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Results from self hosted Github actions - NVIDIARTX4090
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arjunsuresh committed Jan 15, 2025
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| Model | Scenario | Accuracy | Throughput | Latency (in ms) |
|---------------------|------------|------------|--------------|-------------------|
| stable-diffusion-xl | offline | () | 0.353 | - |
| Model | Scenario | Accuracy | Throughput | Latency (in ms) |
|---------|------------|------------|--------------|-------------------|
| gptj-99 | offline | 264 | 48.213 | - |
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Expand Up @@ -16,7 +16,7 @@ pip install -U cmind

cm rm cache -f

cm pull repo gateoverflow@mlperf-automations --checkout=f58e256d9ccc736a60769ffcaaa66a093b28da54
cm pull repo gateoverflow@mlperf-automations --checkout=2d0f337e2813814778fe386c2ade45506c154333

cm run script \
--tags=app,mlperf,inference,generic,_reference,_gptj-99,_pytorch,_cuda,_test,_r5.0-dev_default,_float16,_offline \
Expand Down Expand Up @@ -105,4 +105,4 @@ Model Precision: fp32
`GEN_LEN`: `264.0`, Required accuracy for closed division `>= 42.55663`

### Performance Results
`Samples per second`: `48.3065`
`Samples per second`: `48.2132`
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Expand Up @@ -2,17 +2,17 @@ Constructing QSL
Encoding Samples
Finished constructing QSL.
Loading PyTorch model...
Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s]Loading checkpoint shards: 33%|███▎ | 1/3 [00:00<00:01, 1.33it/s]Loading checkpoint shards: 67%|██████▋ | 2/3 [00:01<00:00, 1.50it/s]Loading checkpoint shards: 100%|██████████| 3/3 [00:01<00:00, 2.01it/s]Loading checkpoint shards: 100%|██████████| 3/3 [00:01<00:00, 1.81it/s]
Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s]Loading checkpoint shards: 33%|███▎ | 1/3 [00:00<00:01, 1.59it/s]Loading checkpoint shards: 67%|██████▋ | 2/3 [00:01<00:00, 1.68it/s]Loading checkpoint shards: 100%|██████████| 3/3 [00:01<00:00, 2.16it/s]Loading checkpoint shards: 100%|██████████| 3/3 [00:01<00:00, 1.99it/s]
Some weights of the model checkpoint at /home/cmuser/CM/repos/local/cache/31767c21a8f149e5/checkpoint/checkpoint-final were not used when initializing GPTJForCausalLM: ['transformer.h.0.attn.bias', 'transformer.h.0.attn.masked_bias', 'transformer.h.1.attn.bias', 'transformer.h.1.attn.masked_bias', 'transformer.h.10.attn.bias', 'transformer.h.10.attn.masked_bias', 'transformer.h.11.attn.bias', 'transformer.h.11.attn.masked_bias', 'transformer.h.12.attn.bias', 'transformer.h.12.attn.masked_bias', 'transformer.h.13.attn.bias', 'transformer.h.13.attn.masked_bias', 'transformer.h.14.attn.bias', 'transformer.h.14.attn.masked_bias', 'transformer.h.15.attn.bias', 'transformer.h.15.attn.masked_bias', 'transformer.h.16.attn.bias', 'transformer.h.16.attn.masked_bias', 'transformer.h.17.attn.bias', 'transformer.h.17.attn.masked_bias', 'transformer.h.18.attn.bias', 'transformer.h.18.attn.masked_bias', 'transformer.h.19.attn.bias', 'transformer.h.19.attn.masked_bias', 'transformer.h.2.attn.bias', 'transformer.h.2.attn.masked_bias', 'transformer.h.20.attn.bias', 'transformer.h.20.attn.masked_bias', 'transformer.h.21.attn.bias', 'transformer.h.21.attn.masked_bias', 'transformer.h.22.attn.bias', 'transformer.h.22.attn.masked_bias', 'transformer.h.23.attn.bias', 'transformer.h.23.attn.masked_bias', 'transformer.h.24.attn.bias', 'transformer.h.24.attn.masked_bias', 'transformer.h.25.attn.bias', 'transformer.h.25.attn.masked_bias', 'transformer.h.26.attn.bias', 'transformer.h.26.attn.masked_bias', 'transformer.h.27.attn.bias', 'transformer.h.27.attn.masked_bias', 'transformer.h.3.attn.bias', 'transformer.h.3.attn.masked_bias', 'transformer.h.4.attn.bias', 'transformer.h.4.attn.masked_bias', 'transformer.h.5.attn.bias', 'transformer.h.5.attn.masked_bias', 'transformer.h.6.attn.bias', 'transformer.h.6.attn.masked_bias', 'transformer.h.7.attn.bias', 'transformer.h.7.attn.masked_bias', 'transformer.h.8.attn.bias', 'transformer.h.8.attn.masked_bias', 'transformer.h.9.attn.bias', 'transformer.h.9.attn.masked_bias']
- This IS expected if you are initializing GPTJForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing GPTJForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Casting models to GPU...
0%| | 0/285 [00:00<?, ?it/s]100%|██████████| 285/285 [00:00<00:00, 2029501.94it/s]
0%| | 0/285 [00:00<?, ?it/s]100%|██████████| 285/285 [00:00<00:00, 1891418.73it/s]
Running LoadGen test...
Number of Samples in query_samples : 1
0%| | 0/1 [00:00<?, ?it/s]/home/cmuser/venv/cm/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:676: UserWarning: `num_beams` is set to 1. However, `early_stopping` is set to `True` -- this flag is only used in beam-based generation modes. You should set `num_beams>1` or unset `early_stopping`.
warnings.warn(
100%|██████████| 1/1 [00:01<00:00, 1.21s/it]100%|██████████| 1/1 [00:01<00:00, 1.22s/it]
100%|██████████| 1/1 [00:01<00:00, 1.23s/it]100%|██████████| 1/1 [00:01<00:00, 1.23s/it]

No warnings encountered during test.

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Expand Up @@ -31,22 +31,22 @@ graph TD
get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,generic-python-lib,_pip
get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy
app-mlperf-inference,d775cac873ee4231_(_reference,_gptj-99,_pytorch,_cuda,_test,_r5.0-dev_default,_float16,_offline_) --> get,cuda-devices,_with-pycuda
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> detect,os
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> detect,os
detect-cpu,586c8a43320142f7 --> detect,os
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> detect,cpu
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,sys-utils-cm
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,python
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,cuda,_cudnn
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> detect,cpu
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,sys-utils-cm
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,python
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,cuda,_cudnn
get-generic-python-lib,94b62a682bc44791_(_torch_cuda_) --> get,python3
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,generic-python-lib,_torch_cuda
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,generic-python-lib,_torch_cuda
get-generic-python-lib,94b62a682bc44791_(_torchvision_cuda_) --> get,python3
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,generic-python-lib,_torchvision_cuda
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,generic-python-lib,_torchvision_cuda
get-generic-python-lib,94b62a682bc44791_(_transformers_) --> get,python3
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,generic-python-lib,_transformers
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,generic-python-lib,_transformers
download-and-extract,c67e81a4ce2649f5_(_rclone,_url.mlc-inference:mlcommons-inference-wg-public/gpt-j_) --> download,file,_rclone,_url.mlc-inference:mlcommons-inference-wg-public/gpt-j
get-ml-model-gptj,a41166210f294fbf_(_pytorch_) --> download-and-extract,_rclone,_url.mlc-inference:mlcommons-inference-wg-public/gpt-j
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,ml-model,large-language-model,gptj,raw,_pytorch
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,dataset,cnndm,_validation
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,ml-model,large-language-model,gptj,raw,_pytorch
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,dataset,cnndm,_validation
generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os
detect-cpu,586c8a43320142f7 --> detect,os
generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu
Expand All @@ -57,22 +57,22 @@ graph TD
generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src
get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs
generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> generate,user-conf,mlperf,inference
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,loadgen
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> generate,user-conf,mlperf,inference
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,loadgen
get-mlperf-inference-src,4b57186581024797 --> detect,os
get-mlperf-inference-src,4b57186581024797 --> get,python3
get-mlperf-inference-src,4b57186581024797 --> get,git,repo,_branch.master,_repo.https://github.com/mlcommons/inference
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,mlcommons,inference,src
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,mlcommons,inference,src
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,mlcommons,inference,src
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,mlcommons,inference,src
get-generic-python-lib,94b62a682bc44791_(_package.psutil_) --> get,python3
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,generic-python-lib,_package.psutil
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,generic-python-lib,_package.psutil
get-generic-python-lib,94b62a682bc44791_(_package.datasets_) --> get,python3
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,generic-python-lib,_package.datasets
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,generic-python-lib,_package.datasets
get-generic-python-lib,94b62a682bc44791_(_package.attrs_) --> get,python3
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,generic-python-lib,_package.attrs
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,generic-python-lib,_package.attrs
get-generic-python-lib,94b62a682bc44791_(_package.accelerate_) --> get,python3
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> get,generic-python-lib,_package.accelerate
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> get,generic-python-lib,_package.accelerate
detect-cpu,586c8a43320142f7 --> detect,os
benchmark-program,19f369ef47084895 --> detect,cpu
benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_pytorch,_offline,_cuda,_gptj-99,_float16_) --> benchmark-mlperf
app-mlperf-inference-mlcommons-python,ff149e9781fc4b65_(_cuda,_pytorch,_gptj-99,_offline,_float16_) --> benchmark-mlperf
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