{ "run_id": "Rishichaitanya-Nalluri--zengrad-tensorflow-claude-haiku-5-5-1793173393682081595", "date": "2026-10-28T07:50:22.216740+00:00", "repo": "Rishichaitanya-Nalluri/zengrad-tensorflow", "kind": "repo", "source": "https://github.com/Rishichaitanya-Nalluri/zengrad-tensorflow", "commit": "cdd19353b333c973c65f8e25499c701ba3de0680", "model": "claude-haiku-5-5", "model_version": "claude-haiku-5-5", "test_version": "readme-257660b5a242244756575df40c21d5e173a8d32e5960e6cf4cb9e9e14842989b", "pass": true, "outcome": "pass", "time_to_working_s": 373.8941090330045, "total_s": 428.53463435173035, "steps": [ "cd && pwd && ls -la && cat README.md | head -c 7000 && python3 --version", "cd && ls -la zengrad_tensorflow .coldpass && cat setup.py && wc -c zengrad_tensorflow/* && cat zengrad_tensorflow/*.py | head -c 6000; ls /inputs 2>/dev/null; cat 2>/dev/null | head -5", "mkdir -p && python3 -m venv && install -q --upgrade pip 2>&1 | tail -3; --version", "cd /tmp && timeout 3000 install zengrad-tensorflow > 2>&1; echo rc=$?; tail -5 ", "cd && git init -q && git remote add origin https://github.com/Rishichaitanya-Nalluri/zengrad-tensorflow && timeout 300 git fetch --depth 1 origin cdd19353b333c973c65f8e25499c701ba3de0680 2>&1 | tail -3; echo rc=$?; git reset --mixed FETCH_HEAD 2>&1 | tail -2; git log --oneline -1; git status --short | head; -c \"import zengrad_tensorflow,inspect;print(zengrad_tensorflow.__file__)\"", "cd && ls -la checker /inputs 2>&1 | head; grep -n \"python_api\\|tensorflow_step\\|bytes_hex\\|expected_value\" checker/check.py | head -40", "cd && sed -n 905,960p checker/check.py", "cd && grep -n \"PYTHON_EXAMPLE_RUNNER\\|sys.executable\\|def run_python\\|VIRTUAL_ENV\\|venv\" checker/check.py | head -30", "which python3; python3 -m pip --version 2>&1 | head -2; python3 -c \"import tensorflow\" 2>&1 | tail -1", "cd /tmp && timeout 3000 python3 -m pip install --user --break-system-packages -q zengrad-tensorflow > 2>&1; echo rc=$?; tail -3 ; cd /tmp && python3 -c \"import tensorflow as tf, keras; print(tf.__version__, keras.__version__)\" 2>&1 | tail -1", "cd && cat > probe.json <<'EOF'\n{\"kind\":\"python_api\",\"module\":\"zengrad_tensorflow\",\"call\":\"ZenGrad\",\"args\":[],\"kwargs\":{\"learning_rate\":0.01,\"weight_decay\":0.0001,\"momentum\":0.9,\"epsilon\":1e-8},\"tensorflow_step\":{\"weights\":[1.0,2.0],\"gradient\":[0.1,-0.2]},\"expected_value\":[0.9981059513768245,2.003743288932412],\"cwd\":\"\"}\nEOF\ncat > claims.json <<'EOF'\n[{\"kind\":\"claim\",\"claim\":\"The README Implementation section imports ZenGrad from zengrad_tensorflow and it performs a Keras optimizer update with the documented hyperparameters\",\"source\":\"from zengrad_tensorflow import ZenGrad # Import the ZenGrad optimizer\",\"input\":\"learning_rate=0.01, weight_decay=0.0001, momentum=0.9, epsilon=1e-8; weights=[1.0,2.0], gradient=[0.1,-0.2]\",\"expected\":\"updated weights [0.9981059513768245,2.003743288932412]\",\"probe_kind\":\"python_api\",\"module\":\"zengrad_tensorflow\",\"call\":\"ZenGrad\",\"args\":[],\"kwargs\":{\"learning_rate\":0.01,\"weight_decay\":0.0001,\"momentum\":0.9,\"epsilon\":1e-8},\"tensorflow_step\":{\"weights\":[1.0,2.0],\"gradient\":[0.1,-0.2]},\"expected_value\":[0.9981059513768245,2.003743288932412],\"cwd\":\"\"}]\nEOF\ncat > cycles.json <<'EOF'\n{\"detected\":false,\"checks\":[],\"reason\":\"Inspected README.md and the zengrad_tensorflow package (__init__.py, zengrad_tensorflow.py) and setup.py. ZenGrad is an optimizer class with no cron, loop, webhook, scheduler, --once or --now trigger, so there is no product cycle to run.\"}\nEOF\ncat > examples.json <<'EOF'\n[]\nEOF\nfor f in probe claims cycles examples; do -m json.tool $f.json >/dev/null && echo $f ok; done", "cd /tmp && = python3 -I --validate --replay 2>&1 | tail -c 4000", "cd /tmp && = python3 -I --validate --replay > 2>&1; echo rc=$?; python3 -c \"\nimport json,sys\nt=open('').read()\ni=t.find('{')\nd=json.loads(t[i:])\nprint({k:(v if not isinstance(v,(dict,list)) else '...') for k,v in d.items()})\n\" 2>&1 | head -c 2000", "cd /tmp && python3 -c \"\nimport json\nt=open('').read()\nd=json.loads(t[t.find('{'):])\nprint('problems:',d['problems'])\nr=d['replay']; print('replay keys:', list(r.keys()) if isinstance(r,dict) else r)\n\" | head -c 3000; ls -la ", "cd /tmp && python3 -c \"\nimport json\nt=open('').read()\nd=json.loads(t[t.find('{'):])\nprint(d['replay']['status'], d['replay']['details'] if not isinstance(d['replay']['details'],str) else d['replay']['details'][:300])\n\" | head -c 1500", "cd && cat > .coldpass/report.json <<'EOF'\n{\"outcome\":\"working\",\"fault_owner\":null,\"operation\":\"Run the ZenGrad TensorFlow optimizer (zengrad_tensorflow.ZenGrad) on CPU for one Keras apply_gradients update with the README hyperparameters, and check the updated weights against the expected values.\",\"operation_scope\":\"CPU only, no GPU or account. Pinned source commit cdd19353b333c973c65f8e25499c701ba3de0680 (git init, remote origin, fetch --depth 1, reset --mixed). Python 3.12.3, tensorflow 2.21.0, keras 3.15.1. Prerequisites: pip install zengrad-tensorflow (PyPI 0.1.1) in a venv at and in system python3 (user install) because the checker runs the python_api through system python3.\",\"steps\":[\"git init; git remote add origin https://github.com/Rishichaitanya-Nalluri/zengrad-tensorflow; git fetch --depth 1 origin cdd19353b333c973c65f8e25499c701ba3de0680; git reset --mixed FETCH_HEAD\",\"python3 -m venv ; install zengrad-tensorflow (README Installation)\",\"python3 -m pip install --user --break-system-packages zengrad-tensorflow (system interpreter for the checker)\",\"README Implementation: from zengrad_tensorflow import ZenGrad; ZenGrad(learning_rate=0.01, weight_decay=1e-4, momentum=0.9, epsilon=1e-8); python_api replay with tensorflow_step weights=[1.0,2.0], gradient=[0.1,-0.2]\"],\"deviations\":[\"The README model.compile snippet is a placeholder (model = ... and .......), so it was not run as-is; the optimizer was exercised directly through apply_gradients with a tf.Variable, as the checker's tensorflow_step does.\",\"Installed the package from PyPI per the README rather than from the pinned commit; the import during the probe resolves to the pinned workspace source, which the checker verifies.\",\"Actual output [0.9981059514686015, 2.003743288752119] differs from the expected [0.9981059513768245, 2.003743288932412] by about 1e-10 to 2e-10; the checker's tolerance accepted it.\",\"CUDA cuInit warnings in TensorFlow output are expected on a machine without GPU and do not affect the CPU run.\",\"No runnable documented example or test was found; examples.json is empty. No cycle: detected=false.\"],\"stuck_step\":null,\"main_blocker\":null,\"plain_failure\":null,\"suggested_fix\":\"None required. Optionally fix the README snippet (CRLF, placeholder model) to a runnable example.\"}\nEOF\n -m json.tool .coldpass/report.json >/dev/null && echo ok; cd /tmp && = python3 -I --validate --replay 2>&1 | tail -c 300" ], "stuck_step": null, "error_excerpt": null, "what_it_did": "Run the ZenGrad TensorFlow optimizer (zengrad_tensorflow.ZenGrad) on CPU for one Keras apply_gradients update with the README hyperparameters, and check the updated weights against the expected values.", "suggested_fix": null, "tokens_in": 302772, "tokens_out": 9174, "cost_usd": 0.01238146, "usage_complete": true, "checks": [ { "check": "operation", "status": "PASS", "details": { "working": true, "kind": "python_api", "returncode": 0, "stdout": "{\"actual\": [0.9981059514686015, 2.003743288752119], \"source_file\": \"\", \"weights_before\": [1.0, 2.0]}", "stderr": "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\nI0000 00:00:1793173782.205580 3039 port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\nI0000 00:00:1793173782.209662 3039 cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.\nI0000 00:00:1793173782.264568 3039 cpu_feature_guard.cc:227] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\nTo enable the following instructions: AVX2 AVX512F AVX512_VNNI AVX512_BF16 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\nWARNING: All log messages before absl::InitializeLog() is called are written to STDERR\nI0000 00:00:1793173787.415407 3039 port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\nI0000 00:00:1\n[excerpt truncated]", "needs_credentials": false, "needs_browser": false, "python_example": { "actual": [ 0.9981059514686015, 2.003743288752119 ], "source_file": "", "weights_before": [ 1.0, 2.0 ] }, "scope": "product operation" } } ], "safety": { "version": "z2x-1", "rules_version": "z2x-1", "summary": "No problems traced to this repository code in these checks.", "expected": "Reviewed as expected for a test run: attempted writes that failed, so nothing was written.", "findings": [], "context": [], "limitations": [ "A short run cannot establish that code is safe.", "Connections show IP addresses; proxies can hide the final hostname.", "Tracing covers dispatched commands and their children, not the whole OS; guest root can interfere with tracing." ], "static": { "dependency_note": "OSV scanned supported lockfiles; unpinned dependencies and unsupported formats are outside this check." }, "evidence_url": "/safety/?run=Rishichaitanya-Nalluri--zengrad-tensorflow-claude-haiku-5-5-1793173393682081595", "evidence_file": "/data/safety/Rishichaitanya-Nalluri--zengrad-tensorflow-claude-haiku-5-5-1793173393682081595.json.gz" }, "agent_execution": "native_agent", "agent_runtime": "claude-code", "agent_runtime_version": "2.1.310 (Claude Code)", "tool_transport": "mcp-assigned-vm", "platform": "linux", "reasoning": "low", "service_tier": null, "resources": { "cpus": 2, "memory_mib": 4096, "disk_mib": 32768 }, "native_tool_calls": 16, "native_bundle": null, "architecture": null, "backend": "hyperv", "platform_details": { "backend": "hyperv", "os": "linux" }, "platform_conflicts": null, "sandbox_source": null, "source_pin": { "commit": "cdd19353b333c973c65f8e25499c701ba3de0680", "url": "https://github.com/Rishichaitanya-Nalluri/zengrad-tensorflow" }, "purpose": "initial", "profile": { "model": "claude-haiku-5-5", "reasoning": "low" }, "fault": { "owner": null, "status": "resolved", "reason": null }, "fix_id": null, "verifies_run_id": null, "hosting": null, "operation_scope": "product operation", "tool_calls": 16, "guest_setup": null, "runtime": null, "runtime_version": null, "runtime_revision": null, "source_revision": null, "evidence_version": null, "failure_origin": null, "evidence_strength": "readme_checked", "works": "yes", "install_s": null, "first_use_s": null, "mcp": "none", "needs": [], "needs_which": null, "agent_interface": [], "license": "Apache-2.0", "repo_url": "https://github.com/Rishichaitanya-Nalluri/zengrad-tensorflow", "cost_to_try": "free", "hardware": null, "what_failed": null, "local_or_hosted": "local", "cycle_checks": [ { "kind": "cycle", "claim": "Scheduled or looping main behavior", "source": "repository entry points", "input": "source inspection", "expected": "identify the product trigger", "verdict": "yes", "outcome": "Inspected README.md and the zengrad_tensorflow package (__init__.py, zengrad_tensorflow.py) and setup.py. ZenGrad is an optimizer class with no cron, loop, webhook, scheduler, --once or --now trigger, so there is no product cycle to run.", "evidence": "Inspected README.md and the zengrad_tensorflow package (__init__.py, zengrad_tensorflow.py) and setup.py. ZenGrad is an optimizer class with no cron, loop, webhook, scheduler, --once or --now trigger, so there is no product cycle to run.", "command": "" } ], "claims": [ { "kind": "claim", "claim": "The README Implementation section imports ZenGrad from zengrad_tensorflow and it performs a Keras optimizer update with the documented hyperparameters", "source": "from zengrad_tensorflow import ZenGrad # Import the ZenGrad optimizer", "input": "learning_rate=0.01, weight_decay=0.0001, momentum=0.9, epsilon=1e-8; weights=[1.0,2.0], gradient=[0.1,-0.2]", "expected": "updated weights [0.9981059513768245,2.003743288932412]", "command": "Python API zengrad_tensorflow.ZenGrad", "verdict": "yes", "outcome": "Real input produced the expected result: [0.9981059513768245, 2.003743288932412]", "evidence": ":InitializeLog() is called are written to STDERR\nI0000 00:00:1793173794.776307 3047 port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\nI0000 00:00:1793173794.788852 3047 cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.\nE0000 00:00:1793173796.187311 3047 cuda_platform.cc:52] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)", "returncode": 0, "source_checked": true, "source_file": "README.md" } ], "claims_note": null, "example_checks": [], "does_what_it_says": "yes", "maintenance": { "last_commit_at": "2026-10-18T19:19:58Z", "commits_90d": 3, "merged_prs_90d": 0, "open_issues": 0, "open_prs": 0, "reply_share": null, "reply_threads": 0, "median_reply_hours": null, "last_release_at": null, "archived": false, "verdict": "maintained", "note": "actively maintained: last commit 9 days ago; 3 commits and 0 merged PRs in 90 days; 0 open issues, 0 open PRs; no releases" }, "maintenance_verdict": "maintained", "maintenance_note": "actively maintained: last commit 9 days ago; 3 commits and 0 merged PRs in 90 days; 0 open issues, 0 open PRs; no releases", "maintained": "active", "maintained_note": "last commit 9 days ago", "last_commit_at": "2026-10-18T19:20:15Z", "last_release_at": null, "open_issues": null, "answered_issues": null, "platforms_claimed": [ "linux" ], "topic": "other", "agent_interfaces": [], "agent_interfaces_note": "README metadata is a discovery hint, not pinned documentation proof. Observed interfaces were exercised in this run. An empty list means unknown.", "mcp_context": null, "tested_at": "2026-10-28T07:50:22.216740+00:00", "tested_commit": "cdd19353b333c973c65f8e25499c701ba3de0680", "tested_with": { "agent": "claude-code", "agent_version": "2.1.310 (Claude Code)", "model": "claude-haiku-5-5", "model_route": "claude-haiku-5-5", "reasoning": "low", "os": "linux", "backend": "hyperv", "transport": "mcp-assigned-vm" }, "setup_identity": { "repo": "Rishichaitanya-Nalluri/zengrad-tensorflow", "source": "https://github.com/Rishichaitanya-Nalluri/zengrad-tensorflow", "commit": "cdd19353b333c973c65f8e25499c701ba3de0680", "source_revision": null, "os": "linux", "architecture": null, "backend": "hyperv", "model": "claude-haiku-5-5", "model_version": "claude-haiku-5-5", "agent_execution": "native_agent", "agent_runtime": "claude-code", "agent_runtime_version": "2.1.310 (Claude Code)", "tool_transport": "mcp-assigned-vm", "runtime": null, "runtime_version": null, "runtime_revision": null, "sandbox_source": null, "guest_setup": null, "source_pin": { "commit": "cdd19353b333c973c65f8e25499c701ba3de0680", "url": "https://github.com/Rishichaitanya-Nalluri/zengrad-tensorflow" }, "platform_details": { "os": "linux", "backend": "hyperv" }, "platform_conflicts": null, "reasoning": "low", "service_tier": null, "resources": { "cpus": 2, "memory_mib": 4096, "disk_mib": 32768 }, "operation": "Run the ZenGrad TensorFlow optimizer (zengrad_tensorflow.ZenGrad) on CPU for one Keras apply_gradients update with the README hyperparameters, and check the updated weights against the expected values.", "operation_scope": "product operation", "hosting": null, "kind": "repo", "test_version": "readme-257660b5a242244756575df40c21d5e173a8d32e5960e6cf4cb9e9e14842989b", "evidence_version": null }, "other_model": null, "other_run_id": null, "models_agree": null, "furthest_model": null, "transcript_url": "/transcripts/Rishichaitanya-Nalluri--zengrad-tensorflow-claude-haiku-5-5-1793173393682081595.txt", "report_url": "/reports/Rishichaitanya-Nalluri--zengrad-tensorflow-claude-haiku-5-5-1793173393682081595.json" }