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"stage": 8,
"name": "Multi-layer, multi-target training core",
"started_utc": "2026-07-22T18:01:39.591576+00:00",
"finished_utc": "2026-07-22T18:52:11.421918+00:00",
"elapsed_seconds": 1212.3412683010101,
"overall_status": "PASS",
"mandatory_counts": {
"PASS": 37,
"FAIL": 0,
"BLOCKED": 0,
"SKIP": 0
},
"paths": {
"repository": "/content/Prism-llama.cpp",
"build": "/content/Prism-llama.cpp/build",
"model": "/content/models/Bonsai-27B-Q1/Bonsai-27B-Q1_0.gguf",
"target_config": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/targets_initial_trio.json",
"target_inventory": "/content/prism_native_q1_lora/target_inventory.json",
"resolved_targets": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/resolved_targets.json",
"native_test_source": "/content/Prism-llama.cpp/tests/test-q1-lora-multitarget.cpp",
"native_test_binary": "/content/Prism-llama.cpp/build/bin/test-q1-lora-multitarget",
"report_txt": "/content/prism_native_q1_lora/step08_multitarget_acceptance_report.txt",
"report_json": "/content/prism_native_q1_lora/step08_multitarget_acceptance_report.json"
},
"results": [
{
"name": "PREFLIGHT_PATHS",
"status": "PASS",
"summary": "All required Stage 7 workspace paths exist.",
"details": [],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "PINNED_COMMIT",
"status": "PASS",
"summary": "Resolved commit: 7529fdaaf99ffdc5ca71ace9c7409a56b27ad92f",
"details": [
"Expected: 7529fdaaf99ffdc5ca71ace9c7409a56b27ad92f"
],
"seconds": 0.002008199691772461,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/git_commit.log"
},
{
"name": "MODEL_INITIAL_HASH",
"status": "PASS",
"summary": "SHA256: 17ef842e47450caeb8eaa3ebfbbab5d2f2278b62b79be107985fb69a2f819aa0",
"details": [
"Expected: 17ef842e47450caeb8eaa3ebfbbab5d2f2278b62b79be107985fb69a2f819aa0",
"Size bytes: 3803452480"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "STAGE7_HANDOFF",
"status": "PASS",
"summary": "Stage 7 handoff says READY_FOR_STEP_8.",
"details": [
"{\"attention_adapter\": {\"path\": \"/content/prism_native_q1_lora/step06b_qwen35_loader_integration/bonsai_block11_attn_k_rank4.gguf\", \"sha256\": \"b7d3c61f9570837cb19a846541bd86533b78f1224ad57fe3b8ee52a7b60a084b\"}, \"commit\": \"7529fdaaf99ffdc5ca71ace9c7409a56b27ad92f\", \"created_utc\": \"2026-07-22T15:21:02.286893+00:00\", \"model\": {\"path\": \"/content/models/Bonsai-27B-Q1/Bonsai-27B-Q1_0.gguf\", \"sha256\": \"17ef842e47450caeb8eaa3ebfbbab5d2f2278b62b79be107985fb69a2f819aa0\"}, \"next\": \"Step 8 configurable multi-layer, multi-target packed-Q1 LoRA trainer.\", \"ssm_adapter\": {\"path\": \"/content/prism_native_q1_lora/step06b_qwen35_loader_integration/bonsai_block0_ssm_alpha_rank4.gguf\", \"sha256\": \"a7f5f6307445a98d8c69baf93c50fc93f2e9613f5b89b740be846163288f2d95\"}, \"stage7\": {\"blocked\": 0, \"fail\": 0, \"pass\": 46}, \"status\": \"READY_FOR_STEP_8\"}",
"Path: /content/prism_native_q1_lora/STAGE8_READY.json"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "TARGET_INVENTORY_SCAN",
"status": "PASS",
"summary": "Scanned 851 tensors and found 498 eligible 2D Q1 tensors.",
"details": [
"Inventory: /content/prism_native_q1_lora/target_inventory.json",
"Expected trio present: True",
"Category counts: {'attention': 160, 'ffn': 192, 'ssm': 144, 'other': 2}"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "TARGET_CONFIGURATION_FEATURES",
"status": "PASS",
"summary": "Configuration supports exact, glob, regex, block range, category, include, and exclude selection.",
"details": [
"exact=True",
"glob=True",
"regex=True",
"block_range=True",
"category=True",
"include=True",
"exclude=True"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "INITIAL_TRIO_RESOLUTION",
"status": "PASS",
"summary": "Resolved 3 unique targets.",
"details": [
"Resolved names: ['blk.0.ffn_down.weight', 'blk.0.ssm_alpha.weight', 'blk.11.attn_k.weight']",
"Expected names: ['blk.0.ffn_down.weight', 'blk.0.ssm_alpha.weight', 'blk.11.attn_k.weight']",
"Resolved targets: /content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/resolved_targets.json"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "ALLOCATION_MATH",
"status": "PASS",
"summary": "Static A/B allocation plan contains 135,360 trainable values and 1,082,880 AdamW-state bytes.",
"details": [
"blk.0.ffn_down.weight: K=17408 M=5120 rank=4 A=[17408, 4] B=[4, 5120] params=90,112",
"blk.0.ssm_alpha.weight: K=5120 M=48 rank=4 A=[5120, 4] B=[4, 48] params=20,672",
"blk.11.attn_k.weight: K=5120 M=1024 rank=4 A=[5120, 4] B=[4, 1024] params=24,576"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "STAGE7_SSM_FULL_GRAPH_SOLO",
"status": "PASS",
"summary": "Solo baseline passed.",
"details": [
"Code: 0",
"Timed out: False",
"M_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_b present=1 max_abs=2.64061641693 nelements=192\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_a present=1 max_abs=0.0283466782421 nelements=20480\nPRISM_Q1_LORA_GRAPH weight=blk.0.ssm_alpha.weight exact_q1=1 a_param=1 b_param=1\nPRISM_Q1_LORA_SKIP_NO_KV_INPUTS class=hybrid count=29 k_allocated=0 v_allocated=0 mask_allocated=0\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_b present=1 max_abs=2.8495221138 nelements=192\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_a present=1 max_abs=0.0290913283825 nelements=20480\nPRISM_Q1_LORA_GRAPH weight=blk.0.ssm_alpha.weight exact_q1=1 a_param=1 b_param=1\nPRISM_Q1_LORA_SKIP_NO_KV_INPUTS class=hybrid count=30 k_allocated=0 v_allocated=0 mask_allocated=0\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_b present=1 max_abs=3.05580377579 nelements=192\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_a present=1 max_abs=0.0297195930034 nelements=20480\nPRISM_Q1_LORA_GRAPH weight=blk.0.ssm_alpha.weight exact_q1=1 a_param=1 b_param=1\nPRISM_Q1_LORA_SKIP_NO_KV_INPUTS class=hybrid count=31 k_allocated=0 v_allocated=0 mask_allocated=0\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_b present=1 max_abs=3.25423502922 nelements=192\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_a present=1 max_abs=0.0303055327386 nelements=20480\nPRISM_Q1_LORA_GRAPH weight=blk.0.ssm_alpha.weight exact_q1=1 a_param=1 b_param=1\nPRISM_Q1_LORA_SKIP_NO_KV_INPUTS class=hybrid count=32 k_allocated=0 v_allocated=0 mask_allocated=0\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_b present=1 max_abs=3.45554542542 nelements=192\nPRISM_Q1_LORA_OPT_GRAD name=blk.0.ssm_alpha.weight.lora_a present=1 max_abs=0.0307995341718 nelements=20480\n~llama_context: CUDA0 compute buffer size of 1679.0160 MiB, does not match expectation of 170.9301 MiB\n~llama_context: CUDA_Host compute buffer size of 7.8947 MiB, does not match expectation of 0.3166 MiB\nPROBE_MODE=SSM\nPROBE_SCOPE=FULL_MODEL_CROSS_ENTROPY_BACKWARD\nTARGET_TENSOR=blk.0.ssm_alpha.weight\nMODEL_ARCHITECTURE=qwen35\nMODEL_BLOCK_COUNT=64\nTARGET_BASE_TYPE=Q1_0\nADAPTER_PARAMETER_COUNT=2\nADAPTER_A_PARAM=1\nADAPTER_B_PARAM=1\nADAPTER_A_BUFFER=CUDA0\nADAPTER_B_BUFFER=CUDA0\nCONTEXT_REQUESTED=8\nCONTEXT_ACTUAL=256\nCONTEXT_BATCH=8\nCONTEXT_UBATCH=8\nTRAINABLE_MODEL_PARAMETER_COUNT=0\nDATASET_SEQUENCE_LENGTH=256\nDATASET_SEQUENCE_COUNT=1\nDATASET_SHARD_COUNT=1\nOPTIMIZER_EXPECTED_CALLBACK_COUNT=32\nPROBE_BACKWARD_BEGIN=1\nCALLBACK_INDEX=1\nCALLBACK_MAX=32\nCALLBACK_LOSS=9.435184478760\nCALLBACK_INDEX=2\nCALLBACK_MAX=32\nCALLBACK_LOSS=6.991567850113\nCALLBACK_INDEX=3\nCALLBACK_MAX=32\nCALLBACK_LOSS=6.951730569204\nCALLBACK_INDEX=4\nCALLBACK_MAX=32\nCALLBACK_LOSS=5.591425865889\nCALLBACK_INDEX=5\nCALLBACK_MAX=32\nCALLBACK_LOSS=4.498854500055\nCALLBACK_INDEX=6\nCALLBACK_MAX=32\nCALLBACK_LOSS=3.765621205171\nCALLBACK_INDEX=7\nCALLBACK_MAX=32\nCALLBACK_LOSS=3.247454788004\nCALLBACK_INDEX=8\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.864488886669\nCALLBACK_INDEX=9\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.571981699930\nCALLBACK_INDEX=10\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.343306840956\nCALLBACK_INDEX=11\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.161193225871\nCALLBACK_INDEX=12\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.013896610588\nCALLBACK_INDEX=13\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.893039706808\nCALLBACK_INDEX=14\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.792682176190\nCALLBACK_INDEX=15\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.708444584409\nCALLBACK_INDEX=16\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.637051072903\nCALLBACK_INDEX=17\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.575991561308\nCALLBACK_INDEX=18\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.523337000774\nCALLBACK_INDEX=19\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.477652933252\nCALLBACK_INDEX=20\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.437696731836\nCALLBACK_INDEX=21\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.402585013282\nCALLBACK_INDEX=22\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.371512879702\nCALLBACK_INDEX=23\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.343847078474\nCALLBACK_INDEX=24\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.319028479978\nCALLBACK_INDEX=25\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.296668360829\nCALLBACK_INDEX=26\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.276389083610\nCALLBACK_INDEX=27\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.257873950733\nCALLBACK_INDEX=28\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.240850031908\nCALLBACK_INDEX=29\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.225122365972\nCALLBACK_INDEX=30\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.210492013395\nCALLBACK_INDEX=31\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.196780874364\nCALLBACK_INDEX=32\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.183871351648\nPROBE_BACKWARD_RETURNED=1\nLOSS_CROSS_ENTROPY=1.183871351648\nCALLBACK_COUNT=32\nCALLBACK_EXPECTED_COUNT=32\nLORA_A_MAX_CHANGE=0.002875711871\nLORA_B_MAX_CHANGE=0.003148333635\nBASE_CHANGED_BYTES=0\nCHECK_CROSS_ENTROPY_FORWARD=PASS\nCHECK_COMPLETE_MODEL_BACKWARD=PASS\nCHECK_TARGET_LORA_A_BACKWARD=PASS\nCHECK_TARGET_LORA_B_BACKWARD=PASS\nCHECK_BASE_MODEL_PARAMS_ZERO=PASS\nCHECK_PACKED_Q1_BASE_FROZEN=PASS\nPERSISTENT_EXPANDED_WEIGHT_BYTES=0\nCHECK_COMPLETE_SSM_BLOCK_BACKWARD=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 161.89742994308472,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/stage7_ssm_solo.log"
},
{
"name": "STAGE7_ATTENTION_FULL_GRAPH_SOLO",
"status": "PASS",
"summary": "Solo baseline passed.",
"details": [
"Code: 0",
"Timed out: False",
" name=blk.11.attn_k.weight.lora_b present=1 max_abs=1.28939809656e-05 nelements=4096\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_a present=1 max_abs=8.97498175618e-05 nelements=20480\nPRISM_Q1_LORA_GRAPH weight=blk.11.attn_k.weight exact_q1=1 a_param=1 b_param=1\nPRISM_Q1_LORA_SKIP_NO_KV_INPUTS class=hybrid count=29 k_allocated=0 v_allocated=0 mask_allocated=0\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_b present=1 max_abs=1.61654988915e-05 nelements=4096\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_a present=1 max_abs=0.000103239079181 nelements=20480\nPRISM_Q1_LORA_GRAPH weight=blk.11.attn_k.weight exact_q1=1 a_param=1 b_param=1\nPRISM_Q1_LORA_SKIP_NO_KV_INPUTS class=hybrid count=30 k_allocated=0 v_allocated=0 mask_allocated=0\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_b present=1 max_abs=1.31532324303e-05 nelements=4096\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_a present=1 max_abs=9.64753126027e-05 nelements=20480\nPRISM_Q1_LORA_GRAPH weight=blk.11.attn_k.weight exact_q1=1 a_param=1 b_param=1\nPRISM_Q1_LORA_SKIP_NO_KV_INPUTS class=hybrid count=31 k_allocated=0 v_allocated=0 mask_allocated=0\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_b present=1 max_abs=1.36266817208e-05 nelements=4096\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_a present=1 max_abs=8.94597033039e-05 nelements=20480\nPRISM_Q1_LORA_GRAPH weight=blk.11.attn_k.weight exact_q1=1 a_param=1 b_param=1\nPRISM_Q1_LORA_SKIP_NO_KV_INPUTS class=hybrid count=32 k_allocated=0 v_allocated=0 mask_allocated=0\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_b present=1 max_abs=1.00968309198e-05 nelements=4096\nPRISM_Q1_LORA_OPT_GRAD name=blk.11.attn_k.weight.lora_a present=1 max_abs=7.25003774278e-05 nelements=20480\n~llama_context: CUDA0 compute buffer size of 1404.4144 MiB, does not match expectation of 170.9301 MiB\n~llama_context: CUDA_Host compute buffer size of 7.8947 MiB, does not match expectation of 0.3166 MiB\nPROBE_MODE=ATTENTION\nPROBE_SCOPE=FULL_MODEL_CROSS_ENTROPY_BACKWARD\nTARGET_TENSOR=blk.11.attn_k.weight\nMODEL_ARCHITECTURE=qwen35\nMODEL_BLOCK_COUNT=64\nTARGET_BASE_TYPE=Q1_0\nADAPTER_PARAMETER_COUNT=2\nADAPTER_A_PARAM=1\nADAPTER_B_PARAM=1\nADAPTER_A_BUFFER=CUDA0\nADAPTER_B_BUFFER=CUDA0\nCONTEXT_REQUESTED=8\nCONTEXT_ACTUAL=256\nCONTEXT_BATCH=8\nCONTEXT_UBATCH=8\nTRAINABLE_MODEL_PARAMETER_COUNT=0\nDATASET_SEQUENCE_LENGTH=256\nDATASET_SEQUENCE_COUNT=1\nDATASET_SHARD_COUNT=1\nOPTIMIZER_EXPECTED_CALLBACK_COUNT=32\nPROBE_BACKWARD_BEGIN=1\nCALLBACK_INDEX=1\nCALLBACK_MAX=32\nCALLBACK_LOSS=9.435192108154\nCALLBACK_INDEX=2\nCALLBACK_MAX=32\nCALLBACK_LOSS=6.991573810577\nCALLBACK_INDEX=3\nCALLBACK_MAX=32\nCALLBACK_LOSS=6.951716423035\nCALLBACK_INDEX=4\nCALLBACK_MAX=32\nCALLBACK_LOSS=5.591724932194\nCALLBACK_INDEX=5\nCALLBACK_MAX=32\nCALLBACK_LOSS=4.499108514190\nCALLBACK_INDEX=6\nCALLBACK_MAX=32\nCALLBACK_LOSS=3.765804099540\nCALLBACK_INDEX=7\nCALLBACK_MAX=32\nCALLBACK_LOSS=3.247487857938\nCALLBACK_INDEX=8\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.864329503849\nCALLBACK_INDEX=9\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.571629409989\nCALLBACK_INDEX=10\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.342686025798\nCALLBACK_INDEX=11\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.160332282836\nCALLBACK_INDEX=12\nCALLBACK_MAX=32\nCALLBACK_LOSS=2.012845077862\nCALLBACK_INDEX=13\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.891923632759\nCALLBACK_INDEX=14\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.791637813406\nCALLBACK_INDEX=15\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.707596239448\nCALLBACK_INDEX=16\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.636516113766\nCALLBACK_INDEX=17\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.575931080124\nCALLBACK_INDEX=18\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.523934772445\nCALLBACK_INDEX=19\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.479016822420\nCALLBACK_INDEX=20\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.440018514544\nCALLBACK_INDEX=21\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.405951063548\nCALLBACK_INDEX=22\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.376011458988\nCALLBACK_INDEX=23\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.349660055145\nCALLBACK_INDEX=24\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.326310665036\nCALLBACK_INDEX=25\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.305531406999\nCALLBACK_INDEX=26\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.287003976221\nCALLBACK_INDEX=27\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.270347831978\nCALLBACK_INDEX=28\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.255386461637\nCALLBACK_INDEX=29\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.241903278848\nCALLBACK_INDEX=30\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.229714058340\nCALLBACK_INDEX=31\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.218638184090\nCALLBACK_INDEX=32\nCALLBACK_MAX=32\nCALLBACK_LOSS=1.208549017552\nPROBE_BACKWARD_RETURNED=1\nLOSS_CROSS_ENTROPY=1.208549017552\nCALLBACK_COUNT=32\nCALLBACK_EXPECTED_COUNT=32\nLORA_A_MAX_CHANGE=0.001150659635\nLORA_B_MAX_CHANGE=0.001416498795\nBASE_CHANGED_BYTES=0\nCHECK_CROSS_ENTROPY_FORWARD=PASS\nCHECK_COMPLETE_MODEL_BACKWARD=PASS\nCHECK_TARGET_LORA_A_BACKWARD=PASS\nCHECK_TARGET_LORA_B_BACKWARD=PASS\nCHECK_BASE_MODEL_PARAMS_ZERO=PASS\nCHECK_PACKED_Q1_BASE_FROZEN=PASS\nPERSISTENT_EXPANDED_WEIGHT_BYTES=0\nCHECK_COMPLETE_ATTENTION_BLOCK_BACKWARD=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 153.16597151756287,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/stage7_attention_solo.log"
},
{
"name": "STAGE7_FFN_REAL_LAYER_SOLO",
"status": "PASS",
"summary": "Solo baseline passed.",
"details": [
"Code: 0",
"Timed out: False",
"ph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 10 reused\nCUDA Graph id 16 reused\nggml_backend_cuda_graph_compute: CUDA graph warmup complete\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nCUDA Graph id 16 reused\nMODEL_ARCHITECTURE=qwen35\nMODEL_TENSOR_COUNT=851\nMODEL_DATA_OFFSET=10992704\nQ1_TENSOR_COUNT=498\nQ1_2D_TENSOR_COUNT=498\nSELECTED_LAYER_COUNT=3\nCUDA_BACKEND=CUDA0\nCUDA_DEVICE=NVIDIA L4\nLAYER_BEGIN=0\nLAYER_CATEGORY=ATTENTION\nLAYER_NAME=blk.11.attn_k.weight\nLAYER_K=5120\nLAYER_M=1024\nLAYER_PACKED_BYTES=737280\nLAYER_DIAGNOSTIC_NAME=blk.11.attn_k.weight\nLAYER_DIAGNOSTIC_INITIAL_LOSS=0.0000049876\nLAYER_DIAGNOSTIC_FINAL_LOSS=0.0000000001\nLAYER_DIAGNOSTIC_LOSS_RATIO=0.0000144203\nLAYER_DIAGNOSTIC_A_CHANGE=0.0001616608\nLAYER_DIAGNOSTIC_B_CHANGE=0.0023718239\nLAYER_INITIAL_LOSS=0.0000049876\nLAYER_FINAL_LOSS=0.0000000001\nLAYER_LOSS_RATIO=0.0000144203\nLAYER_A_MAX_CHANGE=0.0001616608\nLAYER_B_MAX_CHANGE=0.0023718239\nLAYER_BASE_CHANGED_BYTES=0\nLAYER_STATUS=PASS\nLAYER_END=0\nLAYER_BEGIN=1\nLAYER_CATEGORY=FFN\nLAYER_NAME=blk.0.ffn_down.weight\nLAYER_K=17408\nLAYER_M=5120\nLAYER_PACKED_BYTES=12533760\nLAYER_DIAGNOSTIC_NAME=blk.0.ffn_down.weight\nLAYER_DIAGNOSTIC_INITIAL_LOSS=0.0000058323\nLAYER_DIAGNOSTIC_FINAL_LOSS=0.0000000001\nLAYER_DIAGNOSTIC_LOSS_RATIO=0.0000252913\nLAYER_DIAGNOSTIC_A_CHANGE=0.0000593979\nLAYER_DIAGNOSTIC_B_CHANGE=0.0023832463\nLAYER_INITIAL_LOSS=0.0000058323\nLAYER_FINAL_LOSS=0.0000000001\nLAYER_LOSS_RATIO=0.0000252913\nLAYER_A_MAX_CHANGE=0.0000593979\nLAYER_B_MAX_CHANGE=0.0023832463\nLAYER_BASE_CHANGED_BYTES=0\nLAYER_STATUS=PASS\nLAYER_END=1\nLAYER_BEGIN=2\nLAYER_CATEGORY=HYBRID_SSM\nLAYER_NAME=blk.0.ssm_alpha.weight\nLAYER_K=5120\nLAYER_M=48\nLAYER_PACKED_BYTES=34560\nLAYER_DIAGNOSTIC_NAME=blk.0.ssm_alpha.weight\nLAYER_DIAGNOSTIC_INITIAL_LOSS=0.0000050400\nLAYER_DIAGNOSTIC_FINAL_LOSS=0.0000000001\nLAYER_DIAGNOSTIC_LOSS_RATIO=0.0000127534\nLAYER_DIAGNOSTIC_A_CHANGE=0.0001713659\nLAYER_DIAGNOSTIC_B_CHANGE=0.0019946264\nLAYER_INITIAL_LOSS=0.0000050400\nLAYER_FINAL_LOSS=0.0000000001\nLAYER_LOSS_RATIO=0.0000127534\nLAYER_A_MAX_CHANGE=0.0001713659\nLAYER_B_MAX_CHANGE=0.0019946264\nLAYER_BASE_CHANGED_BYTES=0\nLAYER_STATUS=PASS\nLAYER_END=2\nCHECK_ACTUAL_GGUF_TENSOR_BYTES=PASS\nCHECK_ACTUAL_BONSAI_DIMENSIONS=PASS\nCHECK_REAL_EXACT_Q1_FORWARD=PASS\nCHECK_REAL_LORA_A_UPDATE=PASS\nCHECK_REAL_LORA_B_UPDATE=PASS\nCHECK_REAL_BASE_FROZEN=PASS\nCHECK_REAL_LAYER_LOSS_DECREASE=PASS\nPERSISTENT_EXPANDED_WEIGHT_BYTES=0\nFINAL_STATUS=PASS\n"
],
"seconds": 1.6689019203186035,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/stage7_ffn_real_layer_solo.log"
},
{
"name": "MULTITARGET_TEST_SOURCE_PRESENT",
"status": "PASS",
"summary": "Native Step 8 test source exists.",
"details": [
"Expected path: /content/Prism-llama.cpp/tests/test-q1-lora-multitarget.cpp",
"Contract: /content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/native_test_contract.txt"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "MULTITARGET_CMAKE_REGISTRATION",
"status": "PASS",
"summary": "CMake target is registered.",
"details": [
"CMake modified now: False",
"Path: /content/Prism-llama.cpp/tests/CMakeLists.txt"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "MULTITARGET_NATIVE_BUILD",
"status": "PASS",
"summary": "Native Step 8 executable built successfully.",
"details": [
"Configure code: 0",
"Build code: 0",
"ninja: no work to do.\n"
],
"seconds": 1.4630544185638428,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/build_multitarget.log"
},
{
"name": "NATIVE_8_1_INVENTORY",
"status": "PASS",
"summary": "Native mode 'inventory' passed.",
"details": [
"Mode: inventory",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"TARGET_COUNT=3\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 0.08491396903991699,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_8_1_inventory.log"
},
{
"name": "NATIVE_8_2_ALLOCATION",
"status": "PASS",
"summary": "Native mode 'allocation' passed.",
"details": [
"Mode: allocation",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"TARGET_COUNT=3\nOPTIMIZER_PARAMETER_COUNT=6\nTRAINABLE_PARAMETER_VALUES=135360\nOPTIMIZER_STATE_BYTES=1082880\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 0.08632302284240723,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_8_2_allocation.log"
},
{
"name": "NATIVE_8_3_REGISTRY",
"status": "PASS",
"summary": "Native mode 'registry' passed.",
"details": [
"Mode: registry",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"\ncreate_tensor: loading tensor blk.60.ssm_conv1d.weight\ncreate_tensor: loading tensor blk.60.ssm_dt.bias\ncreate_tensor: loading tensor blk.60.ssm_a\ncreate_tensor: loading tensor blk.60.ssm_beta.weight\ncreate_tensor: loading tensor blk.60.ssm_alpha.weight\ncreate_tensor: loading tensor blk.60.ssm_norm.weight\ncreate_tensor: loading tensor blk.60.ssm_out.weight\ncreate_tensor: loading tensor blk.60.ffn_gate.weight\ncreate_tensor: loading tensor blk.60.ffn_down.weight\ncreate_tensor: loading tensor blk.60.ffn_up.weight\ncreate_tensor: loading tensor blk.61.attn_norm.weight\ncreate_tensor: loading tensor blk.61.post_attention_norm.weight\ncreate_tensor: loading tensor blk.61.attn_qkv.weight\ncreate_tensor: loading tensor blk.61.attn_gate.weight\ncreate_tensor: loading tensor blk.61.ssm_conv1d.weight\ncreate_tensor: loading tensor blk.61.ssm_dt.bias\ncreate_tensor: loading tensor blk.61.ssm_a\ncreate_tensor: loading tensor blk.61.ssm_beta.weight\ncreate_tensor: loading tensor blk.61.ssm_alpha.weight\ncreate_tensor: loading tensor blk.61.ssm_norm.weight\ncreate_tensor: loading tensor blk.61.ssm_out.weight\ncreate_tensor: loading tensor blk.61.ffn_gate.weight\ncreate_tensor: loading tensor blk.61.ffn_down.weight\ncreate_tensor: loading tensor blk.61.ffn_up.weight\ncreate_tensor: loading tensor blk.62.attn_norm.weight\ncreate_tensor: loading tensor blk.62.post_attention_norm.weight\ncreate_tensor: loading tensor blk.62.attn_qkv.weight\ncreate_tensor: loading tensor blk.62.attn_gate.weight\ncreate_tensor: loading tensor blk.62.ssm_conv1d.weight\ncreate_tensor: loading tensor blk.62.ssm_dt.bias\ncreate_tensor: loading tensor blk.62.ssm_a\ncreate_tensor: loading tensor blk.62.ssm_beta.weight\ncreate_tensor: loading tensor blk.62.ssm_alpha.weight\ncreate_tensor: loading tensor blk.62.ssm_norm.weight\ncreate_tensor: loading tensor blk.62.ssm_out.weight\ncreate_tensor: loading tensor blk.62.ffn_gate.weight\ncreate_tensor: loading tensor blk.62.ffn_down.weight\ncreate_tensor: loading tensor blk.62.ffn_up.weight\ncreate_tensor: loading tensor blk.63.attn_norm.weight\ncreate_tensor: loading tensor blk.63.post_attention_norm.weight\ncreate_tensor: loading tensor blk.63.attn_q.weight\ncreate_tensor: loading tensor blk.63.attn_k.weight\ncreate_tensor: loading tensor blk.63.attn_v.weight\ncreate_tensor: loading tensor blk.63.attn_output.weight\ncreate_tensor: loading tensor blk.63.attn_q_norm.weight\ncreate_tensor: loading tensor blk.63.attn_k_norm.weight\ncreate_tensor: loading tensor blk.63.ffn_gate.weight\ncreate_tensor: loading tensor blk.63.ffn_down.weight\ncreate_tensor: loading tensor blk.63.ffn_up.weight\ndone_getting_tensors: tensor 'token_embd.weight' (q1_0) (and 0 others) cannot be used with preferred buffer type CUDA_Host, using CPU instead\nload_tensors: offloading output layer to GPU\nload_tensors: offloading 63 repeating layers to GPU\nload_tensors: offloaded 65/65 layers to GPU\nload_tensors: CPU_Mapped model buffer size = 170.51 MiB\nload_tensors: CUDA0 model buffer size = 3446.27 MiB\n.............................................................................................\nllama_adapter_lora_init_impl: loading lora adapter from '/content/prism_native_q1_lora/step08_multitarget_implementation/multi_target_adapter_template.gguf' ...\nllama_adapter_lora_init_impl: Dumping metadata keys/values.\nllama_adapter_lora_init_impl: - kv 0: general.architecture str = qwen35\nllama_adapter_lora_init_impl: - kv 1: general.type str = adapter\nllama_adapter_lora_init_impl: - kv 2: general.name str = Bonsai-27B Step 8 initial trio\nllama_adapter_lora_init_impl: - kv 3: adapter.type str = lora\nllama_adapter_lora_init_impl: - kv 4: adapter.lora.alpha f32 = 8.000000\nllama_adapter_lora_init_impl: - kv 5: prism.q1_lora.format str = native-packed-q1-multitarget-v1\nllama_adapter_lora_init_impl: - kv 6: prism.q1_lora.target_count u32 = 3\nllama_adapter_lora_init_impl: lora for 'blk.0.ffn_down.weight' -> 'CUDA0'\nPRISM_Q1_LORA_PARAM weight=blk.0.ffn_down.weight a_param=1 b_param=1\nllama_adapter_lora_init_impl: lora for 'blk.0.ssm_alpha.weight' -> 'CUDA0'\nPRISM_Q1_LORA_PARAM weight=blk.0.ssm_alpha.weight a_param=1 b_param=1\nllama_adapter_lora_init_impl: lora for 'blk.11.attn_k.weight' -> 'CUDA0'\nPRISM_Q1_LORA_PARAM weight=blk.11.attn_k.weight a_param=1 b_param=1\nllama_adapter_lora_init_impl: CUDA0 LoRA buffer size = 0.52 MiB\nllama_adapter_lora_init_impl: loaded 6 tensors from lora file\nREGISTRY_TARGET=blk.0.ssm_alpha.weight FOUND=1 SHAPE_OK=1 FLAGS_OK=1 BASE_Q1=1\nREGISTRY_TARGET=blk.11.attn_k.weight FOUND=1 SHAPE_OK=1 FLAGS_OK=1 BASE_Q1=1\nREGISTRY_TARGET=blk.0.ffn_down.weight FOUND=1 SHAPE_OK=1 FLAGS_OK=1 BASE_Q1=1\nTARGET_COUNT=3\nOPTIMIZER_PARAMETER_COUNT=6\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 2.3658289909362793,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_8_3_registry.log"
},
{
"name": "NATIVE_8_4_PARAMETERS",
"status": "PASS",
"summary": "Native mode 'parameters' passed.",
"details": [
"Mode: parameters",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"\ncreate_tensor: loading tensor blk.60.ssm_conv1d.weight\ncreate_tensor: loading tensor blk.60.ssm_dt.bias\ncreate_tensor: loading tensor blk.60.ssm_a\ncreate_tensor: loading tensor blk.60.ssm_beta.weight\ncreate_tensor: loading tensor blk.60.ssm_alpha.weight\ncreate_tensor: loading tensor blk.60.ssm_norm.weight\ncreate_tensor: loading tensor blk.60.ssm_out.weight\ncreate_tensor: loading tensor blk.60.ffn_gate.weight\ncreate_tensor: loading tensor blk.60.ffn_down.weight\ncreate_tensor: loading tensor blk.60.ffn_up.weight\ncreate_tensor: loading tensor blk.61.attn_norm.weight\ncreate_tensor: loading tensor blk.61.post_attention_norm.weight\ncreate_tensor: loading tensor blk.61.attn_qkv.weight\ncreate_tensor: loading tensor blk.61.attn_gate.weight\ncreate_tensor: loading tensor blk.61.ssm_conv1d.weight\ncreate_tensor: loading tensor blk.61.ssm_dt.bias\ncreate_tensor: loading tensor blk.61.ssm_a\ncreate_tensor: loading tensor blk.61.ssm_beta.weight\ncreate_tensor: loading tensor blk.61.ssm_alpha.weight\ncreate_tensor: loading tensor blk.61.ssm_norm.weight\ncreate_tensor: loading tensor blk.61.ssm_out.weight\ncreate_tensor: loading tensor blk.61.ffn_gate.weight\ncreate_tensor: loading tensor blk.61.ffn_down.weight\ncreate_tensor: loading tensor blk.61.ffn_up.weight\ncreate_tensor: loading tensor blk.62.attn_norm.weight\ncreate_tensor: loading tensor blk.62.post_attention_norm.weight\ncreate_tensor: loading tensor blk.62.attn_qkv.weight\ncreate_tensor: loading tensor blk.62.attn_gate.weight\ncreate_tensor: loading tensor blk.62.ssm_conv1d.weight\ncreate_tensor: loading tensor blk.62.ssm_dt.bias\ncreate_tensor: loading tensor blk.62.ssm_a\ncreate_tensor: loading tensor blk.62.ssm_beta.weight\ncreate_tensor: loading tensor blk.62.ssm_alpha.weight\ncreate_tensor: loading tensor blk.62.ssm_norm.weight\ncreate_tensor: loading tensor blk.62.ssm_out.weight\ncreate_tensor: loading tensor blk.62.ffn_gate.weight\ncreate_tensor: loading tensor blk.62.ffn_down.weight\ncreate_tensor: loading tensor blk.62.ffn_up.weight\ncreate_tensor: loading tensor blk.63.attn_norm.weight\ncreate_tensor: loading tensor blk.63.post_attention_norm.weight\ncreate_tensor: loading tensor blk.63.attn_q.weight\ncreate_tensor: loading tensor blk.63.attn_k.weight\ncreate_tensor: loading tensor blk.63.attn_v.weight\ncreate_tensor: loading tensor blk.63.attn_output.weight\ncreate_tensor: loading tensor blk.63.attn_q_norm.weight\ncreate_tensor: loading tensor blk.63.attn_k_norm.weight\ncreate_tensor: loading tensor blk.63.ffn_gate.weight\ncreate_tensor: loading tensor blk.63.ffn_down.weight\ncreate_tensor: loading tensor blk.63.ffn_up.weight\ndone_getting_tensors: tensor 'token_embd.weight' (q1_0) (and 0 others) cannot be used with preferred buffer type CUDA_Host, using CPU instead\nload_tensors: offloading output layer to GPU\nload_tensors: offloading 63 repeating layers to GPU\nload_tensors: offloaded 65/65 layers to GPU\nload_tensors: CPU_Mapped model buffer size = 170.51 MiB\nload_tensors: CUDA0 model buffer size = 3446.27 MiB\n.............................................................................................\nllama_adapter_lora_init_impl: loading lora adapter from '/content/prism_native_q1_lora/step08_multitarget_implementation/multi_target_adapter_template.gguf' ...\nllama_adapter_lora_init_impl: Dumping metadata keys/values.\nllama_adapter_lora_init_impl: - kv 0: general.architecture str = qwen35\nllama_adapter_lora_init_impl: - kv 1: general.type str = adapter\nllama_adapter_lora_init_impl: - kv 2: general.name str = Bonsai-27B Step 8 initial trio\nllama_adapter_lora_init_impl: - kv 3: adapter.type str = lora\nllama_adapter_lora_init_impl: - kv 4: adapter.lora.alpha f32 = 8.000000\nllama_adapter_lora_init_impl: - kv 5: prism.q1_lora.format str = native-packed-q1-multitarget-v1\nllama_adapter_lora_init_impl: - kv 6: prism.q1_lora.target_count u32 = 3\nllama_adapter_lora_init_impl: lora for 'blk.0.ffn_down.weight' -> 'CUDA0'\nPRISM_Q1_LORA_PARAM weight=blk.0.ffn_down.weight a_param=1 b_param=1\nllama_adapter_lora_init_impl: lora for 'blk.0.ssm_alpha.weight' -> 'CUDA0'\nPRISM_Q1_LORA_PARAM weight=blk.0.ssm_alpha.weight a_param=1 b_param=1\nllama_adapter_lora_init_impl: lora for 'blk.11.attn_k.weight' -> 'CUDA0'\nPRISM_Q1_LORA_PARAM weight=blk.11.attn_k.weight a_param=1 b_param=1\nllama_adapter_lora_init_impl: CUDA0 LoRA buffer size = 0.52 MiB\nllama_adapter_lora_init_impl: loaded 6 tensors from lora file\nREGISTRY_TARGET=blk.0.ssm_alpha.weight FOUND=1 SHAPE_OK=1 FLAGS_OK=1 BASE_Q1=1\nREGISTRY_TARGET=blk.11.attn_k.weight FOUND=1 SHAPE_OK=1 FLAGS_OK=1 BASE_Q1=1\nREGISTRY_TARGET=blk.0.ffn_down.weight FOUND=1 SHAPE_OK=1 FLAGS_OK=1 BASE_Q1=1\nTARGET_COUNT=3\nOPTIMIZER_PARAMETER_COUNT=6\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 2.3377742767333984,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_8_4_parameters.log"
},
{
"name": "NATIVE_SOLO_SSM",
"status": "PASS",
"summary": "Native mode 'solo_ssm' passed.",
"details": [
"Mode: solo_ssm",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"SOLO_LOG=/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/runs/native_solo_ssm/solo_ssm.log\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 162.32891511917114,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_solo_ssm.log"
},
{
"name": "NATIVE_SOLO_ATTENTION",
"status": "PASS",
"summary": "Native mode 'solo_attention' passed.",
"details": [
"Mode: solo_attention",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"SOLO_LOG=/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/runs/native_solo_attention/solo_attention.log\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 153.4007477760315,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_solo_attention.log"
},
{
"name": "NATIVE_SOLO_FFN",
"status": "PASS",
"summary": "Native mode 'solo_ffn' passed.",
"details": [
"Mode: solo_ffn",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"SOLO_LOG=/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/runs/native_solo_ffn/solo_ffn.log\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 1.7808811664581299,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_solo_ffn.log"
},
{
"name": "NATIVE_8_5_DIAGNOSTICS",
"status": "PASS",
"summary": "Native mode 'diagnostics' passed.",
"details": [
"Mode: diagnostics",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"84d835c964c4a0ae32fed9be2106124ff9319b74317ba9cdb0ea21069150edb5\n87a251d004b4bf9821b2b0ff198fad84d48a863bc7aeb258afaf6f636f511756\nTARGET_DIAG_JSON={\"tensor_name\":\"blk.0.ssm_alpha.weight\",\"category\":\"ssm\",\"block\":0,\"K\":5120,\"M\":48,\"rank\":4,\"alpha\":8.000000000000,\"a_grad_max\":0.03050948493180000,\"b_grad_max\":0.35347056388900000,\"a_update_max\":0.00215250515611842,\"b_update_max\":0.00278883753344417,\"parameter_count\":20672,\"optimizer_state_bytes\":165376,\"enabled\":1,\"base_is_parameter\":0,\"a_is_parameter\":1,\"b_is_parameter\":1}\nTARGET_DIAG_JSON={\"tensor_name\":\"blk.11.attn_k.weight\",\"category\":\"attention\",\"block\":11,\"K\":5120,\"M\":1024,\"rank\":4,\"alpha\":8.00000000000000000,\"a_grad_max\":0.06333008408550000,\"b_grad_max\":0.00231829937547000,\"a_update_max\":0.00114458351163194,\"b_update_max\":0.00114967674016953,\"parameter_count\":24576,\"optimizer_state_bytes\":196608,\"enabled\":1,\"base_is_parameter\":0,\"a_is_parameter\":1,\"b_is_parameter\":1}\nTARGET_DIAG_JSON={\"tensor_name\":\"blk.0.ffn_down.weight\",\"category\":\"ffn\",\"block\":0,\"K\":17408,\"M\":5120,\"rank\":4,\"alpha\":8.00000000000000000,\"a_grad_max\":0.58977997302999996,\"b_grad_max\":0.17448918521400000,\"a_update_max\":0.00282804788002977,\"b_update_max\":0.00334705794265133,\"parameter_count\":90112,\"optimizer_state_bytes\":720896,\"enabled\":1,\"base_is_parameter\":0,\"a_is_parameter\":1,\"b_is_parameter\":1}\nCORE_RETURN_CODE=0\nTARGET_COUNT=3\nOPTIMIZER_PARAMETER_COUNT=6\nBASE_CHANGED_BYTES=0\nPERSISTENT_EXPANDED_BASE_BYTES=0\nADAPTER_INITIAL_PATH=/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/runs/native_8_5_diagnostics/multi_target_adapter_initial.gguf\nADAPTER_UPDATED_PATH=/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/runs/native_8_5_diagnostics/multi_target_adapter_updated.gguf\nADAPTER_INITIAL_SHA256=84d835c964c4a0ae32fed9be2106124ff9319b74317ba9cdb0ea21069150edb5\nADAPTER_UPDATED_SHA256=87a251d004b4bf9821b2b0ff198fad84d48a863bc7aeb258afaf6f636f511756\nDETERMINISM_FINGERPRINT=87a251d004b4bf9821b2b0ff198fad84d48a863bc7aeb258afaf6f636f511756\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 162.97227025032043,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_8_5_diagnostics.log"
},
{
"name": "NATIVE_8_6_TRIO_RUN_A",
"status": "PASS",
"summary": "Native mode 'trio' passed.",
"details": [
"Mode: trio",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"84d835c964c4a0ae32fed9be2106124ff9319b74317ba9cdb0ea21069150edb5\n87a251d004b4bf9821b2b0ff198fad84d48a863bc7aeb258afaf6f636f511756\nTARGET_DIAG_JSON={\"tensor_name\":\"blk.0.ssm_alpha.weight\",\"category\":\"ssm\",\"block\":0,\"K\":5120,\"M\":48,\"rank\":4,\"alpha\":8.000000000000,\"a_grad_max\":0.03050948493180000,\"b_grad_max\":0.35347056388900000,\"a_update_max\":0.00215250515611842,\"b_update_max\":0.00278883753344417,\"parameter_count\":20672,\"optimizer_state_bytes\":165376,\"enabled\":1,\"base_is_parameter\":0,\"a_is_parameter\":1,\"b_is_parameter\":1}\nTARGET_DIAG_JSON={\"tensor_name\":\"blk.11.attn_k.weight\",\"category\":\"attention\",\"block\":11,\"K\":5120,\"M\":1024,\"rank\":4,\"alpha\":8.00000000000000000,\"a_grad_max\":0.06333008408550000,\"b_grad_max\":0.00231829937547000,\"a_update_max\":0.00114458351163194,\"b_update_max\":0.00114967674016953,\"parameter_count\":24576,\"optimizer_state_bytes\":196608,\"enabled\":1,\"base_is_parameter\":0,\"a_is_parameter\":1,\"b_is_parameter\":1}\nTARGET_DIAG_JSON={\"tensor_name\":\"blk.0.ffn_down.weight\",\"category\":\"ffn\",\"block\":0,\"K\":17408,\"M\":5120,\"rank\":4,\"alpha\":8.00000000000000000,\"a_grad_max\":0.58977997302999996,\"b_grad_max\":0.17448918521400000,\"a_update_max\":0.00282804788002977,\"b_update_max\":0.00334705794265133,\"parameter_count\":90112,\"optimizer_state_bytes\":720896,\"enabled\":1,\"base_is_parameter\":0,\"a_is_parameter\":1,\"b_is_parameter\":1}\nCORE_RETURN_CODE=0\nTARGET_COUNT=3\nOPTIMIZER_PARAMETER_COUNT=6\nBASE_CHANGED_BYTES=0\nPERSISTENT_EXPANDED_BASE_BYTES=0\nADAPTER_INITIAL_PATH=/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/runs/native_8_6_trio_run_a/multi_target_adapter_initial.gguf\nADAPTER_UPDATED_PATH=/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/runs/native_8_6_trio_run_a/multi_target_adapter_updated.gguf\nADAPTER_INITIAL_SHA256=84d835c964c4a0ae32fed9be2106124ff9319b74317ba9cdb0ea21069150edb5\nADAPTER_UPDATED_SHA256=87a251d004b4bf9821b2b0ff198fad84d48a863bc7aeb258afaf6f636f511756\nDETERMINISM_FINGERPRINT=87a251d004b4bf9821b2b0ff198fad84d48a863bc7aeb258afaf6f636f511756\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 162.79827642440796,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_8_6_trio_run_a.log"
},
{
"name": "NATIVE_SAVE_RELOAD",
"status": "PASS",
"summary": "Native mode 'save_reload' passed.",
"details": [
"Mode: save_reload",
"Code: 0",
"Timed out: False",
"External GPU before MiB: 0",
"External GPU after MiB: 0",
"rent, layer 8: dev = CUDA0\nllama_memory_recurrent, layer 9: dev = CUDA0\nllama_memory_recurrent, layer 10: dev = CUDA0\nllama_memory_recurrent: layer 11: skipped\nllama_memory_recurrent, layer 12: dev = CUDA0\nllama_memory_recurrent, layer 13: dev = CUDA0\nllama_memory_recurrent, layer 14: dev = CUDA0\nllama_memory_recurrent: layer 15: skipped\nllama_memory_recurrent, layer 16: dev = CUDA0\nllama_memory_recurrent, layer 17: dev = CUDA0\nllama_memory_recurrent, layer 18: dev = CUDA0\nllama_memory_recurrent: layer 19: skipped\nllama_memory_recurrent, layer 20: dev = CUDA0\nllama_memory_recurrent, layer 21: dev = CUDA0\nllama_memory_recurrent, layer 22: dev = CUDA0\nllama_memory_recurrent: layer 23: skipped\nllama_memory_recurrent, layer 24: dev = CUDA0\nllama_memory_recurrent, layer 25: dev = CUDA0\nllama_memory_recurrent, layer 26: dev = CUDA0\nllama_memory_recurrent: layer 27: skipped\nllama_memory_recurrent, layer 28: dev = CUDA0\nllama_memory_recurrent, layer 29: dev = CUDA0\nllama_memory_recurrent, layer 30: dev = CUDA0\nllama_memory_recurrent: layer 31: skipped\nllama_memory_recurrent, layer 32: dev = CUDA0\nllama_memory_recurrent, layer 33: dev = CUDA0\nllama_memory_recurrent, layer 34: dev = CUDA0\nllama_memory_recurrent: layer 35: skipped\nllama_memory_recurrent, layer 36: dev = CUDA0\nllama_memory_recurrent, layer 37: dev = CUDA0\nllama_memory_recurrent, layer 38: dev = CUDA0\nllama_memory_recurrent: layer 39: skipped\nllama_memory_recurrent, layer 40: dev = CUDA0\nllama_memory_recurrent, layer 41: dev = CUDA0\nllama_memory_recurrent, layer 42: dev = CUDA0\nllama_memory_recurrent: layer 43: skipped\nllama_memory_recurrent, layer 44: dev = CUDA0\nllama_memory_recurrent, layer 45: dev = CUDA0\nllama_memory_recurrent, layer 46: dev = CUDA0\nllama_memory_recurrent: layer 47: skipped\nllama_memory_recurrent, layer 48: dev = CUDA0\nllama_memory_recurrent, layer 49: dev = CUDA0\nllama_memory_recurrent, layer 50: dev = CUDA0\nllama_memory_recurrent: layer 51: skipped\nllama_memory_recurrent, layer 52: dev = CUDA0\nllama_memory_recurrent, layer 53: dev = CUDA0\nllama_memory_recurrent, layer 54: dev = CUDA0\nllama_memory_recurrent: layer 55: skipped\nllama_memory_recurrent, layer 56: dev = CUDA0\nllama_memory_recurrent, layer 57: dev = CUDA0\nllama_memory_recurrent, layer 58: dev = CUDA0\nllama_memory_recurrent: layer 59: skipped\nllama_memory_recurrent, layer 60: dev = CUDA0\nllama_memory_recurrent, layer 61: dev = CUDA0\nllama_memory_recurrent, layer 62: dev = CUDA0\nllama_memory_recurrent: layer 63: skipped\nllama_memory_recurrent: CUDA0 RS buffer size = 149.62 MiB\nllama_memory_recurrent: size = 149.62 MiB ( 1 cells, 64 layers, 1 seqs 0 rs_seq), R (f32): 5.62 MiB, S (f32): 144.00 MiB\nllama_context: enumerating backends\nllama_context: backend_ptrs.size() = 2\nsched_reserve: reserving ...\nsched_reserve: max_nodes = 27232\nsched_reserve: reserving full memory module\nsched_reserve: worst-case: n_tokens = 8, n_seqs = 1, n_outputs = 1\nsched_reserve: resolving fused Gated Delta Net support:\ngraph_reserve: reserving a graph for ubatch with n_tokens = 1, n_seqs = 1, n_outputs = 1\nsched_reserve: fused Gated Delta Net (autoregressive) enabled\ngraph_reserve: reserving a graph for ubatch with n_tokens = 16, n_seqs = 1, n_outputs = 16\nsched_reserve: fused Gated Delta Net (chunked) enabled\ngraph_reserve: reserving a graph for ubatch with n_tokens = 8, n_seqs = 1, n_outputs = 8\ngraph_reserve: reserving a graph for ubatch with n_tokens = 1, n_seqs = 1, n_outputs = 1\ngraph_reserve: reserving a graph for ubatch with n_tokens = 8, n_seqs = 1, n_outputs = 8\nsched_reserve: CUDA0 compute buffer size = 7.96 MiB\nsched_reserve: CUDA_Host compute buffer size = 0.38 MiB\nsched_reserve: graph nodes = 3783\nsched_reserve: graph splits = 2\nsched_reserve: reserve took 351.54 ms, sched copies = 1\nset_adapters_lora: adapters = 0x7fffd5276528\nadapters_lora_are_same: adapters = 0x7fffd5276528\nsched_reserve: reserving ...\nsched_reserve: max_nodes = 27232\nsched_reserve: reserving full memory module\nsched_reserve: worst-case: n_tokens = 8, n_seqs = 1, n_outputs = 1\ngraph_reserve: reserving a graph for ubatch with n_tokens = 8, n_seqs = 1, n_outputs = 8\ngraph_reserve: reserving a graph for ubatch with n_tokens = 1, n_seqs = 1, n_outputs = 1\ngraph_reserve: reserving a graph for ubatch with n_tokens = 8, n_seqs = 1, n_outputs = 8\nsched_reserve: CUDA0 compute buffer size = 7.96 MiB\nsched_reserve: CUDA_Host compute buffer size = 0.38 MiB\nsched_reserve: graph nodes = 3795\nsched_reserve: graph splits = 2\nsched_reserve: reserve took 221.18 ms, sched copies = 1\n~llama_context: CUDA0 compute buffer size is 7.9614 MiB, matches expectation of 7.9614 MiB\n~llama_context: CUDA_Host compute buffer size is 0.3831 MiB, matches expectation of 0.3831 MiB\nRELOAD_LOGITS_MAX_ABS_DIFF=0\nRELOAD_ADAPTER_MAX_ABS_DIFF=0\nSUBTEST_STATUS=PASS\nFINAL_STATUS=PASS\n"
],
"seconds": 3.8967783451080322,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_multitarget_parallel_acceptance/logs/native_save_reload.log"
},
{
"name": "NATIVE_MEMORY_RETURN",
"status": "PASS",
"summary": "Native memory mode passed using isolated child-process exit measurement.",
"details": [
"Measurement scope: child process exited before the parent sampled post-run memory.",
"Tolerance MiB: 96",
"Run 1 native internal before MiB: 0",
"Run 1 native internal after-exit MiB: 0",
"Run 1 native internal residual MiB: 0",
"Run 1 external before minimum MiB: 0",
"Run 1 external after minimum MiB: 0",
"Run 1 worker exit code: 0",
"Run 1 log: /content/prism_native_q1_lora/step08_memory_repair_v5/logs/memory_run_1.log",
"Run 2 native internal before MiB: 0",
"Run 2 native internal after-exit MiB: 0",
"Run 2 native internal residual MiB: 0",
"Run 2 external before minimum MiB: 0",
"Run 2 external after minimum MiB: 0",
"Run 2 worker exit code: 0",
"Run 2 log: /content/prism_native_q1_lora/step08_memory_repair_v5/logs/memory_run_2.log"
],
"seconds": 28.03964614868164,
"mandatory": true,
"log": "/content/prism_native_q1_lora/step08_memory_repair_v5/logs/memory_run_2.log"
},
{
"name": "THREE_TARGETS_ONE_GRAPH",
"status": "PASS",
"summary": "Native trio target count: 3",
"details": [
"Required: 3"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "ONLY_AB_OPTIMIZER_PARAMETERS",
"status": "PASS",
"summary": "Optimizer parameter tensor count: 6",
"details": [
"Required: 2 \u00d7 3 = 6"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "BASE_TENSORS_FROZEN",
"status": "PASS",
"summary": "Changed base bytes: 0",
"details": [
"Required: 0"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "NO_PERSISTENT_EXPANDED_BASE",
"status": "PASS",
"summary": "Persistent expanded base bytes: 0",
"details": [
"Required: 0"
],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "ALL_TARGETS_GRADIENT_AND_UPDATE",
"status": "PASS",
"summary": "Every A/B tensor has finite nonzero gradients and updates.",
"details": [],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "PER_TARGET_DIAGNOSTICS_COMPLETE",
"status": "PASS",
"summary": "Diagnostics cover all three targets.",
"details": [],
"seconds": 0.0,
"mandatory": true,
"log": null
},
{
"name": "NATIVE_8_6_TRIO_RUN_B",
"status": "PASS",
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