3194f, 107.2755f, 39.8756f, 143.1295f, 78.2680f,
	52.3550f, 62.2463f, 91.9079f, 121.1729f, 93.2160f, 69.6623f, 111.8797f, 107.2634f, 139.7207f, 45.7991f, 154.9616f, 74.9719f,
	167.2671f, 160.7261f, 187.2941f, 206.6506f, 179.1259f, 129.1106f, 189.2970f, 183.4070f, 74.4343f, 0.3572f, 127.0189f, 43.8782f,
	95.1992f, 170.4922f, 112.9108f, 228.3217f, 142.9101f, 152.2709f, 177.0380f, 199.4092f, 39.0269f, 30.7110f, 86.7534f, 82.8523f,
	143.8537f, 163.5132f, 191.0993f, 171.2454f, 85.3959f, -0.8223f, 112.2607f, 43.3901f, 8.6218f, 186.3383f, 37.7209f, 213.3036f,
	-15.4319f, 116.3204f, 44.2555f, 149.9535f, 147.9980f, 110.2290f, 188.7993f, 149.8210f, -13.4183f, -11.0214f, 35.6454f, 47.1977f,
	28.9969f, 149.8616f, 83.2476f, 208.9517f, 43.0921f, -3.2028f, 90.5599f, 14.8026f, 28.6361f, 26.0199f, 40.5617f, 70.3113f,
	45.6946f, 5.9799f, 79.8627f, 51.2289f, 145.0326f, 144.6320f, 152.0444f, 166.0751f, -16.8246f, 35.4867f, 22.6978f, 43.7950f,
	136.7519f, 180.4197f, 194.1175f, 183.8356f, 155.6840f, 107.8222f, 186.9352f, 154.6854f, 61.1796f, -7.7136f, 87.7250f, 22.1787f,
	29.1652f, -28.4875f, 32.2799f, 30.6594f, 91.3547f, -3.8851f, 148.9814f, 24.5483f, 20.3959f, 91.8365f, 27.4731f, 150.5336f,
	71.2720f, 147.6549f, 74.6957f, 172.9379f, 183.9269f, 23.7969f, 199.4448f, 71.6242f, 196.6597f, 166.8796f, 201.5260f, 172.8839f,
	140.4950f, -5.4397f, 168.3470f, 28.3325f, 46.4677f, 136.0320f, 77.9169f, 184.3535f, 127.8122f, 157.7804f, 147.2538f, 213.3378f,
	139.0779f, 129.6555f, 143.0846f, 179.1879f, 73.7761f, 138.0335f, 81.3605f, 141.2148f, 116.3348f, 156.1013f, 140.0206f, 179.0908f,
	-0.1401f, 6.0937f, 4.4311f, 9.9669f, 20.7149f, 36.6326f, 62.9081f, 44.0802f, 98.4106f, 4.5632f, 111.6248f, 45.4062f,
	23.3391f, 79.3651f, 42.1614f, 122.4473f, 21.0547f, 125.7129f, 45.3081f, 172.3624f, 154.4709f, 99.9714f, 180.0508f, 152.0333f,
	197.2776f, 147.9130f, 198.3756f, 192.5394f, 107.3878f, 6.9169f, 115.0000f, 55.1683f, 141.8624f, 144.9798f, 193.7655f, 148.8687f,
	197.5280f, 31.1895f, 198.6007f, 46.0271f, 12.8282f, 35.3058f, 43.8101f, 72.9977f, 74.7088f, 116.1662f, 104.5894f, 167.7956f,
	68.1883f, 195.4082f, 88.8408f, 196.6737f, 2.7857f, 106.6272f, 29.2340f, 137.9903f, 127.5389f, -9.5799f, 174.5932f, 31.3800f,
	61.4403f, 121.8884f, 112.0713f, 124.6352f, 15.4868f, 35.9096f, 55.8899f, 68.2298f, 35.5922f, 56.6701f, 44.2246f, 72.3261f,
	163.1796f, 40.7751f, 180.4136f, 56.2181f, 177.9262f, 90.7157f, 187.1069f, 101.2297f, 33.5656f, 108.4211f, 51.2933f, 164.8822f,
	73.5555f, 18.9549f, 114.3649f, 72.3462f, 119.3443f, 42.7151f, 174.0536f, 89.5792f, 169.1987f, 170.3059f, 182.1476f, 201.8479f,
	59.3192f, -5.2591f, 92.3019f, 24.6868f, 82.2129f, 76.0264f, 124.5949f, 108.2814f, 119.7321f, 125.9828f, 176.9545f, 158.6404f,
	127.7304f, 16.7712f, 164.7240f, 43.4104f, 148.5664f, 5.0880f, 164.6177f, 13.8616f, 95.0352f, 23.4340f, 132.9384f, 31.8482f,
	10.9685f, 155.1733f, 30.8775f, 212.3560f, 151.4989f, -12.8680f, 210.0904f, 16.5719f, 160.8241f, 9.0448f, 185.4050f, 66.2840f,
	138.8994f, 0.9312f, 180.3396f, 11.5822f, 18.7873f, 5.2706f, 21.1577f, 38.9812f, 28.5777f, 117.4022f, 53.1813f, 130.6575f,
	122.4044f, 40.3588f, 175.0358f, 56.2967f, -13.8737f, 112.4558f, 23.1297f, 115.2290f, 182.2486f, 114.0300f, 209.4412f, 122.0482f,
	47.3188f, 142.3400f, 103.5391f, 197.4341f, 118.1700f, -9.0369f, 169.5550f, 10.9335f, 167.5089f, 152.2341f, 187.5196f, 189.1137f,
	62.3618f, 109.6059f, 95.4902f, 138.0417f, 48.8767f, 20.2354f, 78.7763f, 44.8620f, 102.5983f, 138.3968f, 140.8982f, 170.7781f,
	105.8416f, 165.0748f, 126.5542f, 177.1219f, 74.1239f, 21.1889f, 89.5320f, 80.5165f, 92.9311f, 159.1187f, 147.7788f, 208.3988f,
	159.3220f, 68.5139f, 214.8306f, 113.2691f, 68.1500f, 106.3565f, 118.9061f, 135.0133f, 9.9914f, 191.9200f, 68.7055f, 201.9398f,
	52.9639f, 44.6476f, 97.9184f, 99.9669f, 55.7637f, 152.0609f, 101.8791f, 173.2028f, 3.2253f, 61.7017f, 49.2181f, 65.6580f,
	17.8964f, 149.2418f, 47.2522f, 170.4436f, 122.9471f, 96.2103f, 150.8778f, 144.0833f, 60.3089f, 24.4012f, 75.4822f, 62.1410f,
	171.4575f, 60.1555f, 210.5018f, 105.4550f, 39.6844f, 39.6149f, 57.7543f, 87.4394f, 11.6796f, 8.8690f, 27.8902f, 22.3743f,
	132.9151f, -21.7847f, 168.4868f, 33.7186f, 163.6127f, 55.8750f, 188.8017f, 82.7164f, 48.6664f, -15.5441f, 62.5789f, 23.1577f,
	15.8440f, 32.5294f, 64.9913f, 33.6657f, 11.2664f, 115.2323f, 63.0400f, 174.8410f, 98.9553f, 132.8318f, 109.8496f, 150.4047f,
	92.9619f, 145.3852f, 94.4048f, 150.0469f, 41.4721f, 49.4119f, 62.3038f, 77.4494f, -14.9919f, 173.6975f, 33.0612f, 182.3103f,
	71.0426f, 113.7725f, 121.5539f, 123.7598f, 187.2858f, 6.0529f, 196.4472f, 44.3576f, 107.1609f, 16.6524f, 153.8468f, 40.8351f,
	95.1880f, 110.9244f, 103.0146f, 166.3137f, 10.1316f, 24.6737f, 34.1453f, 44.5039f, 20.5283f, 79.5362f, 80.4462f, 123.3809f,
	52.7734f, 184.2525f, 65.1362f, 212.4573f, 147.9188f, -19.1670f, 158.0026f, 20.7701f, 162.3696f, -14.8751f, 188.3148f, 21.5070f,
	161.5482f, 184.1698f, 199.1086f, 213.0640f, 168.8931f, 88.4010f, 224.9343f, 145.4546f, 167.0391f, 14.7719f, 225.9076f, 35.9920f,
	188.0454f, 173.7320f, 193.1542f, 185.1889f, 9.7935f, 155.5723f, 18.9354f, 196.5798f, 3.7319f, 81.7829f, 51.3855f, 132.6973f,
	52.4097f, 122.6709f, 69.3770f, 126.0459f, 83.9766f, 40.8733f, 137.1827f, 68.4016f, -0.6763f, -16.7244f, 39.4674f, 36.9323f,
	165.3600f, 96.2998f, 172.9588f, 141.5273f, 98.2916f, 29.1927f, 148.4108f, 88.7094f, 102.7704f, 116.5475f, 114.1754f, 148.9009f,
	20.0692f, 147.2792f, 46.0554f, 187.2189f, 33.8616f, -5.7911f, 67.4406f, 13.0553f, 16.7898f, 90.6905f, 47.3350f, 147.5951f,
	149.6448f, 34.9492f, 191.1284f, 57.5630f, 97.0913f, 152.4916f, 136.5998f, 197.0638f, 117.2606f, 38.3403f, 176.7911f, 63.1255f,
	29.2236f, 105.0804f, 89.1895f, 139.2277f, 58.5150f, 88.9746f, 89.9861f, 132.4418f, 77.6626f, 63.7197f, 84.2794f, 94.7469f,
	130.0316f, 108.2651f, 173.9744f, 162.7832f, 125.1590f, 132.2845f, 183.7822f, 158.0233f, 31.4721f, 93.7989f, 51.2533f, 132.9762f,
	174.2021f, 141.0848f, 202.4134f, 162.2841f, 11.1001f, 184.1428f, 37.1620f, 209.2240f, 177.2076f, 70.3730f, 181.2413f, 97.3360f,
	-0.2527f, 98.7053f, 40.4109f, 107.1279f, 41.9845f, -0.7119f, 63.8314f, 5.6998f, 145.5655f, 139.0148f, 193.0259f, 179.3967f,
	10.8509f, 84.2082f, 60.9460f, 123.8838f, 57.9873f, 61.5364f, 107.4399f, 101.6481f, 77.1802f, 17.7313f, 102.7635f, 19.8975f,
	39.0662f, 167.7982f, 59.0374f, 188.0644f, 119.4588f, 72.6661f, 164.6393f, 85.3368f, 146.1259f, 113.0609f, 194.4079f, 159.9718f,
	159.9229f, 3.9862f, 189.9071f, 55.7634f, 41.0200f, 184.5329f, 94.7088f, 200.0870f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 562 to 578 in b5c1e77

	0.1439f, 0.8791f, 0.0961f, 0.1535f, 0.5338f, 0.0675f, 0.0528f, 0.0005f, 0.4363f, 0.7746f, 0.0348f, 0.6523f,
	0.8231f, 0.1680f, 0.1469f, 0.8608f, 0.8231f, 0.5389f, 0.8192f, 0.0928f, 0.3945f, 0.7378f, 0.2575f, 0.7523f,
	0.5042f, 0.7503f, 0.4647f, 0.3679f, 0.2192f, 0.2084f, 0.7515f, 0.1189f, 0.0860f, 0.1763f, 0.1753f, 0.8231f,
	0.3985f, 0.9904f, 0.1372f, 0.6535f, 0.4487f, 0.3929f, 0.8751f, 0.9756f, 0.8729f, 0.1923f, 0.2208f, 0.6561f,
	0.2891f, 0.7347f, 0.5664f, 0.5509f, 0.8285f, 0.7105f, 0.0266f, 0.0495f, 0.6016f, 0.4862f, 0.2602f, 0.4187f,
	0.7579f, 0.8266f, 0.5612f, 0.3854f, 0.2707f, 0.5219f, 0.3147f, 0.5641f, 0.6767f, 0.0661f, 0.0011f, 0.2123f,
	0.8945f, 0.6463f, 0.1720f, 0.8903f, 0.4700f, 0.4761f, 0.9355f, 0.0595f, 0.2152f, 0.5858f, 0.1955f, 0.6795f,
	0.2141f, 0.0992f, 0.2070f, 0.4227f, 0.1761f, 0.1347f, 0.8603f, 0.3204f, 0.3608f, 0.0553f, 0.3574f, 0.2648f,
	0.6105f, 0.2054f, 0.8884f, 0.9297f, 0.0998f, 0.1074f, 0.1153f, 0.6196f, 0.1220f, 0.8524f, 0.7543f, 0.8198f,
	0.5261f, 0.9967f, 0.0442f, 0.4013f, 0.3239f, 0.9486f, 0.5769f, 0.8062f, 0.1703f, 0.9786f, 0.4986f, 0.4937f,
	0.9709f, 0.3807f, 0.3975f, 0.5848f, 0.1281f, 0.3211f, 0.1932f, 0.1033f, 0.8661f, 0.5893f, 0.3587f, 0.4087f,
	0.4315f, 0.6331f, 0.9268f, 0.9328f, 0.3915f, 0.3293f, 0.4510f, 0.5679f, 0.4618f, 0.6588f, 0.5544f, 0.3207f,
	0.3457f, 0.3786f, 0.0946f, 0.1661f, 0.7231f, 0.3891f, 0.2145f, 0.5627f, 0.7555f, 0.2574f, 0.8268f, 0.9275f,
	0.5974f, 0.6689f, 0.0526f, 0.9455f, 0.3925f, 0.9239f, 0.5790f, 0.0046f, 0.0385f, 0.6804f, 0.5627f, 0.0265f,
	0.7435f, 0.8521f, 0.4964f, 0.4658f, 0.0055f, 0.7866f, 0.3307f, 0.8788f, 0.3731f, 0.5651f, 0.2703f, 0.1606f,
	0.7749f, 0.4966f, 0.5365f, 0.9654f, 0.9636f, 0.8556f, 0.1876f, 0.5943f, 0.8781f, 0.3745f, 0.1011f, 0.8110f,
	0.4818f, 0.5644f, 0.9821f, 0.6072f, 0.4250f, 0.3700f, 0.4176f, 0.1184f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 586 in b5c1e77

std::vector<int64_t> gold = {0, 0, 37, 0, 0, 43, 0, 0, 78, 0, 0, 99, 0, 0, 72, 0, 0, 75, 0, 0, 98, 0, 0, 1, 0, 0, 42, 0, 0, 44, 0, 0, 15, 0, 0, 90, 0, 0, 52, 0, 0, 61, 0, 0, 12, 1, 0, 9, 1, 0, 94, 1, 0, 17, 1, 0, 20, 1, 0, 83, 1, 0, 84, 1, 0, 13, 1, 0, 59, 1, 0, 35, 1, 0, 55, 1, 0, 34, 1, 0, 61, 1, 0, 75, 1, 0, 88, 1, 0, 28};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 605 to 611 in b5c1e77

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 615 to 624 in b5c1e77

	31.2680f, 53.5348f, 37.7043f, 73.6253f, 1.8071f, 55.2945f, 3.9368f, 78.7402f, 40.5016f, 12.5670f, 45.0345f, 32.9366f,
	78.2552f, 12.9548f, 80.7117f, 35.6526f, 73.9527f, 67.9870f, 79.4405f, 71.9065f, -3.8066f, -7.7339f, 10.2705f, 11.5692f,
	45.4706f, 34.8613f, 67.4569f, 48.4119f, 17.4632f, 30.3439f, 30.8192f, 43.8443f, 64.5403f, 44.3725f, 79.9380f, 66.0477f,
	0.7877f, 1.3956f, 6.4307f, 24.7471f, 65.1632f, 44.8608f, 84.5766f, 62.0721f, 59.3935f, 24.0849f, 74.6026f, 36.1925f,
	-1.0372f, 43.7485f, 19.8379f, 55.2458f, -6.6257f, -1.7353f, 16.1976f, 8.1505f, 62.2758f, 32.2798f, 71.2775f, 41.5966f,
	10.9190f, 36.7777f, 14.0023f, 46.7824f, 39.6937f, 15.6139f, 45.8900f, 18.6783f, 67.7244f, 9.7794f, 78.7948f, 12.5604f,
	34.0204f, 5.6094f, 56.7713f, 24.5464f, 26.9281f, 21.9014f, 36.6292f, 33.1611f, 26.2374f, -3.4581f, 44.9652f, 18.9477f,
	-1.6661f, 68.2450f, 11.7649f, 83.3261f, 74.8979f, 31.4950f, 80.1025f, 33.3041f, 20.6639f, 62.4061f, 29.0408f, 67.0291f,
	7.1374f, 75.0864f, 23.1608f, 80.8203f, 14.6460f, -5.2621f, 31.1216f, 18.1798f, 71.6501f, 49.1185f, 82.6496f, 55.1487f,
	4.4135f, 63.2815f, 10.6723f, 76.1439f, 60.5823f, 39.4727f, 78.1862f, 62.0048f, 54.1855f, 22.5844f, 59.0696f, 46.0598f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 626 to 633 in b5c1e77

	0.9367f, 0.1879f, 0.1073f, 0.4976f, 0.5195f, 0.5082f, 0.4367f, 0.9948f, 0.4863f, 0.4779f, 0.4218f, 0.0668f,
	0.5930f, 0.2280f, 0.6376f, 0.0508f, 0.9814f, 0.4690f, 0.8968f, 0.4756f, 0.0603f, 0.8222f, 0.6482f, 0.7818f,
	0.4282f, 0.6379f, 0.8562f, 0.6311f, 0.3477f, 0.6625f, 0.6719f, 0.9606f, 0.3709f, 0.4251f, 0.8121f, 0.5058f,
	0.7366f, 0.4597f, 0.2155f, 0.7452f, 0.1312f, 0.1986f, 0.6268f, 0.7473f, 0.8947f, 0.2726f, 0.1107f, 0.9560f,
	0.1544f, 0.1977f, 0.2913f, 0.5294f, 0.8828f, 0.7605f, 0.7082f, 0.1752f, 0.3577f, 0.4784f, 0.1474f, 0.2734f,
	0.3083f, 0.1273f, 0.5502f, 0.7050f, 0.0699f, 0.4811f, 0.7822f, 0.7480f, 0.8151f, 0.4482f, 0.8206f, 0.2408f,
	0.3608f, 0.1764f, 0.4675f, 0.3921f, 0.2409f, 0.7518f, 0.3138f, 0.2728f, 0.1309f, 0.4388f, 0.3030f, 0.3693f,
	0.2360f, 0.7632f, 0.9300f, 0.4979f, 0.6430f, 0.8672f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 641 in b5c1e77

std::vector<int64_t> gold = {0, 0, 7, 0, 0, 16, 0, 0, 0, 0, 0, 18, 0, 0, 26, 0, 1, 1, 0, 1, 17, 0, 1, 14, 0, 1, 22, 0, 1, 4, 0, 2, 26, 0, 2, 29, 0, 2, 10, 0, 2, 6, 0, 2, 25};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 660 to 666 in b5c1e77

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 670 to 803 in b5c1e77

	132.1894f, 453.1169f, 199.9736f, 545.7127f, 64.3090f, 275.1729f, 104.8258f, 338.3436f, 76.1273f, 401.7875f, 135.6448f, 487.9920f,
	12.8305f, 442.3624f, 77.1708f, 466.2458f, -5.9609f, 340.1129f, 126.0715f, 451.3386f, 15.0119f, 224.3769f, 56.2927f, 236.5545f,
	427.8277f, -14.2917f, 561.9954f, 95.4457f, 4.7940f, -55.8461f, 69.2637f, 71.6517f, 41.3494f, 202.9014f, 91.1927f, 274.2992f,
	375.6902f, 208.6749f, 451.5645f, 285.6396f, 258.4982f, 179.9212f, 321.7420f, 227.4412f, 367.5344f, 211.3590f, 406.8828f, 356.8083f,
	277.5064f, 220.9636f, 353.4056f, 331.1991f, 429.2783f, 390.3169f, 452.8968f, 446.2962f, 292.5150f, 40.8054f, 345.9525f, 67.8517f,
	218.4112f, 95.7302f, 303.7139f, 129.4475f, 325.0759f, 361.4403f, 387.6738f, 431.5647f, 161.8149f, 353.1971f, 285.5779f, 494.6398f,
	153.4061f, 442.2182f, 192.6577f, 552.6060f, 161.0782f, 419.9203f, 306.5742f, 452.9917f, 25.8953f, 380.4122f, 143.8188f, 509.4868f,
	325.7002f, 128.4980f, 470.8716f, 185.8499f, 67.4107f, 136.8775f, 193.2931f, 264.7841f, 65.6790f, 115.5359f, 87.8525f, 152.5492f,
	83.4548f, 256.5595f, 162.8974f, 349.7399f, 407.8717f, 399.8657f, 434.1985f, 538.9396f, 103.6427f, 152.6073f, 226.5586f, 192.0336f,
	299.0049f, 226.3779f, 387.0450f, 330.6239f, 408.0779f, 74.0950f, 448.3318f, 222.2046f, -30.8828f, 73.1804f, 108.6275f, 96.6196f,
	373.4308f, 90.5068f, 391.5936f, 104.6787f, 111.3250f, -21.7549f, 196.3405f, 79.7002f, 54.0937f, 448.8364f, 162.5287f, 500.4571f,
	339.5665f, 195.6321f, 349.3349f, 207.2475f, 409.8580f, 381.1502f, 499.9386f, 452.9707f, 86.2250f, 284.0088f, 208.7943f, 397.3206f,
	278.8861f, 74.2190f, 289.9477f, 117.7022f, 106.2550f, 62.2701f, 183.5792f, 113.1921f, 257.3803f, 342.4895f, 296.9053f, 469.4987f,
	261.0432f, 93.1105f, 360.8189f, 171.6012f, 295.8262f, 393.3591f, 314.5092f, 519.9261f, 241.4629f, 36.2717f, 382.0835f, 103.7837f,
	0.3826f, 267.3577f, 134.6972f, 410.3510f, 332.4151f, 358.2527f, 361.1253f, 456.2211f, 312.7919f, 108.4937f, 361.9585f, 126.7627f,
	297.0153f, 71.6643f, 385.5729f, 204.5431f, -16.9604f, 445.3092f, 91.0309f, 519.2097f, 189.9415f, 121.2467f, 256.8973f, 143.3509f,
	192.3739f, 203.1031f, 216.6613f, 226.8539f, 35.0965f, 164.5365f, 51.6150f, 267.9791f, 36.2014f, 122.4881f, 186.1665f, 130.5466f,
	186.0576f, 366.0443f, 254.9050f, 409.7468f, 305.9496f, 375.0105f, 436.9568f, 396.8388f, 82.0940f, 155.7987f, 154.9680f, 222.5193f,
	345.6593f, 386.1935f, 484.0906f, 448.9323f, 265.8611f, 67.1577f, 279.9372f, 145.9173f, 371.2164f, -19.1800f, 389.2053f, 23.4858f,
	166.5204f, 282.6964f, 306.0356f, 288.4709f, 178.5089f, 450.7671f, 320.6853f, 543.3107f, 285.9132f, -9.0198f, 333.8062f, 47.6641f,
	437.0255f, 54.9746f, 490.9451f, 153.0235f, 211.6987f, 250.8616f, 280.1138f, 268.0530f, 232.8247f, 403.4440f, 295.8328f, 406.4968f,
	286.3401f, 25.5231f, 315.6569f, 63.5189f, 301.3286f, 163.1046f, 436.1865f, 232.1301f, 16.5538f, 343.6795f, 55.2966f, 403.3963f,
	204.8009f, 124.9041f, 310.8865f, 246.6391f, 235.2927f, 65.7693f, 246.2989f, 123.0671f, 457.4555f, 57.7300f, 464.2295f, 137.7658f,
	197.5504f, 160.3075f, 295.9562f, 249.7413f, 208.4036f, 237.5821f, 259.9170f, 241.8350f, 431.7683f, 392.0298f, 530.4317f, 469.7846f,
	217.7836f, 294.9363f, 232.7928f, 347.3161f, 19.1783f, 313.3156f, 161.7061f, 377.0863f, 52.1937f, 483.5222f, 164.7224f, 499.4650f,
	-18.1881f, 147.1016f, 113.3757f, 264.7419f, -10.3830f, 130.9681f, 10.9511f, 272.3863f, 191.6208f, 459.5145f, 240.3248f, 463.8325f,
	356.6797f, 77.6355f, 412.5629f, 168.2401f, 326.2139f, 307.5013f, 407.2526f, 422.3140f, -6.5422f, 355.5684f, 38.6912f, 399.0047f,
	279.9745f, -10.2789f, 290.0085f, 108.0669f, 49.1601f, 186.5052f, 105.1230f, 281.7262f, 451.0742f, 30.5586f, 490.0021f, 170.0038f,
	54.4314f, 19.1028f, 112.9336f, 166.2725f, 298.1461f, 228.2593f, 328.4931f, 235.5688f, 143.1079f, 111.0670f, 183.1305f, 178.3627f,
	273.5727f, 356.7796f, 367.9886f, 439.2808f, 176.7118f, 442.3701f, 235.5468f, 465.2348f, 353.5905f, 375.8070f, 406.0526f, 426.9136f,
	75.0636f, 58.9357f, 155.6155f, 207.0952f, 394.8923f, 135.3580f, 510.8995f, 138.7764f, 221.3792f, 93.1523f, 278.8305f, 161.5760f,
	333.7764f, 4.2413f, 422.3168f, 130.7968f, 352.3830f, 447.2686f, 497.3472f, 496.5298f, 460.0268f, 164.7789f, 538.8018f, 237.2689f,
	43.6929f, 38.9803f, 180.2527f, 185.7092f, 83.8176f, 387.4572f, 203.0748f, 459.2138f, 120.3420f, 189.3440f, 130.0911f, 209.8513f,
	98.9678f, 13.2052f, 163.9035f, 21.9117f, 238.6976f, 10.0373f, 343.7471f, 151.9043f, 422.7512f, 299.3224f, 570.7713f, 339.9280f,
	460.4900f, 353.3999f, 529.7881f, 429.5054f, 255.9741f, 98.2099f, 270.7991f, 112.7245f, 277.1439f, 426.6355f, 361.8833f, 490.7601f,
	420.0563f, 355.7057f, 439.9143f, 495.2914f, 409.9785f, 386.2606f, 522.9550f, 462.1201f, 63.6084f, 40.9810f, 140.2522f, 186.6801f,
	209.8752f, 5.4847f, 318.6665f, 45.0513f, 351.1511f, 395.6231f, 481.6860f, 471.8004f, 104.2444f, 88.3651f, 198.9577f, 217.4352f,
	173.7778f, 275.5634f, 266.0312f, 343.3530f, 436.0951f, 358.6616f, 549.5261f, 401.3052f, 429.2604f, -0.0863f, 555.7863f, 128.3795f,
	387.8089f, 360.8724f, 518.2979f, 419.9659f, 396.0101f, 429.2169f, 402.4382f, 509.2946f, 92.6291f, 290.9362f, 176.5014f, 437.4388f,
	143.8130f, 206.2184f, 177.0371f, 235.0044f, 209.0457f, 415.3847f, 338.2372f, 461.2934f, 231.5831f, 260.9141f, 329.1943f, 266.5435f,
	220.9448f, 342.6935f, 284.5580f, 402.0774f, 303.8214f, 394.8393f, 332.8489f, 425.6666f, 178.4043f, 323.5138f, 229.9188f, 425.8390f,
	321.6556f, 129.9190f, 427.5185f, 157.9359f, 151.0502f, 8.1484f, 182.4998f, 109.6955f, 157.8666f, 99.0403f, 172.8104f, 139.2982f,
	-3.0452f, 224.4737f, 130.2711f, 278.4012f, 36.9224f, 226.1483f, 151.7898f, 279.1286f, 409.8757f, 237.4242f, 440.6452f, 345.2202f,
	200.8640f, 162.2960f, 245.4184f, 232.8059f, 41.0147f, 366.0289f, 186.8531f, 420.8625f, 326.4108f, 392.5565f, 432.9303f, 520.5973f,
	231.0067f, 80.2522f, 322.9745f, 166.4729f, -12.8403f, 351.8312f, 33.9963f, 384.6920f, 135.3959f, 271.4291f, 180.9655f, 406.5427f,
	85.0562f, 235.5178f, 91.9452f, 287.5727f, 273.1645f, 90.8612f, 382.7083f, 97.6691f, 133.7990f, 360.2684f, 141.2321f, 434.9638f,
	31.6115f, 470.5798f, 33.3353f, 490.0465f, -27.3799f, 342.6524f, 82.3149f, 379.1839f, 219.6726f, 402.7702f, 362.0547f, 515.0898f,
	-45.9977f, 481.8516f, 67.7212f, 502.3336f, 388.7589f, 115.4080f, 460.0333f, 236.6427f, 40.9882f, 248.8122f, 114.4089f, 389.4114f,
	270.2910f, 191.2797f, 336.2753f, 282.6530f, 197.6581f, 439.8926f, 247.0300f, 546.7361f, 182.0580f, -6.7583f, 260.7935f, 100.5661f,
	3.2778f, 131.7233f, 68.5193f, 280.6516f, 356.3126f, 411.8249f, 446.4396f, 463.7141f, 379.1163f, 129.3928f, 513.9362f, 154.6585f,
	-69.1199f, 354.7185f, 80.1365f, 433.0744f, 82.9357f, 151.1645f, 95.6685f, 231.6187f, 422.7932f, 476.2348f, 481.1110f, 503.7437f,
	260.7842f, 395.5883f, 288.7094f, 487.9416f, 48.2868f, 149.1079f, 101.7528f, 152.2125f, 79.4785f, 315.4853f, 123.3120f, 454.7079f,
	316.4901f, 148.2175f, 343.4961f, 188.6391f, 304.9847f, 299.7342f, 419.8321f, 306.6287f, 262.2399f, 320.6758f, 337.1869f, 337.8050f,
	407.5904f, 396.3992f, 545.5580f, 433.1963f, 244.1037f, -8.6806f, 249.9599f, 33.1314f, 144.6461f, 107.1346f, 155.6258f, 113.0233f,
	208.0726f, 334.6470f, 269.1603f, 377.2708f, 173.3525f, 266.8875f, 186.3138f, 296.6358f, 92.1346f, 219.0953f, 132.2813f, 276.5098f,
	-50.9776f, -1.5900f, 96.9408f, 56.8000f, 160.0388f, 148.3819f, 192.1737f, 199.8940f, 340.4449f, 407.6198f, 370.9644f, 457.4804f,
	-34.0173f, 8.2614f, 52.4551f, 22.6314f, 181.9884f, 195.8403f, 257.1901f, 200.5959f, 278.2621f, 457.0166f, 365.7473f, 488.1317f,
	276.6353f, -31.4300f, 333.7688f, 82.3108f, 326.2304f, 300.5375f, 450.4180f, 449.1682f, 394.4356f, 59.1311f, 416.0841f, 198.4815f,
	323.4377f, 395.2401f, 388.2682f, 471.3687f, -0.4884f, 332.9131f, 103.2861f, 413.1549f, 172.3276f, 418.9163f, 302.6948f, 466.7889f,
	273.6699f, 49.8039f, 329.7361f, 166.1209f, 79.9860f, 208.1720f, 165.5801f, 323.1208f, 15.6250f, 326.2367f, 26.9268f, 453.0333f,
	98.6064f, 55.6348f, 124.9839f, 190.0650f, 221.7964f, 82.5141f, 233.0980f, 148.2322f, 152.2380f, -44.0412f, 261.6923f, 71.2233f,
	66.3730f, 418.6809f, 110.2940f, 539.8344f, 357.7888f, 331.5282f, 466.6268f, 378.4887f, 457.3967f, 248.0516f, 468.2900f, 387.5087f,
	35.9143f, 364.4689f, 165.4340f, 379.5258f, 402.0395f, 191.2334f, 527.5334f, 340.3795f, 1.8053f, 180.1951f, 16.0557f, 295.9387f,
	460.2114f, 217.3174f, 464.7511f, 232.2148f, 471.2709f, 270.8305f, 480.6579f, 369.6087f, -58.0695f, 97.7211f, 70.1214f, 103.8139f,
	363.5242f, 386.1504f, 399.4951f, 501.9083f, 443.7544f, 345.8341f, 526.4471f, 465.9183f, 420.6959f, 129.4022f, 485.2063f, 220.1614f,
	425.5884f, 224.9686f, 545.1217f, 353.6407f, 238.2388f, 62.7213f, 312.0847f, 78.3060f, 1.2788f, 465.1168f, 76.8773f, 507.2295f,
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---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 805 to 871 in b5c1e77

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	0.3092f, 0.2031f, 0.3177f, 0.0829f, 0.1585f, 0.4171f, 0.8795f, 0.0573f, 0.2127f, 0.9083f, 0.8900f, 0.6795f,
	0.2405f, 0.4198f, 0.2112f, 0.1286f, 0.3800f, 0.5758f, 0.3599f, 0.6108f, 0.2963f, 0.3459f, 0.7907f, 0.8783f,
	0.3220f, 0.5715f, 0.2782f, 0.0533f, 0.7379f, 0.1710f, 0.4257f, 0.4870f, 0.1845f, 0.0946f, 0.3480f, 0.9523f,
	0.6151f, 0.3814f, 0.0389f, 0.6003f, 0.0923f, 0.5425f, 0.7520f, 0.4236f, 0.2994f, 0.0474f, 0.0248f, 0.4300f,
	0.8833f, 0.2441f, 0.5741f, 0.6843f, 0.0608f, 0.1531f, 0.3313f, 0.6701f, 0.4390f, 0.7342f, 0.8676f, 0.7584f,
	0.9922f, 0.7544f, 0.8522f, 0.8324f, 0.7303f, 0.8018f, 0.9347f, 0.4752f, 0.6383f, 0.5149f, 0.8510f, 0.4314f,
	0.8197f, 0.7994f, 0.9619f, 0.2489f, 0.7096f, 0.7569f, 0.9363f, 0.9069f, 0.5735f, 0.5792f, 0.1673f, 0.9750f,
	0.2550f, 0.7247f, 0.7958f, 0.4412f, 0.2112f, 0.1890f, 0.8565f, 0.5108f, 0.0901f, 0.7170f, 0.2502f, 0.8764f,
	0.3096f, 0.2003f, 0.0849f, 0.5115f, 0.4507f, 0.7513f, 0.4646f, 0.3438f, 0.2617f, 0.2781f, 0.9278f, 0.1651f,
	0.9882f, 0.3269f, 0.0884f, 0.2487f, 0.0584f, 0.7900f, 0.5126f, 0.3370f, 0.6620f, 0.6306f, 0.9399f, 0.9613f,
	0.6807f, 0.8178f, 0.7924f, 0.4913f, 0.7045f, 0.0783f, 0.7580f, 0.9618f, 0.0850f, 0.8361f, 0.9330f, 0.2262f,
	0.5248f, 0.9279f, 0.9602f, 0.1279f, 0.3490f, 0.6981f, 0.2216f, 0.3248f, 0.0233f, 0.1535f, 0.5623f, 0.6531f,
	0.6489f, 0.7784f, 0.4153f, 0.2735f, 0.0156f, 0.2066f, 0.3124f, 0.1782f, 0.0201f, 0.1574f, 0.6661f, 0.6296f,
	0.9357f, 0.7982f, 0.5678f, 0.1376f, 0.5641f, 0.0616f, 0.4309f, 0.3903f, 0.4278f, 0.2798f, 0.6858f, 0.8409f,
	0.7685f, 0.6278f, 0.5383f, 0.0311f, 0.7229f, 0.5450f, 0.2707f, 0.3278f, 0.9356f, 0.6244f, 0.4759f, 0.6209f,
	0.4137f, 0.4702f, 0.2903f, 0.4399f, 0.6856f, 0.0399f, 0.7950f, 0.2830f, 0.6826f, 0.6427f, 0.6526f, 0.6081f,
	0.9591f, 0.5083f, 0.7323f, 0.7054f, 0.2363f, 0.2833f, 0.4240f, 0.2777f, 0.3667f, 0.3910f, 0.6039f, 0.2199f,
	0.8043f, 0.4375f, 0.7062f, 0.0814f, 0.4700f, 0.0282f, 0.6759f, 0.3437f, 0.9493f, 0.3241f, 0.5638f, 0.2574f,
	0.6201f, 0.4670f, 0.3706f, 0.2037f, 0.1115f, 0.1199f, 0.9990f, 0.4123f, 0.0019f, 0.9529f, 0.0200f, 0.4186f,
	0.7175f, 0.9146f, 0.7129f, 0.4636f, 0.9744f, 0.0393f, 0.9869f, 0.8494f, 0.9289f, 0.2548f, 0.1425f, 0.6633f,
	0.5159f, 0.5232f, 0.9246f, 0.6201f, 0.3111f, 0.4001f, 0.1335f, 0.1923f, 0.1434f, 0.8103f, 0.7049f, 0.5303f,
	0.3744f, 0.6685f, 0.8129f, 0.8812f, 0.5470f, 0.8199f, 0.5113f, 0.4745f, 0.8654f, 0.3864f, 0.3959f, 0.3049f,
	0.5187f, 0.5449f, 0.6605f, 0.4305f, 0.2178f, 0.8668f, 0.3460f, 0.9229f, 0.2074f, 0.5601f, 0.5366f, 0.8286f,
	0.1389f, 0.9099f, 0.5314f, 0.5861f, 0.5102f, 0.0360f, 0.4971f, 0.2635f, 0.3427f, 0.6491f, 0.4977f, 0.0932f,
	0.0730f, 0.1857f, 0.1909f, 0.6083f, 0.1778f, 0.8817f, 0.2098f, 0.0911f, 0.8757f, 0.2953f, 0.4254f, 0.9590f,
	0.9444f, 0.7149f, 0.0689f, 0.5933f, 0.9891f, 0.9469f, 0.1060f, 0.3960f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 879 in b5c1e77

std::vector<int64_t> gold = {0, 0, 143, 0, 0, 10, 0, 0, 13, 0, 0, 0, 0, 0, 90, 0, 0, 135, 0, 0, 1, 0, 0, 76, 0, 0, 108, 0, 0, 170, 0, 0, 140, 0, 0, 20, 0, 0, 151, 0, 0, 150, 0, 0, 39, 0, 0, 44, 0, 0, 41, 0, 0, 82, 0, 0, 80, 0, 0, 88, 0, 0, 16, 0, 0, 27, 0, 0, 167, 0, 0, 165, 0, 0, 181, 0, 1, 187, 0, 1, 94, 0, 1, 152, 0, 1, 72, 0, 1, 32, 0, 1, 153, 0, 1, 109, 0, 1, 150, 0, 1, 19, 0, 1, 27, 0, 1, 96, 0, 1, 35, 0, 1, 197, 0, 1, 68, 0, 1, 22, 0, 1, 154, 0, 1, 17, 0, 1, 117, 0, 1, 43, 0, 1, 97, 0, 1, 10, 0, 1, 180, 0, 1, 182, 0, 1, 67, 0, 1, 44, 1, 0, 35, 1, 0, 152, 1, 0, 175, 1, 0, 4, 1, 0, 71, 1, 0, 166, 1, 0, 127, 1, 0, 38, 1, 0, 170, 1, 0, 44, 1, 0, 158, 1, 0, 198, 1, 0, 24, 1, 0, 101, 1, 0, 171, 1, 0, 2, 1, 0, 53, 1, 0, 102, 1, 0, 66, 1, 0, 140, 1, 0, 37, 1, 0, 98, 1, 0, 115, 1, 0, 150, 1, 0, 6, 1, 1, 114, 1, 1, 196, 1, 1, 0, 1, 1, 126, 1, 1, 124, 1, 1, 19, 1, 1, 11, 1, 1, 26, 1, 1, 84, 1, 1, 191, 1, 1, 117, 1, 1, 104, 1, 1, 197, 1, 1, 192, 1, 1, 10, 1, 1, 48, 1, 1, 68, 1, 1, 22, 1, 1, 128, 1, 1, 25, 1, 1, 134, 1, 1, 163, 1, 1, 121, 1, 1, 169, 1, 1, 185};

[github-actions]

Remaining comments which cannot be posted as a review comment to avoid GitHub Rate Limit

format.py

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 62 in 1011256

const auto num_boxes = boxes_s.lens()[1];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 64 in 1011256

const auto aligned_b = static_cast<std::size_t>(bit_ceil(static_cast<std::uint32_t>(num_boxes)));

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 143 in 1011256

const auto num_boxes = boxes_s.lens()[1];

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Line 145 in 1011256

const auto iou_packed = (num_boxes * (num_boxes - 1) / 2);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/src/targets/gpu/prepare_nonmaxsuppression.cpp

Lines 168 to 182 in 1011256

	auto sorted = m.insert_instruction(
	ins,
	make_op("gpu::nms_sort", {{"center_point_box", center_point_box}}),
	inputs[0],
	inputs[1]);
	auto filter = m.insert_instruction(
	ins,
	make_op("gpu::nms_filter",
	{{"num_batches", num_batches}, {"num_classes", num_classes}, {"num_boxes", num_boxes}}),
	sorted,
	inputs[2],
	inputs[3],
	inputs[4],
	mask_alloc);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 220 in 1011256

int64_t max_out_val = 4;

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 299 to 302 in 1011256

	std::vector<float> boxes_vec = {0.5, 0.5, 1.0, 1.0, 0.5, 0.6, 1.0, 1.0, 0.5, 0.4, 1.0, 1.0,
	0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0,
	0.5, 0.5, 1.0, 1.0, 0.5, 0.6, 1.0, 1.0, 0.5, 0.4, 1.0, 1.0,
	0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 346 to 348 in 1011256

	std::vector<float> boxes_vec = {0.0, 0.0, 1.0, 1.0, 0.0, 0.1, 1.0, 1.1,
	0.0, -0.1, 1.0, 0.9, 0.0, 10.0, 1.0, 11.0,
	0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 379 to 385 in 1011256

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 389 to 398 in 1011256

	32.7256f, 35.1377f, 43.0832f, 42.2579f, 13.9286f, 15.6152f, 21.5240f, 28.2727f, 44.0782f, 37.5280f, 52.9916f, 48.3318f,
	38.8011f, 32.1818f, 50.5110f, 37.5550f, 33.9761f, -1.6170f, 43.8622f, 11.0347f, 5.3569f, 42.6478f, 14.1070f, 54.9145f,
	18.9216f, 34.8446f, 27.7505f, 41.2693f, -0.4375f, 36.7849f, 4.8178f, 41.8215f, 6.9987f, 1.1282f, 8.4302f, 11.6832f,
	30.5954f, 21.0410f, 37.7095f, 23.9976f, 35.2360f, 16.6405f, 39.2402f, 20.4393f, 45.0158f, 45.7867f, 51.7352f, 46.8898f,
	9.8174f, 26.1848f, 22.7651f, 38.2017f, 16.3854f, 35.9841f, 20.6606f, 46.2920f, 22.5697f, 16.7346f, 24.3859f, 27.6069f,
	7.0039f, 5.3968f, 11.9433f, 17.3270f, 3.9409f, 24.0168f, 9.0512f, 31.4417f, 18.6518f, -1.2903f, 28.9187f, 7.6721f,
	6.9462f, 39.9030f, 15.7447f, 42.8601f, 27.5034f, 30.2815f, 39.4780f, 32.8849f};
	std::vector<float> scores_vec = {
	0.6979f, 0.4657f, 0.8326f, 0.2503f, 0.1204f, 0.1810f, 0.7501f, 0.5157f, 0.2451f, 0.5509f, 0.2371f, 0.7267f,
	0.5015f, 0.4429f, 0.3714f, 0.6673f, 0.4256f, 0.1789f, 0.2062f, 0.9657f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 406 in 1011256

std::vector<int64_t> gold = {0, 0, 19, 0, 0, 2, 0, 0, 6, 0, 0, 11, 0, 0, 0, 0, 0, 15, 0, 0, 9, 0, 0, 7, 0, 0, 12, 0, 0, 1};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 435 to 451 in 1011256

	90.8581f, 82.6292f, 23.5447f, 19.9060f, 69.9707f, 89.6161f, 29.1830f, 26.1572f, 26.5870f, 14.0249f, 15.5215f, 14.1630f,
	96.9176f, 55.4036f, 5.1730f, 8.1873f, 77.8751f, 10.8576f, 1.4042f, 7.8632f, 71.6890f, 67.2240f, 7.6600f, 22.6344f,
	44.9361f, 28.1234f, 4.8228f, 24.6805f, 27.2242f, 65.9423f, 20.6521f, 4.0531f, 9.6391f, 72.6995f, 4.5331f, 2.9302f,
	90.2602f, 76.8647f, 15.6836f, 18.2386f, 45.5776f, 10.7741f, 21.1336f, 5.2390f, 20.2363f, 91.6012f, 17.8524f, 24.9153f,
	30.5957f, 23.0214f, 6.7935f, 9.9997f, 57.9220f, 3.7413f, 24.3196f, 5.1723f, 17.6773f, 55.4852f, 21.7468f, 27.7081f,
	85.6614f, 37.0922f, 22.4305f, 5.8004f, 75.8520f, 82.9790f, 4.8007f, 9.2569f, 71.9463f, 80.8251f, 4.5889f, 5.4548f,
	43.2093f, 31.7139f, 27.8993f, 4.3492f, 62.7309f, 95.2899f, 12.5298f, 1.6133f, 58.4098f, 29.0918f, 9.7275f, 2.6065f,
	64.9847f, 51.5057f, 15.1689f, 6.0646f, 8.4444f, 25.5965f, 20.2231f, 2.5481f, 41.5807f, 93.6044f, 28.7131f, 18.1432f,
	4.1614f, 16.4608f, 9.3069f, 20.7407f, 49.3991f, 4.4911f, 27.8194f, 12.4153f, 32.9861f, 43.5097f, 1.7209f, 10.2217f,
	14.4524f, 99.2376f, 17.1007f, 15.6313f, 10.3403f, 89.1677f, 19.3853f, 26.3751f, 58.7645f, 74.8608f, 4.0710f, 25.6828f,
	17.0593f, 89.0792f, 5.0698f, 2.2608f, 92.5120f, 89.3447f, 13.1543f, 6.2635f, 58.1061f, 51.8858f, 29.0207f, 7.8656f,
	34.6870f, 31.5929f, 18.2852f, 8.2322f, 59.0915f, 77.2012f, 28.0577f, 17.5657f, 2.2804f, 66.1661f, 24.3265f, 13.0716f,
	95.8559f, 37.3658f, 14.5541f, 2.4284f, 48.2303f, 9.4467f, 23.7581f, 11.8348f, 78.2735f, 74.6790f, 1.5173f, 16.1888f,
	8.2730f, 26.2461f, 4.1652f, 3.9485f, 48.6658f, 93.6813f, 25.0534f, 25.1703f, 49.0707f, 24.0971f, 24.1077f, 2.5069f,
	93.7826f, 12.2758f, 7.7466f, 27.8204f, 57.1728f, 83.1113f, 16.3923f, 3.8743f, 47.3489f, 15.3284f, 18.5745f, 25.4637f,
	26.6976f, 17.9268f, 26.1644f, 27.1769f, 33.1569f, 59.9383f, 18.4901f, 29.4075f, 52.0672f, 87.4562f, 12.9646f, 24.2588f,
	43.8911f, 19.6435f, 11.8513f, 23.6048f, 2.1612f, 31.0324f, 13.3506f, 19.6320f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 453 to 457 in 1011256

	0.8011f, 0.2211f, 0.5825f, 0.5628f, 0.8718f, 0.5165f, 0.4466f, 0.6756f, 0.3398f, 0.2258f, 0.5301f, 0.4752f,
	0.3093f, 0.4308f, 0.4298f, 0.3947f, 0.4415f, 0.7172f, 0.3672f, 0.9540f, 0.9247f, 0.5328f, 0.3955f, 0.5819f,
	0.8637f, 0.6873f, 0.8240f, 0.5795f, 0.6696f, 0.3593f, 0.7614f, 0.2822f, 0.7253f, 0.8746f, 0.2189f, 0.6529f,
	0.1856f, 0.7531f, 0.1760f, 0.9423f, 0.2237f, 0.9630f, 0.8208f, 0.6343f, 0.8044f, 0.8156f, 0.9514f, 0.3280f,
	0.6311f, 0.1855f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 465 in 1011256

std::vector<int64_t> gold = {0, 0, 41, 0, 0, 19, 0, 0, 46, 0, 0, 39, 0, 0, 20, 0, 0, 33, 0, 0, 4, 0, 0, 24, 0, 0, 26, 0, 0, 42, 0, 0, 45, 0, 0, 44, 0, 0, 0, 0, 0, 30, 0, 0, 32, 0, 0, 17, 0, 0, 25, 0, 0, 7, 0, 0, 28, 0, 0, 35};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 484 to 490 in 1011256

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 494 to 560 in 1011256

	-3.8699f, 108.8880f, 20.8101f, 137.5783f, 149.9079f, 29.3134f, 203.7504f, 39.2031f, 121.6031f, 107.1528f, 162.2282f, 118.8275f,
	27.1146f, 87.2265f, 42.1365f, 141.7457f, -7.3128f, 91.3799f, 44.0012f, 95.0142f, 25.9397f, 97.1572f, 47.4736f, 111.8955f,
	170.3318f, 143.6689f, 221.6791f, 161.9004f, 82.3933f, 144.8881f, 101.0310f, 174.8098f, 138.9017f, 80.6305f, 174.7306f, 116.2308f,
	115.0719f, 104.8666f, 139.4914f, 134.9707f, 105.8753f, 183.2658f, 123.0900f, 189.2287f, 2.3726f, 16.2585f, 55.6795f, 31.6349f,
	183.1709f, -1.9651f, 195.2389f, 48.8066f, 57.2666f, -1.7671f, 63.2705f, 36.8507f, 105.0166f, 111.9228f, 126.1903f, 151.2225f,
	118.2848f, 63.4507f, 161.6255f, 103.9927f, 105.5274f, 131.8586f, 154.1659f, 177.8699f, 158.1560f, 132.0321f, 218.0818f, 136.4605f,
	20.4451f, 55.4126f, 38.9305f, 78.0425f, 89.1363f, 163.2572f, 114.2048f, 196.0894f, 76.2707f, 142.0220f, 85.3431f, 162.9909f,
	77.3750f, 28.6949f, 112.2925f, 79.5191f, -6.0851f, 58.1025f, 53.7721f, 87.5743f, 5.6429f, 39.7135f, 47.9949f, 86.0625f,
	37.5563f, 5.8879f, 73.6739f, 57.1568f, 48.8660f, 14.1653f, 73.0158f, 44.9480f, 58.0793f, 159.8937f, 113.0820f, 214.5573f,
	107.0385f, 69.7607f, 137.3566f, 105.4010f, 122.4620f, 51.0809f, 131.3896f, 102.2471f, 71.0835f, 135.3897f, 93.6408f, 156.4846f,
	79.2752f, 95.3835f, 84.2380f, 125.8137f, 37.0673f, 171.0514f, 49.9841f, 203.4046f, 116.6400f, 152.4634f, 118.6825f, 159.6572f,
	49.5364f, 83.6166f, 77.2799f, 108.1312f, -12.0070f, 47.7104f, 26.4309f, 102.8334f, 73.0529f, 178.2168f, 94.3071f, 216.4359f,
	81.9253f, 137.8156f, 107.7278f, 149.2885f, 16.3219f, 179.7427f, 73.9152f, 200.7352f, 91.8087f, 17.5434f, 137.1745f, 29.8480f,
	96.6991f, 168.8745f, 129.6096f, 171.3390f, 131.5065f, 99.5547f, 149.2944f, 155.2749f, 102.6283f, 10.6622f, 156.5511f, 38.1065f,
	123.0512f, 108.0793f, 137.9220f, 127.2239f, 53.1452f, 119.0642f, 73.3404f, 155.3743f, 130.1690f, 1.7448f, 184.8039f, 3.1763f,
	93.7074f, 82.1619f, 125.9504f, 99.5652f, 63.8853f, 143.8404f, 108.6820f, 186.3194f, 107.2755f, 39.8756f, 143.1295f, 78.2680f,
	52.3550f, 62.2463f, 91.9079f, 121.1729f, 93.2160f, 69.6623f, 111.8797f, 107.2634f, 139.7207f, 45.7991f, 154.9616f, 74.9719f,
	167.2671f, 160.7261f, 187.2941f, 206.6506f, 179.1259f, 129.1106f, 189.2970f, 183.4070f, 74.4343f, 0.3572f, 127.0189f, 43.8782f,
	95.1992f, 170.4922f, 112.9108f, 228.3217f, 142.9101f, 152.2709f, 177.0380f, 199.4092f, 39.0269f, 30.7110f, 86.7534f, 82.8523f,
	143.8537f, 163.5132f, 191.0993f, 171.2454f, 85.3959f, -0.8223f, 112.2607f, 43.3901f, 8.6218f, 186.3383f, 37.7209f, 213.3036f,
	-15.4319f, 116.3204f, 44.2555f, 149.9535f, 147.9980f, 110.2290f, 188.7993f, 149.8210f, -13.4183f, -11.0214f, 35.6454f, 47.1977f,
	28.9969f, 149.8616f, 83.2476f, 208.9517f, 43.0921f, -3.2028f, 90.5599f, 14.8026f, 28.6361f, 26.0199f, 40.5617f, 70.3113f,
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	136.7519f, 180.4197f, 194.1175f, 183.8356f, 155.6840f, 107.8222f, 186.9352f, 154.6854f, 61.1796f, -7.7136f, 87.7250f, 22.1787f,
	29.1652f, -28.4875f, 32.2799f, 30.6594f, 91.3547f, -3.8851f, 148.9814f, 24.5483f, 20.3959f, 91.8365f, 27.4731f, 150.5336f,
	71.2720f, 147.6549f, 74.6957f, 172.9379f, 183.9269f, 23.7969f, 199.4448f, 71.6242f, 196.6597f, 166.8796f, 201.5260f, 172.8839f,
	140.4950f, -5.4397f, 168.3470f, 28.3325f, 46.4677f, 136.0320f, 77.9169f, 184.3535f, 127.8122f, 157.7804f, 147.2538f, 213.3378f,
	139.0779f, 129.6555f, 143.0846f, 179.1879f, 73.7761f, 138.0335f, 81.3605f, 141.2148f, 116.3348f, 156.1013f, 140.0206f, 179.0908f,
	-0.1401f, 6.0937f, 4.4311f, 9.9669f, 20.7149f, 36.6326f, 62.9081f, 44.0802f, 98.4106f, 4.5632f, 111.6248f, 45.4062f,
	23.3391f, 79.3651f, 42.1614f, 122.4473f, 21.0547f, 125.7129f, 45.3081f, 172.3624f, 154.4709f, 99.9714f, 180.0508f, 152.0333f,
	197.2776f, 147.9130f, 198.3756f, 192.5394f, 107.3878f, 6.9169f, 115.0000f, 55.1683f, 141.8624f, 144.9798f, 193.7655f, 148.8687f,
	197.5280f, 31.1895f, 198.6007f, 46.0271f, 12.8282f, 35.3058f, 43.8101f, 72.9977f, 74.7088f, 116.1662f, 104.5894f, 167.7956f,
	68.1883f, 195.4082f, 88.8408f, 196.6737f, 2.7857f, 106.6272f, 29.2340f, 137.9903f, 127.5389f, -9.5799f, 174.5932f, 31.3800f,
	61.4403f, 121.8884f, 112.0713f, 124.6352f, 15.4868f, 35.9096f, 55.8899f, 68.2298f, 35.5922f, 56.6701f, 44.2246f, 72.3261f,
	163.1796f, 40.7751f, 180.4136f, 56.2181f, 177.9262f, 90.7157f, 187.1069f, 101.2297f, 33.5656f, 108.4211f, 51.2933f, 164.8822f,
	73.5555f, 18.9549f, 114.3649f, 72.3462f, 119.3443f, 42.7151f, 174.0536f, 89.5792f, 169.1987f, 170.3059f, 182.1476f, 201.8479f,
	59.3192f, -5.2591f, 92.3019f, 24.6868f, 82.2129f, 76.0264f, 124.5949f, 108.2814f, 119.7321f, 125.9828f, 176.9545f, 158.6404f,
	127.7304f, 16.7712f, 164.7240f, 43.4104f, 148.5664f, 5.0880f, 164.6177f, 13.8616f, 95.0352f, 23.4340f, 132.9384f, 31.8482f,
	10.9685f, 155.1733f, 30.8775f, 212.3560f, 151.4989f, -12.8680f, 210.0904f, 16.5719f, 160.8241f, 9.0448f, 185.4050f, 66.2840f,
	138.8994f, 0.9312f, 180.3396f, 11.5822f, 18.7873f, 5.2706f, 21.1577f, 38.9812f, 28.5777f, 117.4022f, 53.1813f, 130.6575f,
	122.4044f, 40.3588f, 175.0358f, 56.2967f, -13.8737f, 112.4558f, 23.1297f, 115.2290f, 182.2486f, 114.0300f, 209.4412f, 122.0482f,
	47.3188f, 142.3400f, 103.5391f, 197.4341f, 118.1700f, -9.0369f, 169.5550f, 10.9335f, 167.5089f, 152.2341f, 187.5196f, 189.1137f,
	62.3618f, 109.6059f, 95.4902f, 138.0417f, 48.8767f, 20.2354f, 78.7763f, 44.8620f, 102.5983f, 138.3968f, 140.8982f, 170.7781f,
	105.8416f, 165.0748f, 126.5542f, 177.1219f, 74.1239f, 21.1889f, 89.5320f, 80.5165f, 92.9311f, 159.1187f, 147.7788f, 208.3988f,
	159.3220f, 68.5139f, 214.8306f, 113.2691f, 68.1500f, 106.3565f, 118.9061f, 135.0133f, 9.9914f, 191.9200f, 68.7055f, 201.9398f,
	52.9639f, 44.6476f, 97.9184f, 99.9669f, 55.7637f, 152.0609f, 101.8791f, 173.2028f, 3.2253f, 61.7017f, 49.2181f, 65.6580f,
	17.8964f, 149.2418f, 47.2522f, 170.4436f, 122.9471f, 96.2103f, 150.8778f, 144.0833f, 60.3089f, 24.4012f, 75.4822f, 62.1410f,
	171.4575f, 60.1555f, 210.5018f, 105.4550f, 39.6844f, 39.6149f, 57.7543f, 87.4394f, 11.6796f, 8.8690f, 27.8902f, 22.3743f,
	132.9151f, -21.7847f, 168.4868f, 33.7186f, 163.6127f, 55.8750f, 188.8017f, 82.7164f, 48.6664f, -15.5441f, 62.5789f, 23.1577f,
	15.8440f, 32.5294f, 64.9913f, 33.6657f, 11.2664f, 115.2323f, 63.0400f, 174.8410f, 98.9553f, 132.8318f, 109.8496f, 150.4047f,
	92.9619f, 145.3852f, 94.4048f, 150.0469f, 41.4721f, 49.4119f, 62.3038f, 77.4494f, -14.9919f, 173.6975f, 33.0612f, 182.3103f,
	71.0426f, 113.7725f, 121.5539f, 123.7598f, 187.2858f, 6.0529f, 196.4472f, 44.3576f, 107.1609f, 16.6524f, 153.8468f, 40.8351f,
	95.1880f, 110.9244f, 103.0146f, 166.3137f, 10.1316f, 24.6737f, 34.1453f, 44.5039f, 20.5283f, 79.5362f, 80.4462f, 123.3809f,
	52.7734f, 184.2525f, 65.1362f, 212.4573f, 147.9188f, -19.1670f, 158.0026f, 20.7701f, 162.3696f, -14.8751f, 188.3148f, 21.5070f,
	161.5482f, 184.1698f, 199.1086f, 213.0640f, 168.8931f, 88.4010f, 224.9343f, 145.4546f, 167.0391f, 14.7719f, 225.9076f, 35.9920f,
	188.0454f, 173.7320f, 193.1542f, 185.1889f, 9.7935f, 155.5723f, 18.9354f, 196.5798f, 3.7319f, 81.7829f, 51.3855f, 132.6973f,
	52.4097f, 122.6709f, 69.3770f, 126.0459f, 83.9766f, 40.8733f, 137.1827f, 68.4016f, -0.6763f, -16.7244f, 39.4674f, 36.9323f,
	165.3600f, 96.2998f, 172.9588f, 141.5273f, 98.2916f, 29.1927f, 148.4108f, 88.7094f, 102.7704f, 116.5475f, 114.1754f, 148.9009f,
	20.0692f, 147.2792f, 46.0554f, 187.2189f, 33.8616f, -5.7911f, 67.4406f, 13.0553f, 16.7898f, 90.6905f, 47.3350f, 147.5951f,
	149.6448f, 34.9492f, 191.1284f, 57.5630f, 97.0913f, 152.4916f, 136.5998f, 197.0638f, 117.2606f, 38.3403f, 176.7911f, 63.1255f,
	29.2236f, 105.0804f, 89.1895f, 139.2277f, 58.5150f, 88.9746f, 89.9861f, 132.4418f, 77.6626f, 63.7197f, 84.2794f, 94.7469f,
	130.0316f, 108.2651f, 173.9744f, 162.7832f, 125.1590f, 132.2845f, 183.7822f, 158.0233f, 31.4721f, 93.7989f, 51.2533f, 132.9762f,
	174.2021f, 141.0848f, 202.4134f, 162.2841f, 11.1001f, 184.1428f, 37.1620f, 209.2240f, 177.2076f, 70.3730f, 181.2413f, 97.3360f,
	-0.2527f, 98.7053f, 40.4109f, 107.1279f, 41.9845f, -0.7119f, 63.8314f, 5.6998f, 145.5655f, 139.0148f, 193.0259f, 179.3967f,
	10.8509f, 84.2082f, 60.9460f, 123.8838f, 57.9873f, 61.5364f, 107.4399f, 101.6481f, 77.1802f, 17.7313f, 102.7635f, 19.8975f,
	39.0662f, 167.7982f, 59.0374f, 188.0644f, 119.4588f, 72.6661f, 164.6393f, 85.3368f, 146.1259f, 113.0609f, 194.4079f, 159.9718f,
	159.9229f, 3.9862f, 189.9071f, 55.7634f, 41.0200f, 184.5329f, 94.7088f, 200.0870f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 562 to 578 in 1011256

	0.1439f, 0.8791f, 0.0961f, 0.1535f, 0.5338f, 0.0675f, 0.0528f, 0.0005f, 0.4363f, 0.7746f, 0.0348f, 0.6523f,
	0.8231f, 0.1680f, 0.1469f, 0.8608f, 0.8231f, 0.5389f, 0.8192f, 0.0928f, 0.3945f, 0.7378f, 0.2575f, 0.7523f,
	0.5042f, 0.7503f, 0.4647f, 0.3679f, 0.2192f, 0.2084f, 0.7515f, 0.1189f, 0.0860f, 0.1763f, 0.1753f, 0.8231f,
	0.3985f, 0.9904f, 0.1372f, 0.6535f, 0.4487f, 0.3929f, 0.8751f, 0.9756f, 0.8729f, 0.1923f, 0.2208f, 0.6561f,
	0.2891f, 0.7347f, 0.5664f, 0.5509f, 0.8285f, 0.7105f, 0.0266f, 0.0495f, 0.6016f, 0.4862f, 0.2602f, 0.4187f,
	0.7579f, 0.8266f, 0.5612f, 0.3854f, 0.2707f, 0.5219f, 0.3147f, 0.5641f, 0.6767f, 0.0661f, 0.0011f, 0.2123f,
	0.8945f, 0.6463f, 0.1720f, 0.8903f, 0.4700f, 0.4761f, 0.9355f, 0.0595f, 0.2152f, 0.5858f, 0.1955f, 0.6795f,
	0.2141f, 0.0992f, 0.2070f, 0.4227f, 0.1761f, 0.1347f, 0.8603f, 0.3204f, 0.3608f, 0.0553f, 0.3574f, 0.2648f,
	0.6105f, 0.2054f, 0.8884f, 0.9297f, 0.0998f, 0.1074f, 0.1153f, 0.6196f, 0.1220f, 0.8524f, 0.7543f, 0.8198f,
	0.5261f, 0.9967f, 0.0442f, 0.4013f, 0.3239f, 0.9486f, 0.5769f, 0.8062f, 0.1703f, 0.9786f, 0.4986f, 0.4937f,
	0.9709f, 0.3807f, 0.3975f, 0.5848f, 0.1281f, 0.3211f, 0.1932f, 0.1033f, 0.8661f, 0.5893f, 0.3587f, 0.4087f,
	0.4315f, 0.6331f, 0.9268f, 0.9328f, 0.3915f, 0.3293f, 0.4510f, 0.5679f, 0.4618f, 0.6588f, 0.5544f, 0.3207f,
	0.3457f, 0.3786f, 0.0946f, 0.1661f, 0.7231f, 0.3891f, 0.2145f, 0.5627f, 0.7555f, 0.2574f, 0.8268f, 0.9275f,
	0.5974f, 0.6689f, 0.0526f, 0.9455f, 0.3925f, 0.9239f, 0.5790f, 0.0046f, 0.0385f, 0.6804f, 0.5627f, 0.0265f,
	0.7435f, 0.8521f, 0.4964f, 0.4658f, 0.0055f, 0.7866f, 0.3307f, 0.8788f, 0.3731f, 0.5651f, 0.2703f, 0.1606f,
	0.7749f, 0.4966f, 0.5365f, 0.9654f, 0.9636f, 0.8556f, 0.1876f, 0.5943f, 0.8781f, 0.3745f, 0.1011f, 0.8110f,
	0.4818f, 0.5644f, 0.9821f, 0.6072f, 0.4250f, 0.3700f, 0.4176f, 0.1184f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 586 in 1011256

std::vector<int64_t> gold = {0, 0, 37, 0, 0, 43, 0, 0, 78, 0, 0, 99, 0, 0, 72, 0, 0, 75, 0, 0, 98, 0, 0, 1, 0, 0, 42, 0, 0, 44, 0, 0, 15, 0, 0, 90, 0, 0, 52, 0, 0, 61, 0, 0, 12, 1, 0, 9, 1, 0, 94, 1, 0, 17, 1, 0, 20, 1, 0, 83, 1, 0, 84, 1, 0, 13, 1, 0, 59, 1, 0, 35, 1, 0, 55, 1, 0, 34, 1, 0, 61, 1, 0, 75, 1, 0, 88, 1, 0, 28};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 605 to 611 in 1011256

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 615 to 624 in 1011256

	31.2680f, 53.5348f, 37.7043f, 73.6253f, 1.8071f, 55.2945f, 3.9368f, 78.7402f, 40.5016f, 12.5670f, 45.0345f, 32.9366f,
	78.2552f, 12.9548f, 80.7117f, 35.6526f, 73.9527f, 67.9870f, 79.4405f, 71.9065f, -3.8066f, -7.7339f, 10.2705f, 11.5692f,
	45.4706f, 34.8613f, 67.4569f, 48.4119f, 17.4632f, 30.3439f, 30.8192f, 43.8443f, 64.5403f, 44.3725f, 79.9380f, 66.0477f,
	0.7877f, 1.3956f, 6.4307f, 24.7471f, 65.1632f, 44.8608f, 84.5766f, 62.0721f, 59.3935f, 24.0849f, 74.6026f, 36.1925f,
	-1.0372f, 43.7485f, 19.8379f, 55.2458f, -6.6257f, -1.7353f, 16.1976f, 8.1505f, 62.2758f, 32.2798f, 71.2775f, 41.5966f,
	10.9190f, 36.7777f, 14.0023f, 46.7824f, 39.6937f, 15.6139f, 45.8900f, 18.6783f, 67.7244f, 9.7794f, 78.7948f, 12.5604f,
	34.0204f, 5.6094f, 56.7713f, 24.5464f, 26.9281f, 21.9014f, 36.6292f, 33.1611f, 26.2374f, -3.4581f, 44.9652f, 18.9477f,
	-1.6661f, 68.2450f, 11.7649f, 83.3261f, 74.8979f, 31.4950f, 80.1025f, 33.3041f, 20.6639f, 62.4061f, 29.0408f, 67.0291f,
	7.1374f, 75.0864f, 23.1608f, 80.8203f, 14.6460f, -5.2621f, 31.1216f, 18.1798f, 71.6501f, 49.1185f, 82.6496f, 55.1487f,
	4.4135f, 63.2815f, 10.6723f, 76.1439f, 60.5823f, 39.4727f, 78.1862f, 62.0048f, 54.1855f, 22.5844f, 59.0696f, 46.0598f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 626 to 633 in 1011256

	0.9367f, 0.1879f, 0.1073f, 0.4976f, 0.5195f, 0.5082f, 0.4367f, 0.9948f, 0.4863f, 0.4779f, 0.4218f, 0.0668f,
	0.5930f, 0.2280f, 0.6376f, 0.0508f, 0.9814f, 0.4690f, 0.8968f, 0.4756f, 0.0603f, 0.8222f, 0.6482f, 0.7818f,
	0.4282f, 0.6379f, 0.8562f, 0.6311f, 0.3477f, 0.6625f, 0.6719f, 0.9606f, 0.3709f, 0.4251f, 0.8121f, 0.5058f,
	0.7366f, 0.4597f, 0.2155f, 0.7452f, 0.1312f, 0.1986f, 0.6268f, 0.7473f, 0.8947f, 0.2726f, 0.1107f, 0.9560f,
	0.1544f, 0.1977f, 0.2913f, 0.5294f, 0.8828f, 0.7605f, 0.7082f, 0.1752f, 0.3577f, 0.4784f, 0.1474f, 0.2734f,
	0.3083f, 0.1273f, 0.5502f, 0.7050f, 0.0699f, 0.4811f, 0.7822f, 0.7480f, 0.8151f, 0.4482f, 0.8206f, 0.2408f,
	0.3608f, 0.1764f, 0.4675f, 0.3921f, 0.2409f, 0.7518f, 0.3138f, 0.2728f, 0.1309f, 0.4388f, 0.3030f, 0.3693f,
	0.2360f, 0.7632f, 0.9300f, 0.4979f, 0.6430f, 0.8672f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 641 in 1011256

std::vector<int64_t> gold = {0, 0, 7, 0, 0, 16, 0, 0, 0, 0, 0, 18, 0, 0, 26, 0, 1, 1, 0, 1, 17, 0, 1, 14, 0, 1, 22, 0, 1, 4, 0, 2, 26, 0, 2, 29, 0, 2, 10, 0, 2, 6, 0, 2, 25};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 660 to 666 in 1011256

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 670 to 803 in 1011256

	132.1894f, 453.1169f, 199.9736f, 545.7127f, 64.3090f, 275.1729f, 104.8258f, 338.3436f, 76.1273f, 401.7875f, 135.6448f, 487.9920f,
	12.8305f, 442.3624f, 77.1708f, 466.2458f, -5.9609f, 340.1129f, 126.0715f, 451.3386f, 15.0119f, 224.3769f, 56.2927f, 236.5545f,
	427.8277f, -14.2917f, 561.9954f, 95.4457f, 4.7940f, -55.8461f, 69.2637f, 71.6517f, 41.3494f, 202.9014f, 91.1927f, 274.2992f,
	375.6902f, 208.6749f, 451.5645f, 285.6396f, 258.4982f, 179.9212f, 321.7420f, 227.4412f, 367.5344f, 211.3590f, 406.8828f, 356.8083f,
	277.5064f, 220.9636f, 353.4056f, 331.1991f, 429.2783f, 390.3169f, 452.8968f, 446.2962f, 292.5150f, 40.8054f, 345.9525f, 67.8517f,
	218.4112f, 95.7302f, 303.7139f, 129.4475f, 325.0759f, 361.4403f, 387.6738f, 431.5647f, 161.8149f, 353.1971f, 285.5779f, 494.6398f,
	153.4061f, 442.2182f, 192.6577f, 552.6060f, 161.0782f, 419.9203f, 306.5742f, 452.9917f, 25.8953f, 380.4122f, 143.8188f, 509.4868f,
	325.7002f, 128.4980f, 470.8716f, 185.8499f, 67.4107f, 136.8775f, 193.2931f, 264.7841f, 65.6790f, 115.5359f, 87.8525f, 152.5492f,
	83.4548f, 256.5595f, 162.8974f, 349.7399f, 407.8717f, 399.8657f, 434.1985f, 538.9396f, 103.6427f, 152.6073f, 226.5586f, 192.0336f,
	299.0049f, 226.3779f, 387.0450f, 330.6239f, 408.0779f, 74.0950f, 448.3318f, 222.2046f, -30.8828f, 73.1804f, 108.6275f, 96.6196f,
	373.4308f, 90.5068f, 391.5936f, 104.6787f, 111.3250f, -21.7549f, 196.3405f, 79.7002f, 54.0937f, 448.8364f, 162.5287f, 500.4571f,
	339.5665f, 195.6321f, 349.3349f, 207.2475f, 409.8580f, 381.1502f, 499.9386f, 452.9707f, 86.2250f, 284.0088f, 208.7943f, 397.3206f,
	278.8861f, 74.2190f, 289.9477f, 117.7022f, 106.2550f, 62.2701f, 183.5792f, 113.1921f, 257.3803f, 342.4895f, 296.9053f, 469.4987f,
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	0.3826f, 267.3577f, 134.6972f, 410.3510f, 332.4151f, 358.2527f, 361.1253f, 456.2211f, 312.7919f, 108.4937f, 361.9585f, 126.7627f,
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	238.7950f, -53.0971f, 286.2983f, 84.0919f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 805 to 871 in 1011256

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	0.3096f, 0.2003f, 0.0849f, 0.5115f, 0.4507f, 0.7513f, 0.4646f, 0.3438f, 0.2617f, 0.2781f, 0.9278f, 0.1651f,
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	0.3744f, 0.6685f, 0.8129f, 0.8812f, 0.5470f, 0.8199f, 0.5113f, 0.4745f, 0.8654f, 0.3864f, 0.3959f, 0.3049f,
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	0.1389f, 0.9099f, 0.5314f, 0.5861f, 0.5102f, 0.0360f, 0.4971f, 0.2635f, 0.3427f, 0.6491f, 0.4977f, 0.0932f,
	0.0730f, 0.1857f, 0.1909f, 0.6083f, 0.1778f, 0.8817f, 0.2098f, 0.0911f, 0.8757f, 0.2953f, 0.4254f, 0.9590f,
	0.9444f, 0.7149f, 0.0689f, 0.5933f, 0.9891f, 0.9469f, 0.1060f, 0.3960f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 879 in 1011256

std::vector<int64_t> gold = {0, 0, 143, 0, 0, 10, 0, 0, 13, 0, 0, 0, 0, 0, 90, 0, 0, 135, 0, 0, 1, 0, 0, 76, 0, 0, 108, 0, 0, 170, 0, 0, 140, 0, 0, 20, 0, 0, 151, 0, 0, 150, 0, 0, 39, 0, 0, 44, 0, 0, 41, 0, 0, 82, 0, 0, 80, 0, 0, 88, 0, 0, 16, 0, 0, 27, 0, 0, 167, 0, 0, 165, 0, 0, 181, 0, 1, 187, 0, 1, 94, 0, 1, 152, 0, 1, 72, 0, 1, 32, 0, 1, 153, 0, 1, 109, 0, 1, 150, 0, 1, 19, 0, 1, 27, 0, 1, 96, 0, 1, 35, 0, 1, 197, 0, 1, 68, 0, 1, 22, 0, 1, 154, 0, 1, 17, 0, 1, 117, 0, 1, 43, 0, 1, 97, 0, 1, 10, 0, 1, 180, 0, 1, 182, 0, 1, 67, 0, 1, 44, 1, 0, 35, 1, 0, 152, 1, 0, 175, 1, 0, 4, 1, 0, 71, 1, 0, 166, 1, 0, 127, 1, 0, 38, 1, 0, 170, 1, 0, 44, 1, 0, 158, 1, 0, 198, 1, 0, 24, 1, 0, 101, 1, 0, 171, 1, 0, 2, 1, 0, 53, 1, 0, 102, 1, 0, 66, 1, 0, 140, 1, 0, 37, 1, 0, 98, 1, 0, 115, 1, 0, 150, 1, 0, 6, 1, 1, 114, 1, 1, 196, 1, 1, 0, 1, 1, 126, 1, 1, 124, 1, 1, 19, 1, 1, 11, 1, 1, 26, 1, 1, 84, 1, 1, 191, 1, 1, 117, 1, 1, 104, 1, 1, 197, 1, 1, 192, 1, 1, 10, 1, 1, 48, 1, 1, 68, 1, 1, 22, 1, 1, 128, 1, 1, 25, 1, 1, 134, 1, 1, 163, 1, 1, 121, 1, 1, 169, 1, 1, 185};

[github-actions]

Remaining comments which cannot be posted as a review comment to avoid GitHub Rate Limit

format.py

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 453 to 457 in 32c779d

	0.8011f, 0.2211f, 0.5825f, 0.5628f, 0.8718f, 0.5165f, 0.4466f, 0.6756f, 0.3398f, 0.2258f, 0.5301f, 0.4752f,
	0.3093f, 0.4308f, 0.4298f, 0.3947f, 0.4415f, 0.7172f, 0.3672f, 0.9540f, 0.9247f, 0.5328f, 0.3955f, 0.5819f,
	0.8637f, 0.6873f, 0.8240f, 0.5795f, 0.6696f, 0.3593f, 0.7614f, 0.2822f, 0.7253f, 0.8746f, 0.2189f, 0.6529f,
	0.1856f, 0.7531f, 0.1760f, 0.9423f, 0.2237f, 0.9630f, 0.8208f, 0.6343f, 0.8044f, 0.8156f, 0.9514f, 0.3280f,
	0.6311f, 0.1855f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 465 in 32c779d

std::vector<int64_t> gold = {0, 0, 41, 0, 0, 19, 0, 0, 46, 0, 0, 39, 0, 0, 20, 0, 0, 33, 0, 0, 4, 0, 0, 24, 0, 0, 26, 0, 0, 42, 0, 0, 45, 0, 0, 44, 0, 0, 0, 0, 0, 30, 0, 0, 32, 0, 0, 17, 0, 0, 25, 0, 0, 7, 0, 0, 28, 0, 0, 35};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 484 to 490 in 32c779d

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 494 to 560 in 32c779d

	-3.8699f, 108.8880f, 20.8101f, 137.5783f, 149.9079f, 29.3134f, 203.7504f, 39.2031f, 121.6031f, 107.1528f, 162.2282f, 118.8275f,
	27.1146f, 87.2265f, 42.1365f, 141.7457f, -7.3128f, 91.3799f, 44.0012f, 95.0142f, 25.9397f, 97.1572f, 47.4736f, 111.8955f,
	170.3318f, 143.6689f, 221.6791f, 161.9004f, 82.3933f, 144.8881f, 101.0310f, 174.8098f, 138.9017f, 80.6305f, 174.7306f, 116.2308f,
	115.0719f, 104.8666f, 139.4914f, 134.9707f, 105.8753f, 183.2658f, 123.0900f, 189.2287f, 2.3726f, 16.2585f, 55.6795f, 31.6349f,
	183.1709f, -1.9651f, 195.2389f, 48.8066f, 57.2666f, -1.7671f, 63.2705f, 36.8507f, 105.0166f, 111.9228f, 126.1903f, 151.2225f,
	118.2848f, 63.4507f, 161.6255f, 103.9927f, 105.5274f, 131.8586f, 154.1659f, 177.8699f, 158.1560f, 132.0321f, 218.0818f, 136.4605f,
	20.4451f, 55.4126f, 38.9305f, 78.0425f, 89.1363f, 163.2572f, 114.2048f, 196.0894f, 76.2707f, 142.0220f, 85.3431f, 162.9909f,
	77.3750f, 28.6949f, 112.2925f, 79.5191f, -6.0851f, 58.1025f, 53.7721f, 87.5743f, 5.6429f, 39.7135f, 47.9949f, 86.0625f,
	37.5563f, 5.8879f, 73.6739f, 57.1568f, 48.8660f, 14.1653f, 73.0158f, 44.9480f, 58.0793f, 159.8937f, 113.0820f, 214.5573f,
	107.0385f, 69.7607f, 137.3566f, 105.4010f, 122.4620f, 51.0809f, 131.3896f, 102.2471f, 71.0835f, 135.3897f, 93.6408f, 156.4846f,
	79.2752f, 95.3835f, 84.2380f, 125.8137f, 37.0673f, 171.0514f, 49.9841f, 203.4046f, 116.6400f, 152.4634f, 118.6825f, 159.6572f,
	49.5364f, 83.6166f, 77.2799f, 108.1312f, -12.0070f, 47.7104f, 26.4309f, 102.8334f, 73.0529f, 178.2168f, 94.3071f, 216.4359f,
	81.9253f, 137.8156f, 107.7278f, 149.2885f, 16.3219f, 179.7427f, 73.9152f, 200.7352f, 91.8087f, 17.5434f, 137.1745f, 29.8480f,
	96.6991f, 168.8745f, 129.6096f, 171.3390f, 131.5065f, 99.5547f, 149.2944f, 155.2749f, 102.6283f, 10.6622f, 156.5511f, 38.1065f,
	123.0512f, 108.0793f, 137.9220f, 127.2239f, 53.1452f, 119.0642f, 73.3404f, 155.3743f, 130.1690f, 1.7448f, 184.8039f, 3.1763f,
	93.7074f, 82.1619f, 125.9504f, 99.5652f, 63.8853f, 143.8404f, 108.6820f, 186.3194f, 107.2755f, 39.8756f, 143.1295f, 78.2680f,
	52.3550f, 62.2463f, 91.9079f, 121.1729f, 93.2160f, 69.6623f, 111.8797f, 107.2634f, 139.7207f, 45.7991f, 154.9616f, 74.9719f,
	167.2671f, 160.7261f, 187.2941f, 206.6506f, 179.1259f, 129.1106f, 189.2970f, 183.4070f, 74.4343f, 0.3572f, 127.0189f, 43.8782f,
	95.1992f, 170.4922f, 112.9108f, 228.3217f, 142.9101f, 152.2709f, 177.0380f, 199.4092f, 39.0269f, 30.7110f, 86.7534f, 82.8523f,
	143.8537f, 163.5132f, 191.0993f, 171.2454f, 85.3959f, -0.8223f, 112.2607f, 43.3901f, 8.6218f, 186.3383f, 37.7209f, 213.3036f,
	-15.4319f, 116.3204f, 44.2555f, 149.9535f, 147.9980f, 110.2290f, 188.7993f, 149.8210f, -13.4183f, -11.0214f, 35.6454f, 47.1977f,
	28.9969f, 149.8616f, 83.2476f, 208.9517f, 43.0921f, -3.2028f, 90.5599f, 14.8026f, 28.6361f, 26.0199f, 40.5617f, 70.3113f,
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	136.7519f, 180.4197f, 194.1175f, 183.8356f, 155.6840f, 107.8222f, 186.9352f, 154.6854f, 61.1796f, -7.7136f, 87.7250f, 22.1787f,
	29.1652f, -28.4875f, 32.2799f, 30.6594f, 91.3547f, -3.8851f, 148.9814f, 24.5483f, 20.3959f, 91.8365f, 27.4731f, 150.5336f,
	71.2720f, 147.6549f, 74.6957f, 172.9379f, 183.9269f, 23.7969f, 199.4448f, 71.6242f, 196.6597f, 166.8796f, 201.5260f, 172.8839f,
	140.4950f, -5.4397f, 168.3470f, 28.3325f, 46.4677f, 136.0320f, 77.9169f, 184.3535f, 127.8122f, 157.7804f, 147.2538f, 213.3378f,
	139.0779f, 129.6555f, 143.0846f, 179.1879f, 73.7761f, 138.0335f, 81.3605f, 141.2148f, 116.3348f, 156.1013f, 140.0206f, 179.0908f,
	-0.1401f, 6.0937f, 4.4311f, 9.9669f, 20.7149f, 36.6326f, 62.9081f, 44.0802f, 98.4106f, 4.5632f, 111.6248f, 45.4062f,
	23.3391f, 79.3651f, 42.1614f, 122.4473f, 21.0547f, 125.7129f, 45.3081f, 172.3624f, 154.4709f, 99.9714f, 180.0508f, 152.0333f,
	197.2776f, 147.9130f, 198.3756f, 192.5394f, 107.3878f, 6.9169f, 115.0000f, 55.1683f, 141.8624f, 144.9798f, 193.7655f, 148.8687f,
	197.5280f, 31.1895f, 198.6007f, 46.0271f, 12.8282f, 35.3058f, 43.8101f, 72.9977f, 74.7088f, 116.1662f, 104.5894f, 167.7956f,
	68.1883f, 195.4082f, 88.8408f, 196.6737f, 2.7857f, 106.6272f, 29.2340f, 137.9903f, 127.5389f, -9.5799f, 174.5932f, 31.3800f,
	61.4403f, 121.8884f, 112.0713f, 124.6352f, 15.4868f, 35.9096f, 55.8899f, 68.2298f, 35.5922f, 56.6701f, 44.2246f, 72.3261f,
	163.1796f, 40.7751f, 180.4136f, 56.2181f, 177.9262f, 90.7157f, 187.1069f, 101.2297f, 33.5656f, 108.4211f, 51.2933f, 164.8822f,
	73.5555f, 18.9549f, 114.3649f, 72.3462f, 119.3443f, 42.7151f, 174.0536f, 89.5792f, 169.1987f, 170.3059f, 182.1476f, 201.8479f,
	59.3192f, -5.2591f, 92.3019f, 24.6868f, 82.2129f, 76.0264f, 124.5949f, 108.2814f, 119.7321f, 125.9828f, 176.9545f, 158.6404f,
	127.7304f, 16.7712f, 164.7240f, 43.4104f, 148.5664f, 5.0880f, 164.6177f, 13.8616f, 95.0352f, 23.4340f, 132.9384f, 31.8482f,
	10.9685f, 155.1733f, 30.8775f, 212.3560f, 151.4989f, -12.8680f, 210.0904f, 16.5719f, 160.8241f, 9.0448f, 185.4050f, 66.2840f,
	138.8994f, 0.9312f, 180.3396f, 11.5822f, 18.7873f, 5.2706f, 21.1577f, 38.9812f, 28.5777f, 117.4022f, 53.1813f, 130.6575f,
	122.4044f, 40.3588f, 175.0358f, 56.2967f, -13.8737f, 112.4558f, 23.1297f, 115.2290f, 182.2486f, 114.0300f, 209.4412f, 122.0482f,
	47.3188f, 142.3400f, 103.5391f, 197.4341f, 118.1700f, -9.0369f, 169.5550f, 10.9335f, 167.5089f, 152.2341f, 187.5196f, 189.1137f,
	62.3618f, 109.6059f, 95.4902f, 138.0417f, 48.8767f, 20.2354f, 78.7763f, 44.8620f, 102.5983f, 138.3968f, 140.8982f, 170.7781f,
	105.8416f, 165.0748f, 126.5542f, 177.1219f, 74.1239f, 21.1889f, 89.5320f, 80.5165f, 92.9311f, 159.1187f, 147.7788f, 208.3988f,
	159.3220f, 68.5139f, 214.8306f, 113.2691f, 68.1500f, 106.3565f, 118.9061f, 135.0133f, 9.9914f, 191.9200f, 68.7055f, 201.9398f,
	52.9639f, 44.6476f, 97.9184f, 99.9669f, 55.7637f, 152.0609f, 101.8791f, 173.2028f, 3.2253f, 61.7017f, 49.2181f, 65.6580f,
	17.8964f, 149.2418f, 47.2522f, 170.4436f, 122.9471f, 96.2103f, 150.8778f, 144.0833f, 60.3089f, 24.4012f, 75.4822f, 62.1410f,
	171.4575f, 60.1555f, 210.5018f, 105.4550f, 39.6844f, 39.6149f, 57.7543f, 87.4394f, 11.6796f, 8.8690f, 27.8902f, 22.3743f,
	132.9151f, -21.7847f, 168.4868f, 33.7186f, 163.6127f, 55.8750f, 188.8017f, 82.7164f, 48.6664f, -15.5441f, 62.5789f, 23.1577f,
	15.8440f, 32.5294f, 64.9913f, 33.6657f, 11.2664f, 115.2323f, 63.0400f, 174.8410f, 98.9553f, 132.8318f, 109.8496f, 150.4047f,
	92.9619f, 145.3852f, 94.4048f, 150.0469f, 41.4721f, 49.4119f, 62.3038f, 77.4494f, -14.9919f, 173.6975f, 33.0612f, 182.3103f,
	71.0426f, 113.7725f, 121.5539f, 123.7598f, 187.2858f, 6.0529f, 196.4472f, 44.3576f, 107.1609f, 16.6524f, 153.8468f, 40.8351f,
	95.1880f, 110.9244f, 103.0146f, 166.3137f, 10.1316f, 24.6737f, 34.1453f, 44.5039f, 20.5283f, 79.5362f, 80.4462f, 123.3809f,
	52.7734f, 184.2525f, 65.1362f, 212.4573f, 147.9188f, -19.1670f, 158.0026f, 20.7701f, 162.3696f, -14.8751f, 188.3148f, 21.5070f,
	161.5482f, 184.1698f, 199.1086f, 213.0640f, 168.8931f, 88.4010f, 224.9343f, 145.4546f, 167.0391f, 14.7719f, 225.9076f, 35.9920f,
	188.0454f, 173.7320f, 193.1542f, 185.1889f, 9.7935f, 155.5723f, 18.9354f, 196.5798f, 3.7319f, 81.7829f, 51.3855f, 132.6973f,
	52.4097f, 122.6709f, 69.3770f, 126.0459f, 83.9766f, 40.8733f, 137.1827f, 68.4016f, -0.6763f, -16.7244f, 39.4674f, 36.9323f,
	165.3600f, 96.2998f, 172.9588f, 141.5273f, 98.2916f, 29.1927f, 148.4108f, 88.7094f, 102.7704f, 116.5475f, 114.1754f, 148.9009f,
	20.0692f, 147.2792f, 46.0554f, 187.2189f, 33.8616f, -5.7911f, 67.4406f, 13.0553f, 16.7898f, 90.6905f, 47.3350f, 147.5951f,
	149.6448f, 34.9492f, 191.1284f, 57.5630f, 97.0913f, 152.4916f, 136.5998f, 197.0638f, 117.2606f, 38.3403f, 176.7911f, 63.1255f,
	29.2236f, 105.0804f, 89.1895f, 139.2277f, 58.5150f, 88.9746f, 89.9861f, 132.4418f, 77.6626f, 63.7197f, 84.2794f, 94.7469f,
	130.0316f, 108.2651f, 173.9744f, 162.7832f, 125.1590f, 132.2845f, 183.7822f, 158.0233f, 31.4721f, 93.7989f, 51.2533f, 132.9762f,
	174.2021f, 141.0848f, 202.4134f, 162.2841f, 11.1001f, 184.1428f, 37.1620f, 209.2240f, 177.2076f, 70.3730f, 181.2413f, 97.3360f,
	-0.2527f, 98.7053f, 40.4109f, 107.1279f, 41.9845f, -0.7119f, 63.8314f, 5.6998f, 145.5655f, 139.0148f, 193.0259f, 179.3967f,
	10.8509f, 84.2082f, 60.9460f, 123.8838f, 57.9873f, 61.5364f, 107.4399f, 101.6481f, 77.1802f, 17.7313f, 102.7635f, 19.8975f,
	39.0662f, 167.7982f, 59.0374f, 188.0644f, 119.4588f, 72.6661f, 164.6393f, 85.3368f, 146.1259f, 113.0609f, 194.4079f, 159.9718f,
	159.9229f, 3.9862f, 189.9071f, 55.7634f, 41.0200f, 184.5329f, 94.7088f, 200.0870f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 562 to 578 in 32c779d

	0.1439f, 0.8791f, 0.0961f, 0.1535f, 0.5338f, 0.0675f, 0.0528f, 0.0005f, 0.4363f, 0.7746f, 0.0348f, 0.6523f,
	0.8231f, 0.1680f, 0.1469f, 0.8608f, 0.8231f, 0.5389f, 0.8192f, 0.0928f, 0.3945f, 0.7378f, 0.2575f, 0.7523f,
	0.5042f, 0.7503f, 0.4647f, 0.3679f, 0.2192f, 0.2084f, 0.7515f, 0.1189f, 0.0860f, 0.1763f, 0.1753f, 0.8231f,
	0.3985f, 0.9904f, 0.1372f, 0.6535f, 0.4487f, 0.3929f, 0.8751f, 0.9756f, 0.8729f, 0.1923f, 0.2208f, 0.6561f,
	0.2891f, 0.7347f, 0.5664f, 0.5509f, 0.8285f, 0.7105f, 0.0266f, 0.0495f, 0.6016f, 0.4862f, 0.2602f, 0.4187f,
	0.7579f, 0.8266f, 0.5612f, 0.3854f, 0.2707f, 0.5219f, 0.3147f, 0.5641f, 0.6767f, 0.0661f, 0.0011f, 0.2123f,
	0.8945f, 0.6463f, 0.1720f, 0.8903f, 0.4700f, 0.4761f, 0.9355f, 0.0595f, 0.2152f, 0.5858f, 0.1955f, 0.6795f,
	0.2141f, 0.0992f, 0.2070f, 0.4227f, 0.1761f, 0.1347f, 0.8603f, 0.3204f, 0.3608f, 0.0553f, 0.3574f, 0.2648f,
	0.6105f, 0.2054f, 0.8884f, 0.9297f, 0.0998f, 0.1074f, 0.1153f, 0.6196f, 0.1220f, 0.8524f, 0.7543f, 0.8198f,
	0.5261f, 0.9967f, 0.0442f, 0.4013f, 0.3239f, 0.9486f, 0.5769f, 0.8062f, 0.1703f, 0.9786f, 0.4986f, 0.4937f,
	0.9709f, 0.3807f, 0.3975f, 0.5848f, 0.1281f, 0.3211f, 0.1932f, 0.1033f, 0.8661f, 0.5893f, 0.3587f, 0.4087f,
	0.4315f, 0.6331f, 0.9268f, 0.9328f, 0.3915f, 0.3293f, 0.4510f, 0.5679f, 0.4618f, 0.6588f, 0.5544f, 0.3207f,
	0.3457f, 0.3786f, 0.0946f, 0.1661f, 0.7231f, 0.3891f, 0.2145f, 0.5627f, 0.7555f, 0.2574f, 0.8268f, 0.9275f,
	0.5974f, 0.6689f, 0.0526f, 0.9455f, 0.3925f, 0.9239f, 0.5790f, 0.0046f, 0.0385f, 0.6804f, 0.5627f, 0.0265f,
	0.7435f, 0.8521f, 0.4964f, 0.4658f, 0.0055f, 0.7866f, 0.3307f, 0.8788f, 0.3731f, 0.5651f, 0.2703f, 0.1606f,
	0.7749f, 0.4966f, 0.5365f, 0.9654f, 0.9636f, 0.8556f, 0.1876f, 0.5943f, 0.8781f, 0.3745f, 0.1011f, 0.8110f,
	0.4818f, 0.5644f, 0.9821f, 0.6072f, 0.4250f, 0.3700f, 0.4176f, 0.1184f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 586 in 32c779d

std::vector<int64_t> gold = {0, 0, 37, 0, 0, 43, 0, 0, 78, 0, 0, 99, 0, 0, 72, 0, 0, 75, 0, 0, 98, 0, 0, 1, 0, 0, 42, 0, 0, 44, 0, 0, 15, 0, 0, 90, 0, 0, 52, 0, 0, 61, 0, 0, 12, 1, 0, 9, 1, 0, 94, 1, 0, 17, 1, 0, 20, 1, 0, 83, 1, 0, 84, 1, 0, 13, 1, 0, 59, 1, 0, 35, 1, 0, 55, 1, 0, 34, 1, 0, 61, 1, 0, 75, 1, 0, 88, 1, 0, 28};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 605 to 611 in 32c779d

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 615 to 624 in 32c779d

	31.2680f, 53.5348f, 37.7043f, 73.6253f, 1.8071f, 55.2945f, 3.9368f, 78.7402f, 40.5016f, 12.5670f, 45.0345f, 32.9366f,
	78.2552f, 12.9548f, 80.7117f, 35.6526f, 73.9527f, 67.9870f, 79.4405f, 71.9065f, -3.8066f, -7.7339f, 10.2705f, 11.5692f,
	45.4706f, 34.8613f, 67.4569f, 48.4119f, 17.4632f, 30.3439f, 30.8192f, 43.8443f, 64.5403f, 44.3725f, 79.9380f, 66.0477f,
	0.7877f, 1.3956f, 6.4307f, 24.7471f, 65.1632f, 44.8608f, 84.5766f, 62.0721f, 59.3935f, 24.0849f, 74.6026f, 36.1925f,
	-1.0372f, 43.7485f, 19.8379f, 55.2458f, -6.6257f, -1.7353f, 16.1976f, 8.1505f, 62.2758f, 32.2798f, 71.2775f, 41.5966f,
	10.9190f, 36.7777f, 14.0023f, 46.7824f, 39.6937f, 15.6139f, 45.8900f, 18.6783f, 67.7244f, 9.7794f, 78.7948f, 12.5604f,
	34.0204f, 5.6094f, 56.7713f, 24.5464f, 26.9281f, 21.9014f, 36.6292f, 33.1611f, 26.2374f, -3.4581f, 44.9652f, 18.9477f,
	-1.6661f, 68.2450f, 11.7649f, 83.3261f, 74.8979f, 31.4950f, 80.1025f, 33.3041f, 20.6639f, 62.4061f, 29.0408f, 67.0291f,
	7.1374f, 75.0864f, 23.1608f, 80.8203f, 14.6460f, -5.2621f, 31.1216f, 18.1798f, 71.6501f, 49.1185f, 82.6496f, 55.1487f,
	4.4135f, 63.2815f, 10.6723f, 76.1439f, 60.5823f, 39.4727f, 78.1862f, 62.0048f, 54.1855f, 22.5844f, 59.0696f, 46.0598f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 626 to 633 in 32c779d

	0.9367f, 0.1879f, 0.1073f, 0.4976f, 0.5195f, 0.5082f, 0.4367f, 0.9948f, 0.4863f, 0.4779f, 0.4218f, 0.0668f,
	0.5930f, 0.2280f, 0.6376f, 0.0508f, 0.9814f, 0.4690f, 0.8968f, 0.4756f, 0.0603f, 0.8222f, 0.6482f, 0.7818f,
	0.4282f, 0.6379f, 0.8562f, 0.6311f, 0.3477f, 0.6625f, 0.6719f, 0.9606f, 0.3709f, 0.4251f, 0.8121f, 0.5058f,
	0.7366f, 0.4597f, 0.2155f, 0.7452f, 0.1312f, 0.1986f, 0.6268f, 0.7473f, 0.8947f, 0.2726f, 0.1107f, 0.9560f,
	0.1544f, 0.1977f, 0.2913f, 0.5294f, 0.8828f, 0.7605f, 0.7082f, 0.1752f, 0.3577f, 0.4784f, 0.1474f, 0.2734f,
	0.3083f, 0.1273f, 0.5502f, 0.7050f, 0.0699f, 0.4811f, 0.7822f, 0.7480f, 0.8151f, 0.4482f, 0.8206f, 0.2408f,
	0.3608f, 0.1764f, 0.4675f, 0.3921f, 0.2409f, 0.7518f, 0.3138f, 0.2728f, 0.1309f, 0.4388f, 0.3030f, 0.3693f,
	0.2360f, 0.7632f, 0.9300f, 0.4979f, 0.6430f, 0.8672f};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 641 in 32c779d

std::vector<int64_t> gold = {0, 0, 7, 0, 0, 16, 0, 0, 0, 0, 0, 18, 0, 0, 26, 0, 1, 1, 0, 1, 17, 0, 1, 14, 0, 1, 22, 0, 1, 4, 0, 2, 26, 0, 2, 29, 0, 2, 10, 0, 2, 6, 0, 2, 25};

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 660 to 666 in 32c779d

	auto nms =
	mm->add_instruction(migraphx::make_op("nonmaxsuppression"),
	boxes_p,
	scores_p,
	max_out_l,
	iou_threshold,
	score_threshold);

---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 670 to 803 in 32c779d

	132.1894f, 453.1169f, 199.9736f, 545.7127f, 64.3090f, 275.1729f, 104.8258f, 338.3436f, 76.1273f, 401.7875f, 135.6448f, 487.9920f,
	12.8305f, 442.3624f, 77.1708f, 466.2458f, -5.9609f, 340.1129f, 126.0715f, 451.3386f, 15.0119f, 224.3769f, 56.2927f, 236.5545f,
	427.8277f, -14.2917f, 561.9954f, 95.4457f, 4.7940f, -55.8461f, 69.2637f, 71.6517f, 41.3494f, 202.9014f, 91.1927f, 274.2992f,
	375.6902f, 208.6749f, 451.5645f, 285.6396f, 258.4982f, 179.9212f, 321.7420f, 227.4412f, 367.5344f, 211.3590f, 406.8828f, 356.8083f,
	277.5064f, 220.9636f, 353.4056f, 331.1991f, 429.2783f, 390.3169f, 452.8968f, 446.2962f, 292.5150f, 40.8054f, 345.9525f, 67.8517f,
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---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Lines 805 to 871 in 32c779d

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---

[format.py] _{reported by reviewdog 🐶}

AMDMIGraphX/test/gpu/nonmaxsuppression.cpp

Line 879 in 32c779d

std::vector<int64_t> gold = {0, 0, 143, 0, 0, 10, 0, 0, 13, 0, 0, 0, 0, 0, 90, 0, 0, 135, 0, 0, 1, 0, 0, 76, 0, 0, 108, 0, 0, 170, 0, 0, 140, 0, 0, 20, 0, 0, 151, 0, 0, 150, 0, 0, 39, 0, 0, 44, 0, 0, 41, 0, 0, 82, 0, 0, 80, 0, 0, 88, 0, 0, 16, 0, 0, 27, 0, 0, 167, 0, 0, 165, 0, 0, 181, 0, 1, 187, 0, 1, 94, 0, 1, 152, 0, 1, 72, 0, 1, 32, 0, 1, 153, 0, 1, 109, 0, 1, 150, 0, 1, 19, 0, 1, 27, 0, 1, 96, 0, 1, 35, 0, 1, 197, 0, 1, 68, 0, 1, 22, 0, 1, 154, 0, 1, 17, 0, 1, 117, 0, 1, 43, 0, 1, 97, 0, 1, 10, 0, 1, 180, 0, 1, 182, 0, 1, 67, 0, 1, 44, 1, 0, 35, 1, 0, 152, 1, 0, 175, 1, 0, 4, 1, 0, 71, 1, 0, 166, 1, 0, 127, 1, 0, 38, 1, 0, 170, 1, 0, 44, 1, 0, 158, 1, 0, 198, 1, 0, 24, 1, 0, 101, 1, 0, 171, 1, 0, 2, 1, 0, 53, 1, 0, 102, 1, 0, 66, 1, 0, 140, 1, 0, 37, 1, 0, 98, 1, 0, 115, 1, 0, 150, 1, 0, 6, 1, 1, 114, 1, 1, 196, 1, 1, 0, 1, 1, 126, 1, 1, 124, 1, 1, 19, 1, 1, 11, 1, 1, 26, 1, 1, 84, 1, 1, 191, 1, 1, 117, 1, 1, 104, 1, 1, 197, 1, 1, 192, 1, 1, 10, 1, 1, 48, 1, 1, 68, 1, 1, 22, 1, 1, 128, 1, 1, 25, 1, 1, 134, 1, 1, 163, 1, 1, 121, 1, 1, 169, 1, 1, 185};

[codecov]

Codecov Report

❌ Patch coverage is 76.00000% with 6 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
src/onnx/parse_nonmaxsuppression.cpp	55.56%	4 Missing ⚠️
src/include/migraphx/op/nonmaxsuppression.hpp	85.71%	2 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #4893      +/-   ##
===========================================
+ Coverage    92.88%   92.89%   +0.01%     
===========================================
  Files          587      587              
  Lines        30348    30350       +2     
===========================================
+ Hits         28187    28193       +6     
+ Misses        2161     2157       -4     

Files with missing lines	Coverage Δ
src/include/migraphx/shape.hpp	90.70% <ø> (ø)
src/onnx/include/migraphx/onnx/onnx_parser.hpp	100.00% <ø> (ø)
src/onnx/onnx.cpp	100.00% <ø> (ø)
src/shape.cpp	93.48% <100.00%> (+1.13%)	⬆️
src/include/migraphx/op/nonmaxsuppression.hpp	91.60% <85.71%> (-0.19%)	⬇️
src/onnx/parse_nonmaxsuppression.cpp	66.67% <55.56%> (-33.33%)	⬇️

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

[Copilot]

Pull request overview

Adds a GPU implementation of ONNX NonMaxSuppression (NMS) and refactors the core nonmaxsuppression op to better represent “dynamic” output sizing in MIGraphX IR by returning a tuple {indices, num_selected} (with optional slicing applied by the ONNX parser).

Changes:

• Introduces a 3-stage GPU NMS pipeline (gpu::nms_sort → gpu::nms_filter → gpu::nms_compact) with new kernels and JIT compilers, and updates GPU lowering to select the pipeline for static shapes (ref fallback for dynamic inputs).
• Refactors op::nonmaxsuppression to always return a tuple (raw indices + selected count) and updates ONNX parsing/tests to extract (and optionally slice) the indices output.
• Renames shape tuple flattening helper to flatten_shapes and updates GPU JIT paths to use it; adds/updates documentation and tests (including new GPU NMS tests).

Reviewed changes

Copilot reviewed 33 out of 35 changed files in this pull request and generated 6 comments.

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File	Description
test/verify/test_nms.cpp	Removes legacy verify-based NMS tests.
test/ref/nonmaxsuppression.cpp	Updates ref tests to slice indices using the tuple’s num_selected.
test/op_shape_test.cpp	Updates NMS shape expectations to a tuple {indices, num_selected}.
test/onnx/parse/nms_use_dyn_output_false_test.cpp	Removes test tied to removed use_dyn_output option/behavior.
test/onnx/parse/nms_test.cpp	Updates ONNX parse test to extract tuple elem 0 (indices).
test/onnx/parse/nms_dynamic_classes_test.cpp	Updates dynamic-classes parse test for tuple-return NMS.
test/onnx/parse/nms_dynamic_boxes_test.cpp	Updates dynamic-boxes parse test for tuple-return NMS.
test/onnx/parse/nms_dynamic_batch_test.cpp	Updates dynamic-batch parse test for tuple-return NMS.
test/onnx/gen_onnx.py	Removes custom use_dyn_output attribute generation in NMS ONNX test models.
test/multi_target/multitarget_test.cpp	Updates multitarget test to slice indices using tuple count.
test/gpu/nonmaxsuppression.cpp	Adds extensive GPU NMS functional tests (plus a dynamic-shape fallback test).
src/targets/gpu/nms_ops.cpp	Adds new internal GPU ops (gpu::nms_sort/filter/compact) and their shapes.
src/targets/gpu/lowering.cpp	Lowers nonmaxsuppression to the GPU pipeline for static shapes; ref fallback for dynamic.
src/targets/gpu/kernels/include/migraphx/kernels/sort.hpp	Adds block-wide bitonic sort helpers used by NMS kernels.
src/targets/gpu/kernels/include/migraphx/kernels/nonmaxsuppression.hpp	Adds GPU kernel implementations for sort/filter/compact stages.
src/targets/gpu/jit/topk.cpp	Switches to flatten_shapes when building HIP compile inputs.
src/targets/gpu/jit/reduce.cpp	Switches to flatten_shapes when building HIP compile inputs.
src/targets/gpu/jit/pointwise.cpp	Switches to flatten_shapes when building HIP compile inputs.
src/targets/gpu/jit/nonmaxsuppression.cpp	Adds JIT compilers for gpu::nms_sort/filter/compact kernels.
src/targets/gpu/include/migraphx/gpu/compile_hip_code_object.hpp	Clarifies meaning of global/local fields in compile options.
src/targets/gpu/device/include/migraphx/gpu/device/scan.hpp	Adds/clarifies block scan documentation/overload.
src/targets/gpu/compile_hip_code_object.cpp	Documents compute_block_size intent.
src/targets/gpu/code_object_op.cpp	Uses flatten_shapes for shape compatibility checks with tuple inputs.
src/targets/gpu/CMakeLists.txt	Adds nms_ops.cpp to GPU target build.
src/shape.cpp	Renames shape flattening helper to flatten_shapes.
src/onnx/parse_nonmaxsuppression.cpp	Parses NMS as tuple-return op and optionally slices indices under MIGRAPHX_USE_DYNAMIC_NMS.
src/onnx/onnx.cpp	Removes propagation of removed use_dyn_output option into parser.
src/onnx/include/migraphx/onnx/onnx_parser.hpp	Removes onnx_parser::use_dyn_output member.
src/include/migraphx/shape.hpp	Renames public API flatten → flatten_shapes.
src/include/migraphx/op/nonmaxsuppression.hpp	Refactors NMS op to return tuple {indices, num_selected} and adds runtime shape validation.
src/include/migraphx/onnx.hpp	Removes public onnx_options::use_dyn_output.
docs/reference/MIGraphX-dev-env-vars.rst	Documents MIGRAPHX_USE_DYNAMIC_NMS env var behavior.
docs/dev/onnx_operators.rst	Updates operator matrix entry for NonMaxSuppression.

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[format.py] _{reported by reviewdog 🐶}

Suggested change

	const auto aligned_b = bit_ceil(static_cast<std::uint64_t>(num_boxes));
	const auto aligned_b = bit_ceil(static_cast<std::uint64_t>(num_boxes));