// Copyright 2022 Google LLC // // This source code is licensed under the BSD-style license found in the // LICENSE file in the root directory of this source tree. #include #include #include #include #include #include TEST(PACK_QU8_DWCONV_GHW_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qu8_packing_params params = { .input_zero_point = 127, .kernel_zero_point = 127, }; xnn_pack_qu8_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); const int32_t bias_offset = h * w * params.input_zero_point * params.kernel_zero_point; ASSERT_EQ(bias_offset, 48387); std::vector expected = { // bias first // 48387 + 0 - (2 + 3 + 4) * 127 = 47,244 = 0xB88C 0x8C, 0xB8, 0, 0, // 48387 + 1 - (5 + 6 + 7) * 127 = 46,102 = 0xB416 0x16, 0xB4, 0, 0, // then weights, channels first 2, 5, 3, 6, 4, 7, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QU8_DWCONV_GHW_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, // 8, 9, 10, // 11, 12, 13, // 14, 15, 16, // 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qu8_packing_params params = { .input_zero_point = 127, .kernel_zero_point = 127, }; xnn_pack_qu8_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); const int32_t bias_offset = h * w * params.input_zero_point * params.kernel_zero_point; ASSERT_EQ(bias_offset, 48387); std::vector expected = { // cr blocks // bias first (cr == 2 of them) // 48387 + 0 - (5 + 6 + 7) * 127 = 46,101 = 0xB415 0x15, 0xB4, 0, 0, // 48387 + 1 - (8 + 9 + 10) * 127 = 44,959 = 0xAF9F 0x9F, 0xAF, 0, 0, // then weights, channels first 5, 8, 6, 9, 7, 10, // bias again // 48387 + 2 - (11 + 12 + 13) * 127 = 43,817 = 0xAB29 0x29, 0xAB, 0, 0, // 48387 + 3 - (14 + 15 + 16) * 127 = 42,675 = 0xA6B3 0xB3, 0xA6, 0, 0, // then weights, channels first 11, 14, 12, 15, 13, 16, // bias again // 48387 + 4 - (17 + 18 + 19) * 127 = 41,533 = 0xA23D 0x3D, 0xA2, 0, 0, 0, 0, 0, 0, // then weights, channels first 17, 0, 18, 0, 19, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QU8_DWCONV_GHW_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qu8_packing_params params = { .input_zero_point = 127, .kernel_zero_point = 127, }; xnn_pack_qu8_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); const int32_t bias_offset = h * w * params.input_zero_point * params.kernel_zero_point; ASSERT_EQ(bias_offset, 64516); std::vector expected = { // bias first (cr == 2 of them) // 64516 + 0 - (2 + 3 + 4 + 5) * 127 = 62,738 = 0xF512 0x12, 0xF5, 0, 0, // 64516 + 1 - (6 + 7 + 8 + 9) * 127 = 60,707 = 0xED23 0x23, 0xED, 0, 0, // then weights, channels first 2, 6, // go down the columns first 4, 8, 3, 7, 5, 9, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QU8_DWCONV_GHW_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, // 7, 8, // 9, 10, // 11, 12, // 13, 14, // 15, 16, // 17, 18, // 19, 20, // 21, 22, // 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qu8_packing_params params = { .input_zero_point = 127, .kernel_zero_point = 127, }; xnn_pack_qu8_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); const int32_t bias_offset = h * w * params.input_zero_point * params.kernel_zero_point; ASSERT_EQ(bias_offset, 64516); std::vector expected = { // bias first (cr == 2 of them) // 64516 + 0 - (5 + 6 + 7 + 8) * 127 = 61,214 = 0xEF1E 0x1E, 0xEF, 0, 0, // 64516 + 1 - (9 + 10 + 11 + 12) * 127 = 59,183 = 0xE72F 0x2F, 0xE7, 0, 0, // then weights, channels first 5, 9, // go down the columns first 7, 11, 6, 10, 8, 12, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias first (cr == 2 of them) // 64516 + 2 - (13 + 14 + 15 + 16) * 127 = 57,152 = 0xDF40 0x40, 0xDF, 0, 0, // 64516 + 3 - (17 + 18 + 19 + 20) * 127 = 55,121 = 0xD751 0x51, 0xD7, 0, 0, // then weights, channels first 13, 17, 15, 19, 14, 18, 16, 20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias // 64516 + 4 - (21 + 22 + 23 + 24) * 127 = 53,090 = 0xCF62 0x62, 0xCF, 0, 0, 0, 0, 0, 0, // weights 21, 0, 23, 0, 22, 0, 24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QU8_DWCONV_HWG_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qu8_packing_params params = { .input_zero_point = 127, .kernel_zero_point = 127, }; xnn_pack_qu8_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); const int32_t bias_offset = h * w * params.input_zero_point * params.kernel_zero_point; ASSERT_EQ(bias_offset, 48387); std::vector expected = { // bias first // 48387 + 0 - (2 + 4 + 6) * 127 = 46,863 = 0xB70F 0x0F, 0xB7, 0, 0, // 48387 + 1 - (3 + 5 + 7) * 127 = 46,483 = 0xB593 0x93, 0xB5, 0, 0, // then weights, channels first 2, 3, 4, 5, 6, 7, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QU8_DWCONV_HWG_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qu8_packing_params params = { .input_zero_point = 127, .kernel_zero_point = 127, }; xnn_pack_qu8_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); const int32_t bias_offset = h * w * params.input_zero_point * params.kernel_zero_point; ASSERT_EQ(bias_offset, 48387); std::vector expected = { // cr blocks // bias first (cr == 2 of them) // 48387 + 0 - (5 + 10 + 15) * 127 = 44577 = 0xAE21 0x21, 0xAE, 0, 0, // 48387 + 1 - (6 + 11 + 16) * 127 = 44197 = 0xACA5 0xA5, 0xAC, 0, 0, // then weights, channels first 5, 6, 10, 11, 15, 16, // bias again // 48387 + 2 - (7, 12, 17) * 127 = 43817 = 0xAB29 0x29, 0xAB, 0, 0, // 48387 + 3 - (8, 13, 18) * 127 = 43434 = 0xA9AD 0xAD, 0xA9, 0, 0, // then weights, channels first 7, 8, 12, 13, 17, 18, // bias again // 48387 + 4 - (9, 14, 19) * 127 = 43053 = 0xA831 0x31, 0xA8, 0, 0, 0, 0, 0, 0, // then weights, channels first 9, 0, 14, 0, 19, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QU8_DWCONV_HWG_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qu8_packing_params params = { .input_zero_point = 127, .kernel_zero_point = 127, }; xnn_pack_qu8_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); const int32_t bias_offset = h * w * params.input_zero_point * params.kernel_zero_point; ASSERT_EQ(bias_offset, 64516); std::vector expected = { // bias first (cr == 2 of them) // 64516 + 0 - (2 + 4 + 6 + 8) * 127 = 61976 = 0xF218 0x18, 0xF2, 0, 0, // 64516 + 1 - (3 + 5 + 7 + 9) * 127 = 61469 = 0xF01D 0x1D, 0xF0, 0, 0, // then weights, channels first 2, 3, // go down the columns first 6, 7, 4, 5, 8, 9, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QU8_DWCONV_HWG_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19, // 20, 21, 22, 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qu8_packing_params params = { .input_zero_point = 127, .kernel_zero_point = 127, }; xnn_pack_qu8_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); const int32_t bias_offset = h * w * params.input_zero_point * params.kernel_zero_point; ASSERT_EQ(bias_offset, 64516); std::vector expected = { // bias first (cr == 2 of them) // 64516 + 0 - (5 + 10 + 15 + 20) * 127 = 58166 = 0xE336 0x36, 0xE3, 0, 0, // 64516 + 1 - (6 + 11 + 16 + 21) * 127 = 57659 = 0xE13B 0x3B, 0xE1, 0, 0, // then weights, channels first 5, 6, // go down the columns first 15, 16, 10, 11, 20, 21, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias first (cr == 2 of them) // 64516 + 2 - (7 + 12 + 17 + 22) * 127 = 57152 = 0xDF40 0x40, 0xDF, 0, 0, // 64516 + 3 - (8 + 13 + 18 + 23) * 127 = 56645 = 0xDD45 0x45, 0xDD, 0, 0, // then weights, channels first 7, 8, 17, 18, 12, 13, 22, 23, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias // 64516 + 4 - (9 + 14 + 19 + 24) * 127 = 56138 = 0xDB4A 0x4A, 0xDB, 0, 0, 0, 0, 0, 0, // weights 9, 0, 19, 0, 14, 0, 24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QS8_DWCONV_GHW_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qs8_packing_params params = { .input_zero_point = 127, }; xnn_pack_qs8_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); std::vector expected = { // bias first // (2 + 3 + 4) * 127 = -1143 = 0xFFFFFB89 0x89, 0xFB, 0xFF, 0xFF, // (5 + 6 + 7) * 127 = -2285 = 0xFFFFF713 0x13, 0xF7, 0xFF, 0xFF, // then weights, channels first 2, 5, 3, 6, 4, 7, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QS8_DWCONV_GHW_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, // 8, 9, 10, // 11, 12, 13, // 14, 15, 16, // 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qs8_packing_params params = { .input_zero_point = 127, }; xnn_pack_qs8_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); std::vector expected = { // cr blocks // bias first (cr == 2 of them) // 0 - (5 + 6 + 7) * 127 = -2286 = 0xFFFFF712 0x12, 0xF7, 0xFF, 0xFF, // 1 - (8 + 9 + 10) * 127 = -3428 = 0xFFFFF29C 0x9C, 0xF2, 0xFF, 0xFF, // then weights, channels first 5, 8, 6, 9, 7, 10, // bias again // 2 - (11 + 12 + 13) * 127 = -4570 = 0xFFFFEE26 0x26, 0xEE, 0xFF, 0xFF, // 3 - (14 + 15 + 16) * 127 = -5712 = 0xFFFFE9B0 0xB0, 0xE9, 0xFF, 0xFF, // then weights, channels first 11, 14, 12, 15, 13, 16, // bias again // 4 - (17 + 18 + 19) * 127 = -6854 = 0xFFFFE53A 0x3A, 0xE5, 0xFF, 0xFF, 0, 0, 0, 0, // then weights, channels first 17, 0, 18, 0, 19, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QS8_DWCONV_GHW_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qs8_packing_params params = { .input_zero_point = 127, }; xnn_pack_qs8_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); std::vector expected = { // bias first (cr == 2 of them) // 0 - (2 + 3 + 4 + 5) * 127 = -1778 = 0xFFFFF90E 0x0E, 0xF9, 0xFF, 0xFF, // 1 - (6 + 7 + 8 + 9) * 127 = -3809 = 0xFFFFF11F 0x1F, 0xF1, 0xFF, 0xFF, // then weights, channels first 2, 6, // go down the columns first 4, 8, 3, 7, 5, 9, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QS8_DWCONV_GHW_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, // 7, 8, // 9, 10, // 11, 12, // 13, 14, // 15, 16, // 17, 18, // 19, 20, // 21, 22, // 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qs8_packing_params params = { .input_zero_point = 127, }; xnn_pack_qs8_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); std::vector expected = { // bias first (cr == 2 of them) // 0 - (5 + 6 + 7 + 8) * 127 = -3302 = 0xFFFFF31A 0x1A, 0xF3, 0xFF, 0xFF, // 1 - (9 + 10 + 11 + 12) * 127 = -5333 = 0xFFFFEB2B 0x2B, 0xEB, 0xFF, 0xFF, // then weights, channels first 5, 9, // go down the columns first 7, 11, 6, 10, 8, 12, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias first (cr == 2 of them) // 2 - (13 + 14 + 15 + 16) * 127 = -7364 = 0xFFFFE33C 0x3C, 0xE3, 0xFF, 0xFF, // 3 - (17 + 18 + 19 + 20) * 127 = -9395 = 0xFFFFDB4D 0x4D, 0xDB, 0xFF, 0xFF, // then weights, channels first 13, 17, 15, 19, 14, 18, 16, 20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias // 4 - (21 + 22 + 23 + 24) * 127 = -11426 = 0xFFFFD35E 0x5E, 0xD3, 0xFF, 0xFF, 0, 0, 0, 0, // weights 21, 0, 23, 0, 22, 0, 24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QS8_DWCONV_HWG_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qs8_packing_params params = { .input_zero_point = 127, }; xnn_pack_qs8_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); std::vector expected = { // bias first // 0 - (2 + 4 + 6) * 127 = -1524 = 0xFFFFFA0C 0x0C, 0xFA, 0xFF, 0xFF, // 1 - (3 + 5 + 7) * 127 = -1904 = 0xFFFFF890 0x90, 0xF8, 0xFF, 0xFF, // then weights, channels first 2, 3, 4, 5, 6, 7, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QS8_DWCONV_HWG_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qs8_packing_params params = { .input_zero_point = 127, }; xnn_pack_qs8_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); std::vector expected = { // cr blocks // bias first (cr == 2 of them) // 0 - (5 + 10 + 15) * 127 = -3810 = 0xFFFFF11E 0x1E, 0xF1, 0xFF, 0xFF, // 1 - (6 + 11 + 16) * 127 = -4190 = 0xFFFFEFA2 0xA2, 0xEF, 0xFF, 0xFF, // then weights, channels first 5, 6, 10, 11, 15, 16, // bias again // 2 - (7, 12, 17) * 127 = -45709 = 0xFFFFEE26 0x26, 0xEE, 0xFF, 0xFF, // 3 - (8, 13, 18) * 127 = -4950 = 0xFFFFECAA 0xAA, 0xEC, 0xFF, 0xFF, // then weights, channels first 7, 8, 12, 13, 17, 18, // bias again // 4 - (9, 14, 19) * 127 = -5330 = 0xFFFFEB2E 0x2E, 0xEB, 0xFF, 0xFF, 0, 0, 0, 0, // then weights, channels first 9, 0, 14, 0, 19, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QS8_DWCONV_HWG_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qs8_packing_params params = { .input_zero_point = 127, }; xnn_pack_qs8_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); std::vector expected = { // bias first (cr == 2 of them) // 0 - (2 + 4 + 6 + 8) * 127 = -2540 = 0xFFFFF614 0x14, 0xF6, 0xFF, 0xFF, // 1 - (3 + 5 + 7 + 9) * 127 = -3047 = 0xFFFFF419 0x19, 0xF4, 0xFF, 0xFF, // then weights, channels first 2, 3, // go down the columns first 6, 7, 4, 5, 8, 9, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_QS8_DWCONV_HWG_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19, // 20, 21, 22, 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + sizeof(int32_t)/sizeof(uint8_t)) * round_up_po2(c, cr))); xnn_qs8_packing_params params = { .input_zero_point = 127, }; xnn_pack_qs8_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, ¶ms); std::vector expected = { // bias first (cr == 2 of them) // 0 - (5 + 10 + 15 + 20) * 127 = -6350 = 0xFFFFE732 0x32, 0xE7, 0xFF, 0xFF, // 1 - (6 + 11 + 16 + 21) * 127 = -6857 = 0xFFFFE537 0x37, 0xE5, 0xFF, 0xFF, // then weights, channels first 5, 6, // go down the columns first 15, 16, 10, 11, 20, 21, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias first (cr == 2 of them) // 2 - (7 + 12 + 17 + 22) * 127 = -7364 = 0xFFFFE33C 0x3C, 0xE3, 0xFF, 0xFF, // 3 - (8 + 13 + 18 + 23) * 127 = -7871 = 0xFFFFE141 0x41, 0xE1, 0xFF, 0xFF, // then weights, channels first 7, 8, 17, 18, 12, 13, 22, 23, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias // 4 - (9 + 14 + 19 + 24) * 127 = -8378 = 0xFFFFDF46 0x46, 0xDF, 0xFF, 0xFF, 0, 0, 0, 0, // weights 9, 0, 19, 0, 14, 0, 24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F16_DWCONV_GHW_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f16_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first 0, 1, // then weights, channels first 2, 5, 3, 6, 4, 7, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F16_DWCONV_GHW_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, // 8, 9, 10, // 11, 12, 13, // 14, 15, 16, // 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f16_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // cr blocks // bias first (cr == 2 of them) 0, 1, // then weights, channels first 5, 8, 6, 9, 7, 10, // bias again 2, 3, // then weights, channels first 11, 14, 12, 15, 13, 16, // bias again 4, 0, // then weights, channels first 17, 0, 18, 0, 19, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F16_DWCONV_GHW_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f16_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first (cr == 2 of them) 0, 1, // then weights, channels first 2, 6, // go down the columns first 4, 8, 3, 7, 5, 9, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F16_DWCONV_GHW_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, // 7, 8, // 9, 10, // 11, 12, // 13, 14, // 15, 16, // 17, 18, // 19, 20, // 21, 22, // 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f16_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first (cr == 2 of them) 0, 1, // then weights, channels first 5, 9, // go down the columns first 7, 11, 6, 10, 8, 12, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias first (cr == 2 of them) 2, 3, // then weights, channels first 13, 17, 15, 19, 14, 18, 16, 20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias 4, 0, // weights 21, 0, 23, 0, 22, 0, 24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F16_DWCONV_HWG_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f16_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first 0, 1, // then weights, channels first 2, 3, 4, 5, 6, 7, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F16_DWCONV_HWG_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f16_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // cr blocks // bias first (cr == 2 of them) 0, 1, // then weights, channels first 5, 6, 10, 11, 15, 16, // bias again 2, 3, // then weights, channels first 7, 8, 12, 13, 17, 18, // bias again 4, 0, // then weights, channels first 9, 0, 14, 0, 19, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F16_DWCONV_HWG_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f16_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first (cr == 2 of them) 0, 1, // then weights, channels first 2, 3, // go down the columns first 6, 7, 4, 5, 8, 9, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F16_DWCONV_HWG_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19, // 20, 21, 22, 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f16_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first (cr == 2 of them) 0, 1, // then weights, channels first 5, 6, // go down the columns first 15, 16, 10, 11, 20, 21, // followed by 10 zeros to make up the difference with primary_tile 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias first (cr == 2 of them) 2, 3, // then weights, channels first 7, 8, 17, 18, 12, 13, 22, 23, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, // bias 4, 0, // weights 9, 0, 19, 0, 14, 0, 24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_DWCONV_GHW_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first 0.0f, 1.0f, // then weights, channels first 2.0f, 5.0f, 3.0f, 6.0f, 4.0f, 7.0f, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_DWCONV_GHW_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, // 8, 9, 10, // 11, 12, 13, // 14, 15, 16, // 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // cr blocks // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 5.0f, 8.0f, 6.0f, 9.0f, 7.0f, 10.0f, // bias again 2.0f, 3.0f, // then weights, channels first 11.0f, 14.0f, 12.0f, 15.0f, 13.0f, 16.0f, // bias again 4.0f, 0.0f, // then weights, channels first 17.0f, 0.0f, 18.0f, 0.0f, 19.0f, 0.0f, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_DWCONV_GHW_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 2.0f, 6.0f, // go down the columns first 4.0f, 8.0f, 3.0f, 7.0f, 5.0f, 9.0f, // followed by 10 zeros to make up the difference with primary_tile 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_DWCONV_GHW_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, // 7, 8, // 9, 10, // 11, 12, // 13, 14, // 15, 16, // 17, 18, // 19, 20, // 21, 22, // 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 5.0f, 9.0f, // go down the columns first 7.0f, 11.0f, 6.0f, 10.0f, 8.0f, 12.0f, // followed by 10 zeros to make up the difference with primary_tile 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, // bias first (cr == 2 of them) 2.0f, 3.0f, // then weights, channels first 13.0f, 17.0f, 15.0f, 19.0f, 14.0f, 18.0f, 16.0f, 20.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, // bias 4.0f, 0.0f, // weights 21.0f, 0.0f, 23.0f, 0.0f, 22.0f, 0.0f, 24.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_DWCONV_HWG_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first 0.0f, 1.0f, // then weights, channels first 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_DWCONV_HWG_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // cr blocks // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 5.0f, 6.0f, 10.0f, 11.0f, 15.0f, 16.0f, // bias again 2.0f, 3.0f, // then weights, channels first 7.0f, 8.0f, 12.0f, 13.0f, 17.0f, 18.0f, // bias again 4.0f, 0.0f, // then weights, channels first 9.0f, 0.0f, 14.0f, 0.0f, 19.0f, 0.0f, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_DWCONV_HWG_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 2.0f, 3.0f, // go down the columns first 6.0f, 7.0f, 4.0f, 5.0f, 8.0f, 9.0f, // followed by 10 zeros to make up the difference with primary_tile 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_DWCONV_HWG_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19, // 20, 21, 22, 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected = { // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 5.0f, 6.0f, // go down the columns first 15.0f, 16.0f, 10.0f, 11.0f, 20.0f, 21.0f, // followed by 10 zeros to make up the difference with primary_tile 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, // bias first (cr == 2 of them) 2.0f, 3.0f, // then weights, channels first 7.0f, 8.0f, 17.0f, 18.0f, 12.0f, 13.0f, 22.0f, 23.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, // bias 4.0f, 0.0f, // weights 9.0f, 0.0f, 19.0f, 0.0f, 14.0f, 0.0f, 24.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, }; ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_TO_F16_DWCONV_GHW_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_to_f16_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected_float = { // bias first 0.0f, 1.0f, // then weights, channels first 2.0f, 5.0f, 3.0f, 6.0f, 4.0f, 7.0f, }; std::vector expected(expected_float.size()); std::transform(expected_float.begin(), expected_float.end(), expected.begin(), [](float f) { return fp16_ieee_from_fp32_value(f); }); ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_TO_F16_DWCONV_GHW_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, // 8, 9, 10, // 11, 12, 13, // 14, 15, 16, // 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_to_f16_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected_float = { // cr blocks // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 5.0f, 8.0f, 6.0f, 9.0f, 7.0f, 10.0f, // bias again 2.0f, 3.0f, // then weights, channels first 11.0f, 14.0f, 12.0f, 15.0f, 13.0f, 16.0f, // bias again 4.0f, 0.0f, // then weights, channels first 17.0f, 0.0f, 18.0f, 0.0f, 19.0f, 0.0f, }; std::vector expected(expected_float.size()); std::transform(expected_float.begin(), expected_float.end(), expected.begin(), [](float f) { return fp16_ieee_from_fp32_value(f); }); ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_TO_F16_DWCONV_GHW_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_to_f16_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected_float = { // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 2.0f, 6.0f, // go down the columns first 4.0f, 8.0f, 3.0f, 7.0f, 5.0f, 9.0f, // followed by 10 zeros to make up the difference with primary_tile 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, }; std::vector expected(expected_float.size()); std::transform(expected_float.begin(), expected_float.end(), expected.begin(), [](float f) { return fp16_ieee_from_fp32_value(f); }); ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_TO_F16_DWCONV_GHW_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, // 7, 8, // 9, 10, // 11, 12, // 13, 14, // 15, 16, // 17, 18, // 19, 20, // 21, 22, // 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_to_f16_dwconv_ghw_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected_float = { // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 5.0f, 9.0f, // go down the columns first 7.0f, 11.0f, 6.0f, 10.0f, 8.0f, 12.0f, // followed by 10 zeros to make up the difference with primary_tile 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, // bias first (cr == 2 of them) 2.0f, 3.0f, // then weights, channels first 13.0f, 17.0f, 15.0f, 19.0f, 14.0f, 18.0f, 16.0f, 20.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, // bias 4.0f, 0.0f, // weights 21.0f, 0.0f, 23.0f, 0.0f, 22.0f, 0.0f, 24.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, }; std::vector expected(expected_float.size()); std::transform(expected_float.begin(), expected_float.end(), expected.begin(), [](float f) { return fp16_ieee_from_fp32_value(f); }); ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_TO_F16_DWCONV_HWG_W, primary_tile_eq_kernel_size) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [2, 3, 4, 5, 6, 7] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_to_f16_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected_float = { // bias first 0.0f, 1.0f, // then weights, channels first 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, }; std::vector expected(expected_float.size()); std::transform(expected_float.begin(), expected_float.end(), expected.begin(), [](float f) { return fp16_ieee_from_fp32_value(f); }); ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_TO_F16_DWCONV_HWG_W, primary_tile_eq_kernel_size_channels_gt_cr) { size_t primary_tile = 3; size_t h = 3; size_t w = 1; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_to_f16_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected_float = { // cr blocks // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 5.0f, 6.0f, 10.0f, 11.0f, 15.0f, 16.0f, // bias again 2.0f, 3.0f, // then weights, channels first 7.0f, 8.0f, 12.0f, 13.0f, 17.0f, 18.0f, // bias again 4.0f, 0.0f, // then weights, channels first 9.0f, 0.0f, 14.0f, 0.0f, 19.0f, 0.0f, }; std::vector expected(expected_float.size()); std::transform(expected_float.begin(), expected_float.end(), expected.begin(), [](float f) { return fp16_ieee_from_fp32_value(f); }); ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_TO_F16_DWCONV_HWG_W, primary_tile_gt_kernel_size) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 2; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1] std::vector k(c * h * w); // k = [ // 2, 3, // 4, 5, // 6, 7, // 8, 9] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_to_f16_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected_float = { // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 2.0f, 3.0f, // go down the columns first 6.0f, 7.0f, 4.0f, 5.0f, 8.0f, 9.0f, // followed by 10 zeros to make up the difference with primary_tile 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, }; std::vector expected(expected_float.size()); std::transform(expected_float.begin(), expected_float.end(), expected.begin(), [](float f) { return fp16_ieee_from_fp32_value(f); }); ASSERT_EQ(expected, packed_weights); } TEST(PACK_F32_TO_F16_DWCONV_HWG_W, primary_tile_gt_kernel_size_channels_gt_cr) { size_t primary_tile = 9; size_t h = 2; size_t w = 2; size_t c = 5; size_t cr = 2; std::vector b(c); std::iota(b.begin(), b.end(), 0); // b = [0, 1, 2, 3, 4] std::vector k(c * h * w); // k = [ // 5, 6, 7, 8, 9, // 10, 11, 12, 13, 14, // 15, 16, 17, 18, 19, // 20, 21, 22, 23, 24] std::iota(k.begin(), k.end(), b.size()); std::vector packed_weights(((primary_tile + 1) * round_up_po2(c, cr))); xnn_pack_f32_to_f16_dwconv_hwg_w( primary_tile, h, w, c, cr, k.data(), b.data(), packed_weights.data(), 0, nullptr); std::vector expected_float = { // bias first (cr == 2 of them) 0.0f, 1.0f, // then weights, channels first 5.0f, 6.0f, // go down the columns first 15.0f, 16.0f, 10.0f, 11.0f, 20.0f, 21.0f, // followed by 10 zeros to make up the difference with primary_tile 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, // bias first (cr == 2 of them) 2.0f, 3.0f, // then weights, channels first 7.0f, 8.0f, 17.0f, 18.0f, 12.0f, 13.0f, 22.0f, 23.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, // bias 4.0f, 0.0f, // weights 9.0f, 0.0f, 19.0f, 0.0f, 14.0f, 0.0f, 24.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, }; std::vector expected(expected_float.size()); std::transform(expected_float.begin(), expected_float.end(), expected.begin(), [](float f) { return fp16_ieee_from_fp32_value(f); }); ASSERT_EQ(expected, packed_weights); }