@@ -264,18 +264,6 @@ elif [[ $TEST_CONFIG == 'nogpu_AVX512' ]]; then
264264 export ATEN_CPU_CAPABILITY=avx2
265265fi
266266
267- # temp workarounds for https://github.com/pytorch/pytorch/issues/126692, remove when fixed
268- if [[ " $BUILD_ENVIRONMENT " != * -bazel-* ]]; then
269- pushd test
270- CUDA_VERSION=$( python -c " import torch; print(torch.version.cuda)" )
271- if [ " $CUDA_VERSION " == " 12.4" ]; then
272- ISCUDA124=" cu124"
273- else
274- ISCUDA124=" "
275- fi
276- popd
277- fi
278-
279267test_python_legacy_jit () {
280268 time python test/run_test.py --include test_jit_legacy test_jit_fuser_legacy --verbose
281269 assert_git_not_dirty
@@ -393,7 +381,7 @@ test_inductor_cpp_wrapper_abi_compatible() {
393381 --output " $TEST_REPORTS_DIR /inductor_cpp_wrapper_training.csv"
394382 python benchmarks/dynamo/check_accuracy.py \
395383 --actual " $TEST_REPORTS_DIR /inductor_cpp_wrapper_training.csv" \
396- --expected " benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124} / inductor_timm_training.csv"
384+ --expected " benchmarks/dynamo/ci_expected_accuracy/inductor_timm_training.csv"
397385}
398386
399387# "Global" flags for inductor benchmarking controlled by TEST_CONFIG
@@ -555,10 +543,10 @@ test_single_dynamo_benchmark() {
555543 --output " $TEST_REPORTS_DIR /${name} _${suite} .csv"
556544 python benchmarks/dynamo/check_accuracy.py \
557545 --actual " $TEST_REPORTS_DIR /${name} _$suite .csv" \
558- --expected " benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124} / ${ TEST_CONFIG} _${name} .csv"
546+ --expected " benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG} _${name} .csv"
559547 python benchmarks/dynamo/check_graph_breaks.py \
560548 --actual " $TEST_REPORTS_DIR /${name} _$suite .csv" \
561- --expected " benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124} / ${ TEST_CONFIG} _${name} .csv"
549+ --expected " benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG} _${name} .csv"
562550 fi
563551}
564552
@@ -618,7 +606,7 @@ test_inductor_torchbench_smoketest_perf() {
618606 --bfloat16 --inference --inductor --only moco --output " $TEST_REPORTS_DIR /inductor_cpp_wrapper_inference.csv"
619607 python benchmarks/dynamo/check_accuracy.py \
620608 --actual " $TEST_REPORTS_DIR /inductor_cpp_wrapper_inference.csv" \
621- --expected " benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124} / inductor_torchbench_inference.csv"
609+ --expected " benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_inference.csv"
622610
623611 python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --float16 --training \
624612 --batch-size-file " $( realpath benchmarks/dynamo/torchbench_models_list.txt) " --only hf_Bert \
@@ -633,13 +621,7 @@ test_inductor_torchbench_smoketest_perf() {
633621 # https://github.com/pytorch/pytorch/actions/runs/7158691360/job/19491437314,
634622 # and thus we lower its threshold to reduce flakiness. If this continues to be a problem,
635623 # we switch to use some other model.
636- # Use 4.7 for cuda 12.4, change back to 4.9 after fixing https://github.com/pytorch/pytorch/issues/126692
637- if [ " $CUDA_VERSION " == " 12.4" ]; then
638- THRESHOLD=4.7
639- else
640- THRESHOLD=4.9
641- fi
642- python benchmarks/dynamo/check_perf_csv.py -f " $TEST_REPORTS_DIR /inductor_inference_smoketest.csv" -t $THRESHOLD
624+ python benchmarks/dynamo/check_perf_csv.py -f " $TEST_REPORTS_DIR /inductor_inference_smoketest.csv" -t 4.9
643625
644626 # Check memory compression ratio for a few models
645627 for test in hf_Albert timm_vision_transformer; do
@@ -658,7 +640,7 @@ test_inductor_torchbench_smoketest_perf() {
658640 --only $test --output " $TEST_REPORTS_DIR /inductor_warm_start_smoketest_$test .csv"
659641 python benchmarks/dynamo/check_accuracy.py \
660642 --actual " $TEST_REPORTS_DIR /inductor_warm_start_smoketest_$test .csv" \
661- --expected " benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124} / inductor_huggingface_training.csv"
643+ --expected " benchmarks/dynamo/ci_expected_accuracy/inductor_huggingface_training.csv"
662644 done
663645}
664646
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