Auto-merge updates from auto-update branch

Author: mlcommons-bot

open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/3d-unet-99.9/singlestream/README.md

@@ -19,7 +19,7 @@ pip install -U cmind
 
 cm rm cache -f
 
-cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd
+cm pull repo mlcommons@mlperf-automations --checkout=467517e4a572872046058e394a0d83512cfff38b
 
 cm run script \
 	--tags=app,mlperf,inference,generic,_nvidia,_3d-unet-99.9,_tensorrt,_cuda,_valid,_r4.1-dev_default,_singlestream \
@@ -126,4 +126,4 @@ Model Precision: int8
 `DICE`: `0.86236`, Required accuracy for closed division `>= 0.86084`
 
 ### Performance Results 
-`90th percentile latency (ns)`: `437330110.0`
+`90th percentile latency (ns)`: `437613279.0`

open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/3d-unet-99.9/singlestream/accuracy_console.out

@@ -1,8 +1,8 @@
-[2024-12-24 21:14:19,911 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1
-[2024-12-24 21:14:20,085 harness.py:249 INFO] The harness will load 3 plugins: ['build/plugins/pixelShuffle3DPlugin/libpixelshuffle3dplugin.so', 'build/plugins/conv3D1X1X1K4Plugin/libconv3D1X1X1K4Plugin.so', 'build/plugins/conv3D3X3X3C1K32Plugin/libconv3D3X3X3C1K32Plugin.so']
-[2024-12-24 21:14:20,086 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/3d-unet-99.9/SingleStream
-[2024-12-24 21:14:20,086 __init__.py:46 INFO] Running command: ./build/bin/harness_3dunet --plugins="build/plugins/pixelShuffle3DPlugin/libpixelshuffle3dplugin.so,build/plugins/conv3D1X1X1K4Plugin/libconv3D1X1X1K4Plugin.so,build/plugins/conv3D3X3X3C1K32Plugin/libconv3D3X3X3C1K32Plugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/3d-unet-99.9/singlestream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=43 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/kits19/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/c1d8c371d52d46a3/inference/mlperf.conf" --tensor_path="build/preprocessed_data/KiTS19/inference/int8" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ce680103d365484b88716a62f18175c8.conf" --unet3d_sw_gaussian_patch_path="/home/cmuser/CM/repos/local/cache/5b2b0cc913a4453a/preprocessed_data/KiTS19/etc/gaussian_patches.npy" --gpu_engines="./build/engines/RTX4090x1/3d-unet/SingleStream/3d-unet-SingleStream-gpu-b1-int8.custom_k_99_9_MaxP.plan" --max_dlas=0 --slice_overlap_patch_kernel_cg_impl=false --scenario SingleStream --model 3d-unet
-[2024-12-24 21:14:20,086 __init__.py:53 INFO] Overriding Environment
+[2024-12-27 19:48:10,290 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1
+[2024-12-27 19:48:10,462 harness.py:249 INFO] The harness will load 3 plugins: ['build/plugins/pixelShuffle3DPlugin/libpixelshuffle3dplugin.so', 'build/plugins/conv3D1X1X1K4Plugin/libconv3D1X1X1K4Plugin.so', 'build/plugins/conv3D3X3X3C1K32Plugin/libconv3D3X3X3C1K32Plugin.so']
+[2024-12-27 19:48:10,463 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/3d-unet-99.9/SingleStream
+[2024-12-27 19:48:10,463 __init__.py:46 INFO] Running command: ./build/bin/harness_3dunet --plugins="build/plugins/pixelShuffle3DPlugin/libpixelshuffle3dplugin.so,build/plugins/conv3D1X1X1K4Plugin/libconv3D1X1X1K4Plugin.so,build/plugins/conv3D3X3X3C1K32Plugin/libconv3D3X3X3C1K32Plugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/3d-unet-99.9/singlestream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=43 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/kits19/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/c1d8c371d52d46a3/inference/mlperf.conf" --tensor_path="build/preprocessed_data/KiTS19/inference/int8" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/e5e3ac975a6a48c49bfdc79eb904188d.conf" --unet3d_sw_gaussian_patch_path="/home/cmuser/CM/repos/local/cache/5b2b0cc913a4453a/preprocessed_data/KiTS19/etc/gaussian_patches.npy" --gpu_engines="./build/engines/RTX4090x1/3d-unet/SingleStream/3d-unet-SingleStream-gpu-b1-int8.custom_k_99_9_MaxP.plan" --max_dlas=0 --slice_overlap_patch_kernel_cg_impl=false --scenario SingleStream --model 3d-unet
+[2024-12-27 19:48:10,463 __init__.py:53 INFO] Overriding Environment
 benchmark : Benchmark.UNET3D
 buffer_manager_thread_count : 0
 data_dir : /home/cmuser/CM/repos/local/cache/5b2b0cc913a4453a/data
@@ -11,7 +11,7 @@ gpu_copy_streams : 1
 gpu_inference_streams : 1
 input_dtype : int8
 input_format : linear
-log_dir : /home/cmuser/CM/repos/local/cache/dfbf240f980947f5/repo/closed/NVIDIA/build/logs/2024.12.24-21.14.19
+log_dir : /home/cmuser/CM/repos/local/cache/dfbf240f980947f5/repo/closed/NVIDIA/build/logs/2024.12.27-19.48.09
 map_path : data_maps/kits19/val_map.txt
 mlperf_conf_path : /home/cmuser/CM/repos/local/cache/c1d8c371d52d46a3/inference/mlperf.conf
 precision : int8
@@ -25,7 +25,7 @@ test_mode : AccuracyOnly
 unet3d_sw_gaussian_patch_path : /home/cmuser/CM/repos/local/cache/5b2b0cc913a4453a/preprocessed_data/KiTS19/etc/gaussian_patches.npy
 use_deque_limit : True
 use_graphs : False
-user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ce680103d365484b88716a62f18175c8.conf
+user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/e5e3ac975a6a48c49bfdc79eb904188d.conf
 system_id : RTX4090x1
 config_name : RTX4090x1_3d-unet_SingleStream
 workload_setting : WorkloadSetting(HarnessType.Custom, AccuracyTarget.k_99_9, PowerSetting.MaxP)
@@ -39,7 +39,7 @@ power_limit : None
 cpu_freq : None
 &&&& RUNNING MLPerf_Inference_3DUNet_Harness # ./build/bin/harness_3dunet
 [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/c1d8c371d52d46a3/inference/mlperf.conf
-[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ce680103d365484b88716a62f18175c8.conf
+[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/e5e3ac975a6a48c49bfdc79eb904188d.conf
 Creating QSL.
 Finished Creating QSL.
 Setting up SUT.
@@ -55,7 +55,7 @@ Setting up SUT.
 [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: true
 Finished setting up SUT.
 Starting warmup. Running for a minimum of 5 seconds.
-Finished warmup. Ran for 5.05304s.
+Finished warmup. Ran for 5.0542s.
 Starting running actual test.
 
 No warnings encountered during test.
@@ -68,8 +68,8 @@ Device Device:0 processed:
   PerSampleCudaMemcpy Calls: 43
   BatchedCudaMemcpy Calls: 0
 &&&& PASSED MLPerf_Inference_3DUNet_Harness # ./build/bin/harness_3dunet
-[2024-12-24 21:14:36,037 run_harness.py:166 INFO] Result: Accuracy run detected.
-[2024-12-24 21:14:36,037 __init__.py:46 INFO] Running command: python3 code/3d-unet/tensorrt/accuracy_kits.py --log_file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/3d-unet-99.9/singlestream/accuracy/mlperf_log_accuracy.json
+[2024-12-27 19:48:26,406 run_harness.py:166 INFO] Result: Accuracy run detected.
+[2024-12-27 19:48:26,406 __init__.py:46 INFO] Running command: python3 code/3d-unet/tensorrt/accuracy_kits.py --log_file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/3d-unet-99.9/singlestream/accuracy/mlperf_log_accuracy.json
 Loading necessary metadata...
 Loading loadgen accuracy log...
 Running postprocessing...