| // Private fixed_graph.cpp vocabulary for model.bin directory positions. |
| // converter.model_contract.RUNTIME_WEIGHT_NAMES is the source |
| // of truth: the exporter lexicographically sorts those semantic names and uses |
| // each tuple index as the slot number. Enum names below are the C++ spelling of |
| // those same entries. To trace a slot, convert (for example) |
| // kModel10M0AttnQkvConvWeight to model.10.m.0.attn.qkv.conv.weight and find that |
| // name in RUNTIME_WEIGHT_NAMES. Keep the explicit ordinals so a review exposes |
| // any compiler/runtime ordering disagreement. |
| enum class WeightSlot : uint16_t { |
| kModel0ConvBias = 0, |
| kModel0ConvWeight = 1, |
| kModel1ConvBias = 2, |
| kModel1ConvWeight = 3, |
| kModel10Cv1ConvBias = 4, |
| kModel10Cv1ConvWeight = 5, |
| kModel10Cv2ConvBias = 6, |
| kModel10Cv2ConvWeight = 7, |
| kModel10M0AttnPeConvBias = 8, |
| kModel10M0AttnPeConvWeight = 9, |
| kModel10M0AttnProjConvBias = 10, |
| kModel10M0AttnProjConvWeight = 11, |
| kModel10M0AttnQkvConvBias = 12, |
| kModel10M0AttnQkvConvWeight = 13, |
| kModel10M0Ffn0ConvBias = 14, |
| kModel10M0Ffn0ConvWeight = 15, |
| kModel10M0Ffn1ConvBias = 16, |
| kModel10M0Ffn1ConvWeight = 17, |
| kModel13Cv1ConvBias = 18, |
| kModel13Cv1ConvWeightInput0256 = 19, |
| kModel13Cv1ConvWeightInput256384 = 20, |
| kModel13Cv2ConvBias = 21, |
| kModel13Cv2ConvWeight = 22, |
| kModel13M0Cv1ConvBias = 23, |
| kModel13M0Cv1ConvWeight = 24, |
| kModel13M0Cv2ConvBias = 25, |
| kModel13M0Cv2ConvWeight = 26, |
| kModel13M0Cv3ConvBias = 27, |
| kModel13M0Cv3ConvWeight = 28, |
| kModel13M0M0Cv1ConvBias = 29, |
| kModel13M0M0Cv1ConvWeight = 30, |
| kModel13M0M0Cv2ConvBias = 31, |
| kModel13M0M0Cv2ConvWeight = 32, |
| kModel13M0M1Cv1ConvBias = 33, |
| kModel13M0M1Cv1ConvWeight = 34, |
| kModel13M0M1Cv2ConvBias = 35, |
| kModel13M0M1Cv2ConvWeight = 36, |
| kModel16Cv1ConvBias = 37, |
| kModel16Cv1ConvWeightInput0128 = 38, |
| kModel16Cv1ConvWeightInput128256 = 39, |
| kModel16Cv2ConvBias = 40, |
| kModel16Cv2ConvWeight = 41, |
| kModel16M0Cv1ConvBias = 42, |
| kModel16M0Cv1ConvWeight = 43, |
| kModel16M0Cv2ConvBias = 44, |
| kModel16M0Cv2ConvWeight = 45, |
| kModel16M0Cv3ConvBias = 46, |
| kModel16M0Cv3ConvWeight = 47, |
| kModel16M0M0Cv1ConvBias = 48, |
| kModel16M0M0Cv1ConvWeight = 49, |
| kModel16M0M0Cv2ConvBias = 50, |
| kModel16M0M0Cv2ConvWeight = 51, |
| kModel16M0M1Cv1ConvBias = 52, |
| kModel16M0M1Cv1ConvWeight = 53, |
| kModel16M0M1Cv2ConvBias = 54, |
| kModel16M0M1Cv2ConvWeight = 55, |
| kModel17ConvBias = 56, |
| kModel17ConvWeight = 57, |
| kModel19Cv1ConvBias = 58, |
| kModel19Cv1ConvWeight = 59, |
| kModel19Cv2ConvBias = 60, |
| kModel19Cv2ConvWeight = 61, |
| kModel19M0Cv1ConvBias = 62, |
| kModel19M0Cv1ConvWeight = 63, |
| kModel19M0Cv2ConvBias = 64, |
| kModel19M0Cv2ConvWeight = 65, |
| kModel19M0Cv3ConvBias = 66, |
| kModel19M0Cv3ConvWeight = 67, |
| kModel19M0M0Cv1ConvBias = 68, |
| kModel19M0M0Cv1ConvWeight = 69, |
| kModel19M0M0Cv2ConvBias = 70, |
| kModel19M0M0Cv2ConvWeight = 71, |
| kModel19M0M1Cv1ConvBias = 72, |
| kModel19M0M1Cv1ConvWeight = 73, |
| kModel19M0M1Cv2ConvBias = 74, |
| kModel19M0M1Cv2ConvWeight = 75, |
| kModel2Cv1ConvBias = 76, |
| kModel2Cv1ConvWeight = 77, |
| kModel2Cv2ConvBias = 78, |
| kModel2Cv2ConvWeight = 79, |
| kModel2M0Cv1ConvBias = 80, |
| kModel2M0Cv1ConvWeight = 81, |
| kModel2M0Cv2ConvBias = 82, |
| kModel2M0Cv2ConvWeight = 83, |
| kModel20ConvBias = 84, |
| kModel20ConvWeight = 85, |
| kModel22Cv1ConvBias = 86, |
| kModel22Cv1ConvWeight = 87, |
| kModel22Cv2ConvBias = 88, |
| kModel22Cv2ConvWeight = 89, |
| kModel22M00Cv1ConvBias = 90, |
| kModel22M00Cv1ConvWeight = 91, |
| kModel22M00Cv2ConvBias = 92, |
| kModel22M00Cv2ConvWeight = 93, |
| kModel22M01AttnPeConvBias = 94, |
| kModel22M01AttnPeConvWeight = 95, |
| kModel22M01AttnProjConvBias = 96, |
| kModel22M01AttnProjConvWeight = 97, |
| kModel22M01AttnQkvConvBias = 98, |
| kModel22M01AttnQkvConvWeight = 99, |
| kModel22M01Ffn0ConvBias = 100, |
| kModel22M01Ffn0ConvWeight = 101, |
| kModel22M01Ffn1ConvBias = 102, |
| kModel22M01Ffn1ConvWeight = 103, |
| kModel23Cv200ConvBias = 104, |
| kModel23Cv200ConvWeight = 105, |
| kModel23Cv201ConvBias = 106, |
| kModel23Cv201ConvWeight = 107, |
| kModel23Cv202Bias = 108, |
| kModel23Cv202Weight = 109, |
| kModel23Cv210ConvBias = 110, |
| kModel23Cv210ConvWeight = 111, |
| kModel23Cv211ConvBias = 112, |
| kModel23Cv211ConvWeight = 113, |
| kModel23Cv212Bias = 114, |
| kModel23Cv212Weight = 115, |
| kModel23Cv220ConvBias = 116, |
| kModel23Cv220ConvWeight = 117, |
| kModel23Cv221ConvBias = 118, |
| kModel23Cv221ConvWeight = 119, |
| kModel23Cv222Bias = 120, |
| kModel23Cv222Weight = 121, |
| kModel23Cv3000ConvBias = 122, |
| kModel23Cv3000ConvWeight = 123, |
| kModel23Cv3001ConvBias = 124, |
| kModel23Cv3001ConvWeight = 125, |
| kModel23Cv3010ConvBias = 126, |
| kModel23Cv3010ConvWeight = 127, |
| kModel23Cv3011ConvBias = 128, |
| kModel23Cv3011ConvWeight = 129, |
| kModel23Cv302Bias = 130, |
| kModel23Cv302Weight = 131, |
| kModel23Cv3100ConvBias = 132, |
| kModel23Cv3100ConvWeight = 133, |
| kModel23Cv3101ConvBias = 134, |
| kModel23Cv3101ConvWeight = 135, |
| kModel23Cv3110ConvBias = 136, |
| kModel23Cv3110ConvWeight = 137, |
| kModel23Cv3111ConvBias = 138, |
| kModel23Cv3111ConvWeight = 139, |
| kModel23Cv312Bias = 140, |
| kModel23Cv312Weight = 141, |
| kModel23Cv3200ConvBias = 142, |
| kModel23Cv3200ConvWeight = 143, |
| kModel23Cv3201ConvBias = 144, |
| kModel23Cv3201ConvWeight = 145, |
| kModel23Cv3210ConvBias = 146, |
| kModel23Cv3210ConvWeight = 147, |
| kModel23Cv3211ConvBias = 148, |
| kModel23Cv3211ConvWeight = 149, |
| kModel23Cv322Bias = 150, |
| kModel23Cv322Weight = 151, |
| kModel3ConvBias = 152, |
| kModel3ConvWeight = 153, |
| kModel4Cv1ConvBias = 154, |
| kModel4Cv1ConvWeight = 155, |
| kModel4Cv2ConvBias = 156, |
| kModel4Cv2ConvWeight = 157, |
| kModel4M0Cv1ConvBias = 158, |
| kModel4M0Cv1ConvWeight = 159, |
| kModel4M0Cv2ConvBias = 160, |
| kModel4M0Cv2ConvWeight = 161, |
| kModel5ConvBias = 162, |
| kModel5ConvWeight = 163, |
| kModel6Cv1ConvBias = 164, |
| kModel6Cv1ConvWeight = 165, |
| kModel6Cv2ConvBias = 166, |
| kModel6Cv2ConvWeight = 167, |
| kModel6M0Cv1ConvBias = 168, |
| kModel6M0Cv1ConvWeight = 169, |
| kModel6M0Cv2ConvBias = 170, |
| kModel6M0Cv2ConvWeight = 171, |
| kModel6M0Cv3ConvBias = 172, |
| kModel6M0Cv3ConvWeight = 173, |
| kModel6M0M0Cv1ConvBias = 174, |
| kModel6M0M0Cv1ConvWeight = 175, |
| kModel6M0M0Cv2ConvBias = 176, |
| kModel6M0M0Cv2ConvWeight = 177, |
| kModel6M0M1Cv1ConvBias = 178, |
| kModel6M0M1Cv1ConvWeight = 179, |
| kModel6M0M1Cv2ConvBias = 180, |
| kModel6M0M1Cv2ConvWeight = 181, |
| kModel7ConvBias = 182, |
| kModel7ConvWeight = 183, |
| kModel8Cv1ConvBias = 184, |
| kModel8Cv1ConvWeight = 185, |
| kModel8Cv2ConvBias = 186, |
| kModel8Cv2ConvWeight = 187, |
| kModel8M0Cv1ConvBias = 188, |
| kModel8M0Cv1ConvWeight = 189, |
| kModel8M0Cv2ConvBias = 190, |
| kModel8M0Cv2ConvWeight = 191, |
| kModel8M0Cv3ConvBias = 192, |
| kModel8M0Cv3ConvWeight = 193, |
| kModel8M0M0Cv1ConvBias = 194, |
| kModel8M0M0Cv1ConvWeight = 195, |
| kModel8M0M0Cv2ConvBias = 196, |
| kModel8M0M0Cv2ConvWeight = 197, |
| kModel8M0M1Cv1ConvBias = 198, |
| kModel8M0M1Cv1ConvWeight = 199, |
| kModel8M0M1Cv2ConvBias = 200, |
| kModel8M0M1Cv2ConvWeight = 201, |
| kModel9Cv1ConvBias = 202, |
| kModel9Cv1ConvWeight = 203, |
| kModel9Cv2ConvBias = 204, |
| kModel9Cv2ConvWeight = 205, |
| kProjectionZeroBias128 = 206, |
| kProjectionZeroBias64 = 207, |
| }; |
| |
| static_assert(static_cast<size_t>(WeightSlot::kProjectionZeroBias64) + 1 == |
| yolo26::kRuntimeWeightSlotCount); |
|
|
