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run_and_time for resnet ci (#10405)
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2
.github/workflows/mlperf.yml
vendored
2
.github/workflows/mlperf.yml
vendored
@@ -18,4 +18,4 @@ jobs:
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ln -s /raid/datasets/imagenet extra/datasets/imagenet
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- name: Run resnet
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run: |
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examples/mlperf/training_submission_v5.0/tinycorp/benchmarks/resnet/implementations/tinybox_green/dev_beam.sh
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LOGMLPERF=0 examples/mlperf/training_submission_v5.0/tinycorp/benchmarks/resnet/implementations/tinybox_green/run_and_time.sh
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@@ -368,6 +368,9 @@ def train_retinanet():
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INITMLPERF = getenv("INITMLPERF")
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RUNMLPERF = getenv("RUNMLPERF")
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if INITMLPERF:
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diskcache_clear()
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if getenv("LOGMLPERF"):
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from mlperf_logging import mllog
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import mlperf_logging.mllog.constants as mllog_constants
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@@ -386,7 +389,6 @@ def train_retinanet():
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MLLOGGER.event(key=mllog_constants.SUBMISSION_BENCHMARK, value=mllog_constants.RETINANET)
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diskcache_clear()
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MLLOGGER.event(key=mllog_constants.CACHE_CLEAR, value=True)
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MLLOGGER.start(key=mllog_constants.INIT_START)
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@@ -10,7 +10,7 @@ export RESET_STEP=0
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export TRAIN_BEAM=4 IGNORE_JIT_FIRST_BEAM=1 BEAM_UOPS_MAX=1500 BEAM_UPCAST_MAX=64 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=10 BEAM_PADTO=0
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# pip install -e ".[mlperf]"
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export LOGMLPERF=1
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export LOGMLPERF=${LOGMLPERF:-1}
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export SEED=$RANDOM
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DATETIME=$(date "+%m%d%H%M")
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