Merge pull request #4 from JArnoldAMD/amd-pin-triton

Pin versions in AMD Docker
mlcommons · Oct 8, 2024 · 30d19b7 · 30d19b7
2 parents 1179bcc + d252efa
commit 30d19b7
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diff --git a/closed/AMD/code/llama2-70b-99.9/README.md b/closed/AMD/code/llama2-70b-99.9/README.md
@@ -48,17 +48,17 @@ KV cache scales for the quantized model weights are used and were downloaded fro
 To generate results for the full submission, running the command below in an inference container. Logs can be found in `/lab-hist/mlperf-results/$datetime1/$datetime2`.
 ``` bash
 cd /lab-mlperf-inference/code/llama2-70b-99.9/test_VllmFp8
-./run_scenarios.sh
+bash ./run_scenarios.sh
 ```
 
 To generate results for the Offline scenario only, run the command below in an inference container. Logs can be found in `/lab-hist/mlperf-results/$datetime1/$datetime2/Offline`.
 ``` bash
 cd /lab-mlperf-inference/code/llama2-70b-99.9/test_VllmFp8
-./run_tests_Offline.sh
+bash ./run_tests_Offline.sh
 ```
 
 To generate results for the Server scenario only, run the command below in an inference container. Logs can be found in `/lab-hist/mlperf-results/$datetime1/$datetime2/Server`.
 ``` bash
 cd /lab-mlperf-inference/code/llama2-70b-99.9/test_VllmFp8
-./run_tests_Server.sh
-```
+bash ./run_tests_Server.sh
+```
diff --git a/closed/AMD/code/llama2-70b-99.9/test_VllmFp8/run_scenarios.sh b/closed/AMD/code/llama2-70b-99.9/test_VllmFp8/run_scenarios.sh
@@ -11,18 +11,12 @@ export RESULTS_DIR=${LAB_CLOG}/${TS_START_BENCHMARKS}
 echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
 
 echo "Running Offline"
-./run_tests_Offline.sh
+bash run_tests_Offline.sh
 echo "Done Offline"
 
 echo "Running Server"
-./run_tests_Server.sh
+bash run_tests_Server.sh
 echo "Done Server"
 
 echo "Done Benchmarks"
 echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
-
-echo "Packaging and checking submission results"
-python ../submission/package_submission.py \
-    --base-package-dir ${PACKAGE_DRAFT_DIR} \
-    --system-name ${SYSTEM_NAME} \
-    --input-dir ${RESULTS_DIR}
diff --git a/closed/AMD/code/llama2-70b-99.9/test_VllmFp8/run_tests_Offline.sh b/closed/AMD/code/llama2-70b-99.9/test_VllmFp8/run_tests_Offline.sh
@@ -12,11 +12,11 @@ echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
 for i in $(seq 1 ${NUM_ITERS})
 do
         echo "Running $SCENARIO - Performance run $i/$NUM_ITERS"
-        ITER=$i ./test_VllmFp8_Offline_perf.sh
+        ITER=$i bash test_VllmFp8_Offline_perf.sh
 done
 echo "Running $SCENARIO - Accuracy"
-./test_VllmFp8_Offline_acc.sh
+bash test_VllmFp8_Offline_acc.sh
 echo "Running $SCENARIO - Audit"
-./test_VllmFp8_Offline_audit.sh
+bash test_VllmFp8_Offline_audit.sh
 echo "Done"
-echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
+echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
diff --git a/closed/AMD/code/llama2-70b-99.9/test_VllmFp8/run_tests_Server.sh b/closed/AMD/code/llama2-70b-99.9/test_VllmFp8/run_tests_Server.sh
@@ -11,11 +11,11 @@ echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
 for i in $(seq 1 ${NUM_ITERS})
 do
         echo "Running $SCENARIO - Performance run $i/$NUM_ITERS"
-        ITER=$i ./test_VllmFp8_SyncServer_perf.sh
+        ITER=$i bash test_VllmFp8_SyncServer_perf.sh
 done
 echo "Running $SCENARIO - Accuracy"
-./test_VllmFp8_SyncServer_acc.sh
+bash test_VllmFp8_SyncServer_acc.sh
 echo "Running $SCENARIO - Audit"
-./test_VllmFp8_SyncServer_audit.sh
+bash test_VllmFp8_SyncServer_audit.sh
 echo "Done SyncServer"
-echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
+echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
diff --git a/closed/AMD/code/llama2-70b-99/README.md b/closed/AMD/code/llama2-70b-99/README.md
@@ -48,17 +48,17 @@ KV cache scales for the quantized model weights are used and were downloaded fro
 To generate results for the full submission, running the command below in an inference container. Logs can be found in `/lab-hist/mlperf-results/$datetime1/$datetime2`.
 ``` bash
 cd /lab-mlperf-inference/code/llama2-70b-99.9/test_VllmFp8
-./run_scenarios.sh
+bash ./run_scenarios.sh
 ```
 
 To generate results for the Offline scenario only, run the command below in an inference container. Logs can be found in `/lab-hist/mlperf-results/$datetime1/$datetime2/Offline`.
 ``` bash
 cd /lab-mlperf-inference/code/llama2-70b-99.9/test_VllmFp8
-./run_tests_Offline.sh
+bash ./run_tests_Offline.sh
 ```
 
 To generate results for the Server scenario only, run the command below in an inference container. Logs can be found in `/lab-hist/mlperf-results/$datetime1/$datetime2/Server`.
 ``` bash
 cd /lab-mlperf-inference/code/llama2-70b-99.9/test_VllmFp8
-./run_tests_Server.sh
-```
+bash ./run_tests_Server.sh
+```
diff --git a/closed/AMD/code/llama2-70b-99/test_VllmFp8/run_scenarios.sh b/closed/AMD/code/llama2-70b-99/test_VllmFp8/run_scenarios.sh
@@ -11,18 +11,12 @@ export RESULTS_DIR=${LAB_CLOG}/${TS_START_BENCHMARKS}
 echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
 
 echo "Running Offline"
-./run_tests_Offline.sh
+bash run_tests_Offline.sh
 echo "Done Offline"
 
 echo "Running Server"
-./run_tests_Server.sh
+bash run_tests_Server.sh
 echo "Done Server"
 
 echo "Done Benchmarks"
 echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
-
-echo "Packaging and checking submission results"
-python ../submission/package_submission.py \
-    --base-package-dir ${PACKAGE_DRAFT_DIR} \
-    --system-name ${SYSTEM_NAME} \
-    --input-dir ${RESULTS_DIR}
diff --git a/closed/AMD/code/llama2-70b-99/test_VllmFp8/run_tests_Offline.sh b/closed/AMD/code/llama2-70b-99/test_VllmFp8/run_tests_Offline.sh
@@ -12,11 +12,11 @@ echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
 for i in $(seq 1 ${NUM_ITERS})
 do
         echo "Running $SCENARIO - Performance run $i/$NUM_ITERS"
-        ITER=$i ./test_VllmFp8_Offline_perf.sh
+        ITER=$i bash test_VllmFp8_Offline_perf.sh
 done
 echo "Running $SCENARIO - Accuracy"
-./test_VllmFp8_Offline_acc.sh
+bash test_VllmFp8_Offline_acc.sh
 echo "Running $SCENARIO - Audit"
-./test_VllmFp8_Offline_audit.sh
+bash test_VllmFp8_Offline_audit.sh
 echo "Done"
-echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
+echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
diff --git a/closed/AMD/code/llama2-70b-99/test_VllmFp8/run_tests_Server.sh b/closed/AMD/code/llama2-70b-99/test_VllmFp8/run_tests_Server.sh
@@ -11,11 +11,11 @@ echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
 for i in $(seq 1 ${NUM_ITERS})
 do
         echo "Running $SCENARIO - Performance run $i/$NUM_ITERS"
-        ITER=$i ./test_VllmFp8_SyncServer_perf.sh
+        ITER=$i bash test_VllmFp8_SyncServer_perf.sh
 done
 echo "Running $SCENARIO - Accuracy"
-./test_VllmFp8_SyncServer_acc.sh
+bash test_VllmFp8_SyncServer_acc.sh
 echo "Running $SCENARIO - Audit"
-./test_VllmFp8_SyncServer_audit.sh
+bash test_VllmFp8_SyncServer_audit.sh
 echo "Done SyncServer"
-echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
+echo "TS_START_BENCHMARKS=${TS_START_BENCHMARKS}"
diff --git a/closed/AMD/docker/Dockerfile.llama2 b/closed/AMD/docker/Dockerfile.llama2
@@ -7,13 +7,13 @@ RUN apt update \
  && rm -rf /var/lib/apt/lists/*
 
 RUN pip install \
-	absl-py \
-	datasets \
-	evaluate \
-	nltk \
+	absl-py==2.1.0 \
+	datasets==2.20.0 \
+	evaluate==0.4.2 \
+	nltk==3.8.1 \
 	numpy==1.26.4 \
-	py-libnuma \
-	rouge_score
+	py-libnuma==1.2 \
+	rouge_score==0.1.2
 
 WORKDIR /app
 RUN git clone --recurse-submodules https://github.com/mlcommons/inference.git --branch v4.1 --depth 1 mlperf_inference \

diff --git a/closed/AMD/docker/build_llama2.sh b/closed/AMD/docker/build_llama2.sh
@@ -3,6 +3,7 @@ BASE_IMAGE=rocm/pytorch:rocm6.1.2_ubuntu20.04_py3.9_pytorch_staging
 VLLM_REV=799388d722e22ecb14d1011faaba54c4882cc8f5 # MLPerf-4.1
 HIPBLASLT_BRANCH=8b71e7a8d26ba95774fdc372883ee0be57af3d28
 FA_BRANCH=23a2b1c2f21de2289db83de7d42e125586368e66 # ck_tile - FA 2.5.9
+TRITON_BRANCH=e4a0d93ff1a367c7d4eeebbcd7079ed267e6b06f
 RELEASE_TAG=${RELEASE_TAG:-latest}
 
 git clone https://github.com/ROCm/vllm
@@ -11,9 +12,7 @@ git checkout main
 git pull
 git checkout ${VLLM_REV}
 git cherry-pick b9013696b23dde372cccecdbaf69f0c852008844 # optimizations for process output step, PR #104
-
-docker build --build-arg BASE_IMAGE=${BASE_IMAGE} --build-arg HIPBLASLT_BRANCH=${HIPBLASLT_BRANCH} --build-arg FA_BRANCH=${FA_BRANCH} -f Dockerfile.rocm -t vllm_dev:${VLLM_REV} .
-
 popd
 
-docker build --build-arg BASE_IMAGE=vllm_dev:${VLLM_REV} -f Dockerfile.llama2 -t mlperf/llama_inference:${RELEASE_TAG} ..
+docker build --build-arg BASE_IMAGE=${BASE_IMAGE} --build-arg HIPBLASLT_BRANCH=${HIPBLASLT_BRANCH} --build-arg FA_BRANCH=${FA_BRANCH} --build-arg TRITON_BRANCH=${TRITON_BRANCH} -f vllm/Dockerfile.rocm -t vllm_dev:${VLLM_REV} vllm \
+&& docker build --build-arg BASE_IMAGE=vllm_dev:${VLLM_REV} -f Dockerfile.llama2 -t mlperf/llama_inference:${RELEASE_TAG} ..