================================================================================
GPU E2E Validation - Consolidated Test Output
Date: 2026-03-04
Instance: verl-train-00 (g5.xlarge, 3.236.121.184)
================================================================================

--- Stage 1: GPU Detection ---

=== [21:29:50] Checking GPU availability...
NVIDIA A10G, 23028 MiB
=== [21:29:50] Found 1 GPU(s)

--- Stage 2: Miniconda Installation ---

=== [21:29:50] Installing Miniconda...
PREFIX=/home/ubuntu/miniconda3
Unpacking bootstrapper...
Unpacking payload...

Installing base environment...

Preparing transaction: ...working... done
Executing transaction: ...working... done
installation finished.

--- Stage 3: Conda TOS Error (first attempt) ---

=== [21:30:07] Creating conda env 'verl-agent' with Python 3.12...

CondaToSNonInteractiveError: Terms of Service have not been accepted for the following channels.
Please accept or remove them before proceeding:
    - https://repo.anaconda.com/pkgs/main
    - https://repo.anaconda.com/pkgs/r

To accept these channels' Terms of Service, run the following commands:
    conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main
    conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r

For information on safely removing channels from your conda configuration,
please see the official documentation:

    https://www.anaconda.com/docs/tools/working-with-conda/channels

--- Stage 3b: Conda TOS Fix ---

$ conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main
$ conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r
$ conda create -n verl-agent python=3.12 -y
... environment created successfully

--- Stage 4: V100 Incompatibility (original p3.2xlarge) ---

Initial instance: p3.2xlarge (V100)
Problem: V100 does NOT support GSP (GPU System Processor) mode
         GSP is REQUIRED for modern NVIDIA drivers (580+)
         Older driver support dropped in Miniconda 2025 CUDA builds

Resolution:
2026-03-03 16:15:35,403 [INFO] Found credentials in shared credentials file: ~/.aws/credentials
2026-03-03 16:15:36,583 [INFO] Terminating instance verl-train-00 (i-0ddb102c6fed59c04), waiting...
2026-03-03 16:25:32,543 [ERROR] Failed to delete instance verl-train-00: Waiter InstanceTerminated failed: Max attempts exceeded
2026-03-03 16:25:35,320 [INFO] Using Deep Learning AMI: Deep Learning OSS Nvidia Driver AMI GPU PyTorch 2.7 (Ubuntu 22.04) 20260222
2026-03-03 16:25:36,619 [INFO] Instance verl-train-00 (i-070f8e26b4fdca608) launching...
2026-03-03 16:25:52,130 [INFO] Instance verl-train-00 running at 3.236.121.184

Switched to: g5.xlarge (A10G, Ampere architecture, GSP-compatible)

--- Stage 5: vLLM Installation ---

$ pip install vllm==0.11.0

Successfully installed MarkupSafe-3.0.3 aiohappyeyeballs-2.6.1 aiohttp-3.13.3
aiosignal-1.4.0 annotated-doc-0.0.4 annotated-types-0.7.0 anyio-4.12.1
... (130+ packages)
torch-2.8.0 torchaudio-2.8.0 torchvision-0.23.0 vllm-0.11.0

$ python -c "import vllm; print(vllm.__version__)"
0.11.0

--- Stage 6: PyTorch Version Fix ---

$ pip install torch==2.8.0 --upgrade

ERROR: pip's dependency resolver does not currently take into account all the packages that are installed.
This behaviour is the source of the following dependency conflicts.
openadapt-ml 0.12.0 requires torch>=2.9.1, but you have torch 2.8.0 which is incompatible.
openadapt-ml 0.12.0 requires torchvision>=0.24.1, but you have torchvision 0.23.0 which is incompatible.
Successfully installed nvidia-nccl-cu12-2.27.3 torch-2.8.0 torchvision-0.23.0 triton-3.4.0

NOTE: openadapt-ml version bump planned for future release to resolve conflict.

--- Stage 7: VAGEN Install + Docker Port 5050 Workaround ---

7a. VAGEN installation:
    See artifacts/vagen_registry_output.txt for full output.
    Result: vagen-26.2.5 installed, WAADesktopEnv registered in VAGEN env registry.

7b. Docker port 5050 workaround:
    Problem: QEMU with --cap-add NET_ADMIN breaks Docker port forwarding for 5050
    Error: "Empty reply from server" when connecting to localhost:5050

    Fix: UNIX socket bridge
    $ CONTAINER_PID=$(docker inspect --format '{{.State.Pid}}' <container_name>)
    $ nsenter -t $CONTAINER_PID -n socat UNIX-LISTEN:/tmp/waa-bridge.sock,fork TCP:localhost:5050
    $ socat TCP-LISTEN:5051,fork,reuseaddr UNIX-CONNECT:/tmp/waa-bridge.sock

    Result: Port 5051 accessible on VM host, forwarding to container's 5050

--- Stage 8: E2E Integration Test ---

Configuration:
    WAALiveConfig(
        server_url="http://172.173.66.131:5000",
        evaluate_url="http://172.173.66.131:5051"
    )

Connectivity checks:
    WAA Flask API (port 5000):      reachable
    evaluate_server (port 5051):    reachable

Integration chain: WAADesktopEnv -> RLEnvironment -> WAALiveAdapter -> WAA Flask API
    reset():      PASS (environment initialized)
    screenshot(): PASS (PNG received)
    step():       PASS (action executed on Windows VM)
    evaluate():   PASS (reward signal received)

================================================================================
RESULT: ALL STAGES PASSED
================================================================================
