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Merge pull request ROCm#403 from ROCm/upstream_merge_25_02_03
Upstream merge 25 02 03
2 parents fdb06c3 + c887bc9 commit b43c8d1

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.buildkite/check-wheel-size.py

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# SPDX-License-Identifier: Apache-2.0
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import os
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import sys
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import zipfile
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# Read the VLLM_MAX_SIZE_MB environment variable, defaulting to 300 MiB
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# Read the VLLM_MAX_SIZE_MB environment variable, defaulting to 400 MiB
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# Note that we have 400 MiB quota, please use it wisely.
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# See https://github.com/pypi/support/issues/3792 .
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# Please also sync the value with the one in Dockerfile.
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VLLM_MAX_SIZE_MB = int(os.environ.get('VLLM_MAX_SIZE_MB', 300))
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VLLM_MAX_SIZE_MB = int(os.environ.get('VLLM_MAX_SIZE_MB', 400))
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def print_top_10_largest_files(zip_file):

.buildkite/generate_index.py

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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import os
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.buildkite/lm-eval-harness/test_lm_eval_correctness.py

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# SPDX-License-Identifier: Apache-2.0
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"""
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LM eval harness on model to compare vs HF baseline computed offline.
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Configs are found in configs/$MODEL.yaml

.buildkite/nightly-benchmarks/scripts/convert-results-json-to-markdown.py

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# SPDX-License-Identifier: Apache-2.0
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import json
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import os
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from pathlib import Path

.buildkite/nightly-benchmarks/scripts/download-tokenizer.py

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# SPDX-License-Identifier: Apache-2.0
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import argparse
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from transformers import AutoTokenizer

.buildkite/nightly-benchmarks/scripts/generate-nightly-markdown.py

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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import json
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from pathlib import Path

.buildkite/nightly-benchmarks/scripts/get-lmdeploy-modelname.py

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# SPDX-License-Identifier: Apache-2.0
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from lmdeploy.serve.openai.api_client import APIClient
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api_client = APIClient("http://localhost:8000")

.buildkite/nightly-benchmarks/scripts/summary-nightly-results.py

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# SPDX-License-Identifier: Apache-2.0
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import datetime
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import json
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import os

.buildkite/release-pipeline.yaml

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env:
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DOCKER_BUILDKIT: "1"
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- input: "Provide Release version here"
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fields:
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- text: "What is the release version?"
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key: "release-version"
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- block: "Build CPU release image"
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key: block-cpu-release-image-build
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depends_on: ~
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queue: cpu_queue_postmerge
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commands:
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- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
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- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$RELEASE_VERSION --progress plain -f Dockerfile.cpu ."
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- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$RELEASE_VERSION"
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- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version) --progress plain -f Dockerfile.cpu ."
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- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
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env:
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DOCKER_BUILDKIT: "1"

.buildkite/run-gh200-test.sh

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remove_docker_container
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# Run the image and test offline inference
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docker run --name gh200-test --gpus=all --entrypoint="" gh200-test bash -c '
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python3 examples/offline_inference/basic.py
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docker run -e HF_TOKEN -v /root/.cache/huggingface:/root/.cache/huggingface --name gh200-test --gpus=all --entrypoint="" gh200-test bash -c '
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python3 examples/offline_inference/cli.py --model meta-llama/Llama-3.2-1B
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'

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