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| echo '🚀 Setting up Brev environment...' | ||
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| docker build --pull --no-cache --tag circuit_training:gpu --build-arg base_image=nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04 --build-arg tf_agents_version='tf-agents-nightly[reverb]' --build-arg dreamplace_version='dreamplace_20231214_c5a83e5_python3.9.tar.gz' -f tools/docker/ubuntu_circuit_training ./tools/docker/ | ||
| docker run --rm --gpus all -v $(pwd):/workspace --workdir /workspace circuit_training:gpu bash tools/e2e_smoke_test.sh --root_dir /workspace/logs |
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Unquoted command substitution breaks on paths with spaces
The $(pwd) in the docker volume mount -v $(pwd):/workspace is unquoted. If the current working directory contains spaces or special characters, bash will perform word splitting and the docker command will fail with a confusing error. This needs to be quoted as "$(pwd)" to handle paths with spaces correctly.
| echo '🚀 Setting up Brev environment...' | ||
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| docker build --pull --no-cache --tag circuit_training:gpu --build-arg base_image=nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04 --build-arg tf_agents_version='tf-agents-nightly[reverb]' --build-arg dreamplace_version='dreamplace_20231214_c5a83e5_python3.9.tar.gz' -f tools/docker/ubuntu_circuit_training ./tools/docker/ | ||
| docker run --rm --gpus all -v $(pwd):/workspace --workdir /workspace circuit_training:gpu bash tools/e2e_smoke_test.sh --root_dir /workspace/logs |
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Missing logs directory creation before smoke test
The script runs the smoke test with --root_dir /workspace/logs but doesn't create the logs directory first. The smoke test script writes to files like ${ROOT_DIR}/reverb.log, which will fail if the directory doesn't exist. The README documentation shows a required mkdir -p logs step before running the docker container that's missing from this script.
| echo '🚀 Setting up Brev environment...' | ||
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| docker build --pull --no-cache --tag circuit_training:gpu --build-arg base_image=nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04 --build-arg tf_agents_version='tf-agents-nightly[reverb]' --build-arg dreamplace_version='dreamplace_20231214_c5a83e5_python3.9.tar.gz' -f tools/docker/ubuntu_circuit_training ./tools/docker/ | ||
| docker run --rm --gpus all -v $(pwd):/workspace --workdir /workspace circuit_training:gpu bash tools/e2e_smoke_test.sh --root_dir /workspace/logs |
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GPU resources provisioned but not used for training
The configuration provisions 4x H100 GPUs but the smoke test command doesn't include --use_gpu True, so training runs on CPU by default. The tools/README.md shows that --use_gpu True is needed when running on GPU hardware. Without this flag, expensive GPU resources are allocated but not actually used for training, wasting compute resources.
Additional Locations (1)
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Brev Doctor Configuration
This PR was automatically generated by Brev Doctor to configure your GPU development environment.
Files Added:
.brev/setup.shbrev-launchable.yamlNext Steps:
Generated by Brev Doctor
Note
Adds Brev.dev environment scaffolding to build and validate a GPU Docker image and define launch requirements.
.brev/setup.shbuildscircuit_training:gpu(CUDA 11.8, cuDNN 8) withtf-agents-nightly[reverb]anddreamplace_20231214_c5a83e5_python3.9.tar.gz, then runstools/e2e_smoke_test.shon GPUsbrev-launchable.yamlspecifies a launchable config (H100 x4, 80GB VRAM each; 32 vCPUs; 256GB RAM; 500GB disk) and wires setup viascript: .brev/setup.shWritten by Cursor Bugbot for commit 4b61e4f. This will update automatically on new commits. Configure here.