From f75d9f93bb14ed56058f4c70ae4670b6cf3a8ed1 Mon Sep 17 00:00:00 2001 From: Ilyas Moutawwakil <57442720+IlyasMoutawwakil@users.noreply.github.com> Date: Thu, 30 Nov 2023 05:26:04 +0100 Subject: [PATCH] Update llama examples (#90) --- .gitignore | 4 +- examples/running-llamas/README.md | 49 ++- .../A100-80GB/forward_latency_plot.png | Bin 39612 -> 0 bytes .../A100-80GB/forward_memory_plot.png | Bin 37099 -> 0 bytes .../artifacts/A100-80GB/full_report.csv | 11 - .../A100-80GB/generate_memory_plot.png | Bin 41656 -> 0 bytes .../A100-80GB/generate_throughput_plot.png | Bin 37626 -> 0 bytes .../artifacts/A100-80GB/rich_table.svg | 163 ------- .../artifacts/A100-80GB/short_report.csv | 11 - .../Llama-13b/decode_throughput_bar_plot.png | Bin 0 -> 41316 bytes .../Llama-13b/decode_throughput_line_plot.png | Bin 0 -> 64674 bytes .../artifacts/Llama-13b/full_report.csv | 31 ++ ...generate_max_memory_allocated_bar_plot.png | Bin 0 -> 44083 bytes ...enerate_max_memory_allocated_line_plot.png | Bin 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examples/running-llamas/configs/fp16+bt.yaml | 9 + .../running-llamas/configs/fp16+dp=2.yaml | 15 + .../running-llamas/configs/fp16+fa2+tp=2.yaml | 22 + examples/running-llamas/configs/fp16+fa2.yaml | 9 + .../configs/fp16+gptq+exllamav1+dp=2.yaml | 27 ++ .../configs/fp16+gptq+exllamav1.yaml | 20 + .../configs/fp16+gptq+exllamav2+dp=2.yaml | 27 ++ .../configs/fp16+gptq+exllamav2.yaml | 20 + .../running-llamas/configs/fp16+tp=2.yaml | 21 + examples/running-llamas/configs/fp16.yaml | 6 + examples/running-llamas/configs/gptq.yaml | 6 - .../0/.hydra/config.yaml | 73 ---- .../0/.hydra/hydra.yaml | 174 -------- .../0/.hydra/overrides.yaml | 1 - .../0/hydra_config.yaml | 79 ---- .../0/inference_results.csv | 2 - .../4/.hydra/config.yaml | 73 ---- .../4/.hydra/hydra.yaml | 174 -------- .../4/.hydra/overrides.yaml | 1 - .../4/hydra_config.yaml | 79 ---- .../4/inference_results.csv | 2 - .../1/.hydra/config.yaml | 73 ---- .../1/.hydra/hydra.yaml | 174 -------- .../1/.hydra/overrides.yaml | 1 - .../1/hydra_config.yaml | 79 ---- .../1/inference_results.csv | 2 - .../multirun.yaml | 246 ----------- .../2/.hydra/config.yaml | 73 ---- .../2/.hydra/hydra.yaml | 174 -------- .../2/.hydra/overrides.yaml | 1 - .../2/hydra_config.yaml | 79 ---- .../2/inference_results.csv | 2 - .../3/.hydra/config.yaml | 73 ---- .../3/.hydra/hydra.yaml | 174 -------- .../3/.hydra/overrides.yaml | 1 - .../3/hydra_config.yaml | 79 ---- .../3/inference_results.csv | 2 - .../0/.hydra/config.yaml | 73 ---- .../0/.hydra/hydra.yaml | 174 -------- .../0/.hydra/overrides.yaml | 1 - .../0/hydra_config.yaml | 79 ---- .../0/inference_results.csv | 2 - .../4/.hydra/config.yaml | 73 ---- .../4/.hydra/hydra.yaml | 174 -------- .../4/.hydra/overrides.yaml | 1 - .../4/hydra_config.yaml | 79 ---- .../4/inference_results.csv | 2 - .../1/.hydra/config.yaml | 73 ---- .../1/.hydra/hydra.yaml | 174 -------- .../1/.hydra/overrides.yaml | 1 - .../1/hydra_config.yaml | 79 ---- .../1/inference_results.csv | 2 - .../multirun.yaml | 246 ----------- .../2/.hydra/config.yaml | 73 ---- .../2/.hydra/hydra.yaml | 174 -------- .../2/.hydra/overrides.yaml | 1 - .../2/hydra_config.yaml | 79 ---- .../2/inference_results.csv | 2 - .../3/.hydra/config.yaml | 73 ---- .../3/.hydra/hydra.yaml | 174 -------- .../3/.hydra/overrides.yaml | 1 - .../3/hydra_config.yaml | 79 ---- .../3/inference_results.csv | 2 - examples/running-llamas/report.py | 405 +++++++++--------- optimum_benchmark/backends/isolation_utils.py | 83 ++-- optimum_benchmark/backends/pytorch/backend.py | 25 +- optimum_benchmark/backends/pytorch/config.py | 4 +- .../benchmarks/inference/benchmark.py | 36 +- optimum_benchmark/experiment.py | 11 +- .../launchers/inline/__init__.py | 0 optimum_benchmark/launchers/inline/config.py | 12 + .../launchers/inline/launcher.py | 20 + .../launchers/process/launcher.py | 8 +- optimum_benchmark/trackers/memory.py | 8 +- 119 files changed, 744 insertions(+), 4298 deletions(-) delete mode 100644 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100644 examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/hydra_config.yaml delete mode 100644 examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/inference_results.csv create mode 100644 optimum_benchmark/launchers/inline/__init__.py create mode 100644 optimum_benchmark/launchers/inline/config.py create mode 100644 optimum_benchmark/launchers/inline/launcher.py diff --git a/.gitignore b/.gitignore index a589733f..30063812 100644 --- a/.gitignore +++ b/.gitignore @@ -168,6 +168,4 @@ data/ version.txt actions-runner/ -experiments/ -examples/ -results/ \ No newline at end of file +experiments/ \ No newline at end of file diff --git a/examples/running-llamas/README.md b/examples/running-llamas/README.md index dca82a4e..f4c9036c 100644 --- a/examples/running-llamas/README.md +++ b/examples/running-llamas/README.md @@ -1,61 +1,66 @@ -# Optimum-Benchmark x LLaMAs x GPTQ +# Optimum-Benchmark x LLaMA A set of benchmarks on Meta's LLaMA2's inference. ## Setup -You will need to install these quantization packages: +You will need to install any necessary third-party libraries like `deepspeed` or `auto-gptq` depending on the hardware and benchmarks you want to run. -```bash -pip install auto-gptq # or install it from source -``` +For example running FlashAttentionV2 on two devices with Tensor Parallelism (i.e. `fp16+fa2+tp=2`) will require: `deepspeed` and `flash-attn` ## Running -Then run these commands from this directory: +Then run the benchmarks from this directory with: ```bash -optimum-benchmark --config-dir configs/ --config-name _base_ --multirun -optimum-benchmark --config-dir configs/ --config-name gptq --multirun +optimum-benchmark --config-dir configs/ --config-name fp16 --multirun +optimum-benchmark --config-dir configs/ --config-name fp16+fa2+tp=2 --multirun +[...] ``` -This will create a folder called `experiments` with the results of the benchmarks with an inference `batch_size` ranging from 1 to 16 and an input `sequence_length` (prompt size) of 256. +This will create a folder called `experiments` with the results of the benchmarks with an inference `batch_size` ranging from 1 to 128 and an input `sequence_length` (prompt size) of 256. ## Reporting -To create a report run: +To create a report for 7B models on A100-80GB, run: ```bash -python report.py -e experiments -m allocated +python report.py -e experiments/hf-dgx-01/NousResearch/Llama-2-7b-hf/ experiments/hf-dgx-01/TheBloke/LLaMa-7B-GPTQ/ -r artifacts/Llama-7b/ +python report.py -e experiments/hf-dgx-01/NousResearch/Llama-2-13b-hf/ experiments/hf-dgx-01/TheBloke/LLaMa-13B-GPTQ/ -r artifacts/Llama-13b/ +python report.py -e experiments/hf-dgx-01/NousResearch/Llama-2-65b-hf/ experiments/hf-dgx-01/TheBloke/LLaMa-65B-GPTQ/ -r artifacts/Llama-65b/ ``` -Which will create some quick reporting artifacts like a `full_report.csv`, `short_report.csv`, some plots and a `rich_table.svg`. - -`-e` is the experiments folder from which to read the results. -`-r` is the report folder to which to write the resulting artifacts. -`-m` is the memory type to use for the reporting. It can be `used`, `allocated` or `reserved`. +Which will create some quick reporting artifacts like a `full_report.csv`, `short_report.csv`, and some interesting analysis plots. ## Results -### On A100-80GB +### LLaMA-7B on A100-80GB

-latency_plot +throughput_plot

-throughput_plot +latency_plot

+### LLaMA-13B on A100-80GB +

-memory_plot +throughput_plot

-memory_plot +latency_plot

+### LLaMA-65B on A100-80GB +

-rich_table +throughput_plot

+ +

+latency_plot +

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- - - - - - - - - - - - - - - - - - - - - - - - Inference Report - - - - - - - - - - ┏━━━━━━━━━━┳━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┓ -┃┃┃┃┃┃ Forward┃ Forward┃ Forward┃┃Generate┃Genera…┃Generate┃┃┃ -┃┃┃┃┃┃     Max┃     Max┃     Max┃┃     Max┃    Max┃     Max┃┃┃ -┃┃┃┃ Forward┃ Forward┃  Memory┃  Memory┃  Memory┃Generate┃  Memory┃ Memory┃  Memory┃┃┃ -┃Experim…┃┃   Batch┃ Latency┃Through…┃    Used┃Allocat…┃Reserved┃Through…┃    Used┃Alloca…┃Reserved┃Quanti…┃┃ -┃Name    ┃ GPU┃    Size┃     (s)┃(sample…┃    (MB)┃    (MB)┃    (MB)┃(tokens…┃    (MB)┃   (MB)┃    (MB)┃ Scheme┃   Group┃ -┡━━━━━━━━━━╇━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━┩ -│fp16-ba…│A100│      16│4.02e-01│   39.80│   19165│   16520│   17779│  471.00│   27988│  26442│   84511│   fp16│A100-fp…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│fp16-ba…│A100│       8│2.04e-01│   39.20│   17087│   15037│   15701│  290.00│   64889│  19997│   63503│   fp16│A100-fp…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│gptq-ba…│A100│      16│4.15e-01│   38.60│   10900│    7080│    8604│  333.00│   65676│  17002│   83596│   GPTQ│A100-GP…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│fp16-ba…│A100│       4│1.07e-01│   37.40│   16022│   14295│   14636│  147.00│   26346│  16774│   24960│   fp16│A100-fp…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│gptq-ba…│A100│       8│2.23e-01│   35.90│    8826│    5597│    6530│  206.00│   56629│  10557│   54333│   GPTQ│A100-GP…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│fp16-ba…│A100│       2│5.79e-02│   34.50│   15392│   13924│   14006│   75.30│   17003│  15162│   15617│   fp16│A100-fp…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│gptq-ba…│A100│       4│1.22e-01│   32.80│    7761│    4855│    5465│  134.00│   18085│   7335│   15789│   GPTQ│A100-GP…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│fp16-ba…│A100│       1│3.28e-02│   30.50│   15153│   13738│   13767│   37.90│   15866│  14356│   14480│   fp16│A100-fp…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│gptq-ba…│A100│       2│7.06e-02│   28.30│    6872│    4484│    4575│   66.50│    8822│   5722│    6526│   GPTQ│A100-GP…│ -├──────────┼──────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────┼──────────┼─────────┼──────────┤ -│gptq-ba…│A100│       1│4.58e-02│   21.80│    6746│    4298│    4450│   34.60│    7606│   4916│    5309│   GPTQ│A100-GP…│ -└──────────┴──────┴──────────┴──────────┴──────────┴──────────┴──────────┴──────────┴──────────┴──────────┴─────────┴──────────┴─────────┴──────────┘ - - - - diff --git a/examples/running-llamas/artifacts/A100-80GB/short_report.csv b/examples/running-llamas/artifacts/A100-80GB/short_report.csv deleted file mode 100644 index 6d6dba2d..00000000 --- a/examples/running-llamas/artifacts/A100-80GB/short_report.csv +++ /dev/null @@ -1,11 +0,0 @@ -experiment_name,GPU,Batch Size,Forward Latency (s),Forward Throughput (samples/s),Forward Max Memory Used (MB),Forward Max Memory Allocated (MB),Forward Max Memory Reserved (MB),Generate Throughput (tokens/s),Generate Max Memory Used (MB),Generate Max Memory Allocated (MB),Generate Max Memory Reserved (MB),Quantization Scheme,Group -fp16-batch_size(16)-sequence_length(256)-new_tokens(512),A100,16,0.402,39.8,19165,16520,17779,471.0,27988,26442,84511,fp16,A100-fp16 -fp16-batch_size(8)-sequence_length(256)-new_tokens(512),A100,8,0.204,39.2,17087,15037,15701,290.0,64889,19997,63503,fp16,A100-fp16 -gptq-batch_size(16)-sequence_length(256)-new_tokens(512),A100,16,0.415,38.6,10900,7080,8604,333.0,65676,17002,83596,GPTQ,A100-GPTQ -fp16-batch_size(4)-sequence_length(256)-new_tokens(512),A100,4,0.107,37.4,16022,14295,14636,147.0,26346,16774,24960,fp16,A100-fp16 -gptq-batch_size(8)-sequence_length(256)-new_tokens(512),A100,8,0.223,35.9,8826,5597,6530,206.0,56629,10557,54333,GPTQ,A100-GPTQ -fp16-batch_size(2)-sequence_length(256)-new_tokens(512),A100,2,0.0579,34.5,15392,13924,14006,75.3,17003,15162,15617,fp16,A100-fp16 -gptq-batch_size(4)-sequence_length(256)-new_tokens(512),A100,4,0.122,32.8,7761,4855,5465,134.0,18085,7335,15789,GPTQ,A100-GPTQ -fp16-batch_size(1)-sequence_length(256)-new_tokens(512),A100,1,0.0328,30.5,15153,13738,13767,37.9,15866,14356,14480,fp16,A100-fp16 -gptq-batch_size(2)-sequence_length(256)-new_tokens(512),A100,2,0.0706,28.3,6872,4484,4575,66.5,8822,5722,6526,GPTQ,A100-GPTQ -gptq-batch_size(1)-sequence_length(256)-new_tokens(512),A100,1,0.0458,21.8,6746,4298,4450,34.6,7606,4916,5309,GPTQ,A100-GPTQ diff --git a/examples/running-llamas/artifacts/Llama-13b/decode_throughput_bar_plot.png b/examples/running-llamas/artifacts/Llama-13b/decode_throughput_bar_plot.png new file mode 100644 index 0000000000000000000000000000000000000000..9c8f6b344efd8196f596348fb3f7c631215b9005 GIT binary patch literal 41316 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a/examples/running-llamas/artifacts/Llama-7b/short_report.csv b/examples/running-llamas/artifacts/Llama-7b/short_report.csv new file mode 100644 index 00000000..bda8c65e --- /dev/null +++ b/examples/running-llamas/artifacts/Llama-7b/short_report.csv @@ -0,0 +1,36 @@ +,Model,GPUs,Experiment Name,Per Process Batch Size,Sequence Length,Decode Latency (s),Prefill Latency (s),Decode Throughput (tokens/s),Prefill Throughput (samples/s),Generate Max Memory Allocated (MB),Generate Max Memory Reserved (MB),GPU Name,Num GPUs,Effective Batch Size,Group +0,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16,1,256,13.2,0.0336,38.7,29.8,14356,14480,1xA100,1,1,1xA100-fp16 +1,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16,4,256,13.7,0.109,149.0,36.7,16774,24960,1xA100,1,4,1xA100-fp16 +2,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16,32,256,26.4,0.826,619.0,38.7,39331,84422,1xA100,1,32,1xA100-fp16 +3,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16,64,256,44.2,1.65,740.0,38.8,65112,84420,1xA100,1,64,1xA100-fp16 +4,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16,8,256,13.9,0.21,294.0,38.1,19997,63503,1xA100,1,8,1xA100-fp16 +5,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16,16,256,17.1,0.412,478.0,38.8,26442,84420,1xA100,1,16,1xA100-fp16 +6,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16,2,256,13.4,0.059,76.3,33.9,15162,15617,1xA100,1,2,1xA100-fp16 +7,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16+bt,1,256,12.2,0.0318,41.9,31.4,14356,14480,1xA100,1,1,1xA100-fp16+bt +8,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16+bt,4,256,13.0,0.104,157.0,38.5,16774,24983,1xA100,1,4,1xA100-fp16+bt +9,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16+bt,32,256,26.5,0.804,617.0,39.8,39331,84408,1xA100,1,32,1xA100-fp16+bt +10,NousResearch/Llama-2-7b-hf,['NVIDIA A100-SXM4-80GB'],fp16+bt,64,256,45.1,1.65,725.0,38.8,65111,84420,1xA100,1,64,1xA100-fp16+bt 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A100-SXM4-80GB'],fp16+gptq+exllamav1,64,256,49.8,1.32,657.0,48.5,55638,84418,1xA100,1,64,1xA100-fp16+gptq+exllamav1 +32,TheBloke/LLaMa-7B-GPTQ,['NVIDIA A100-SXM4-80GB'],fp16+gptq+exllamav1,8,256,19.4,0.191,211.0,41.9,10524,54299,1xA100,1,8,1xA100-fp16+gptq+exllamav1 +33,TheBloke/LLaMa-7B-GPTQ,['NVIDIA A100-SXM4-80GB'],fp16+gptq+exllamav1,16,256,24.2,0.356,338.0,44.9,16969,84406,1xA100,1,16,1xA100-fp16+gptq+exllamav1 +34,TheBloke/LLaMa-7B-GPTQ,['NVIDIA A100-SXM4-80GB'],fp16+gptq+exllamav1,2,256,14.7,0.0621,69.5,32.2,5688,6492,1xA100,1,2,1xA100-fp16+gptq+exllamav1 diff --git a/examples/running-llamas/configs/_base_.yaml b/examples/running-llamas/configs/_base_.yaml index 23a3eaa4..552eb57b 100644 --- a/examples/running-llamas/configs/_base_.yaml +++ b/examples/running-llamas/configs/_base_.yaml @@ -1,38 +1,41 @@ defaults: - backend: pytorch # default backend + - launcher: inline # default launcher - benchmark: inference # default benchmark - experiment # inheriting from experiment config - _self_ # for hydra 1.1 compatibility - override hydra/job_logging: colorlog # colorful logging - override hydra/hydra_logging: colorlog # colorful logging -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - job: - chdir: true - env_set: - CUDA_VISIBLE_DEVICES: 0 - CUDA_DEVICE_ORDER: PCI_BUS_ID - sweeper: - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - -experiment_name: fp16-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: meta-llama/Llama-2-7b-hf -device: cuda:0 +experiment_name: llama-experiment +model: llama-2-model +device: cuda backend: - initial_isolation_check: false - continous_isolation_check: false + no_weights: true torch_dtype: float16 + continuous_isolation: true benchmark: memory: true warmup_runs: 10 - new_tokens: 512 input_shapes: + batch_size: 1 sequence_length: 256 + +hydra: + run: + dir: experiments/${oc.env:HOSTNAME}/${model}/${experiment_name} + sweep: + dir: experiments/${oc.env:HOSTNAME}/${model}/${experiment_name} + subdir: ${benchmark.input_shapes.batch_size} + job: + chdir: true + env_set: + CUDA_VISIBLE_DEVICES: 0 + CUDA_DEVICE_ORDER: PCI_BUS_ID + sweeper: + params: + benchmark.input_shapes.batch_size: 1,2,4,8,16,32,64,128 + model: NousResearch/Llama-2-7b-hf,NousResearch/Llama-2-13b-hf diff --git a/examples/running-llamas/configs/bnb.yaml b/examples/running-llamas/configs/bnb.yaml deleted file mode 100644 index 61cf1ebd..00000000 --- a/examples/running-llamas/configs/bnb.yaml +++ /dev/null @@ -1,11 +0,0 @@ -defaults: - - _base_ - - _self_ - -experiment_name: bnb-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) - -backend: - quantization_scheme: bnb - quantization_config: - load_in_4bit: true - bnb_4bit_compute_dtype: float16 diff --git a/examples/running-llamas/configs/fp16+bt+tp=2.yaml b/examples/running-llamas/configs/fp16+bt+tp=2.yaml new file mode 100644 index 00000000..efaddd22 --- /dev/null +++ b/examples/running-llamas/configs/fp16+bt+tp=2.yaml @@ -0,0 +1,22 @@ +defaults: + - _base_ + - _self_ + - override launcher: torchrun + +experiment_name: fp16+bt+tp=2 + +launcher: + nproc_per_node: 2 + rdzv_endpoint: localhost:29500 + +backend: + to_bettertransformer: true + deepspeed_inference: true + deepspeed_inference_config: + tensor_parallel: + tp_size: 2 + +hydra: + job: + env_set: + CUDA_VISIBLE_DEVICES: 0,1 diff --git a/examples/running-llamas/configs/fp16+bt.yaml b/examples/running-llamas/configs/fp16+bt.yaml new file mode 100644 index 00000000..bee86deb --- /dev/null +++ b/examples/running-llamas/configs/fp16+bt.yaml @@ -0,0 +1,9 @@ +defaults: + - _base_ + - _self_ + - override launcher: process + +experiment_name: fp16+bt + +backend: + to_bettertransformer: true diff --git a/examples/running-llamas/configs/fp16+dp=2.yaml b/examples/running-llamas/configs/fp16+dp=2.yaml new file mode 100644 index 00000000..80adde9d --- /dev/null +++ b/examples/running-llamas/configs/fp16+dp=2.yaml @@ -0,0 +1,15 @@ +defaults: + - _base_ + - _self_ + - override launcher: torchrun + +experiment_name: fp16+dp=2 + +launcher: + nproc_per_node: 2 + rdzv_endpoint: localhost:29511 + +hydra: + job: + env_set: + CUDA_VISIBLE_DEVICES: 0,1 diff --git a/examples/running-llamas/configs/fp16+fa2+tp=2.yaml b/examples/running-llamas/configs/fp16+fa2+tp=2.yaml new file mode 100644 index 00000000..a239e767 --- /dev/null +++ b/examples/running-llamas/configs/fp16+fa2+tp=2.yaml @@ -0,0 +1,22 @@ +defaults: + - _base_ + - _self_ + - override launcher: torchrun + +experiment_name: fp16+fa2+tp=2 + +launcher: + nproc_per_node: 2 + rdzv_endpoint: localhost:29544 + +backend: + use_flash_attention_2: true + deepspeed_inference: true + deepspeed_inference_config: + tensor_parallel: + tp_size: 2 + +hydra: + job: + env_set: + CUDA_VISIBLE_DEVICES: 0,1 diff --git a/examples/running-llamas/configs/fp16+fa2.yaml b/examples/running-llamas/configs/fp16+fa2.yaml new file mode 100644 index 00000000..b045ebd1 --- /dev/null +++ b/examples/running-llamas/configs/fp16+fa2.yaml @@ -0,0 +1,9 @@ +defaults: + - _base_ + - _self_ + - override launcher: process + +experiment_name: fp16+fa2 + +backend: + use_flash_attention_2: true diff --git a/examples/running-llamas/configs/fp16+gptq+exllamav1+dp=2.yaml b/examples/running-llamas/configs/fp16+gptq+exllamav1+dp=2.yaml new file mode 100644 index 00000000..f9a58bd4 --- /dev/null +++ b/examples/running-llamas/configs/fp16+gptq+exllamav1+dp=2.yaml @@ -0,0 +1,27 @@ +defaults: + - _base_ + - _self_ + - override launcher: torchrun + +experiment_name: fp16+gptq+exllamav1+dp=2 + +launcher: + nproc_per_node: 2 + rdzv_endpoint: localhost:29522 + +backend: + # for some reason core gets dumped + # with dummy weights + exllamav1 for 65B + no_weights: false + quantization_scheme: gptq + quantization_config: + exllama_config: + version: 1 + +hydra: + job: + env_set: + CUDA_VISIBLE_DEVICES: 0,1 + sweeper: + params: + model: TheBloke/LLaMa-7B-GPTQ,TheBloke/LLaMa-13B-GPTQ,TheBloke/LLaMa-65B-GPTQ diff --git a/examples/running-llamas/configs/fp16+gptq+exllamav1.yaml b/examples/running-llamas/configs/fp16+gptq+exllamav1.yaml new file mode 100644 index 00000000..c7555a8b --- /dev/null +++ b/examples/running-llamas/configs/fp16+gptq+exllamav1.yaml @@ -0,0 +1,20 @@ +defaults: + - _base_ + - _self_ + - override launcher: process + +experiment_name: fp16+gptq+exllamav1 + +backend: + # for some reason core gets dumped + # with 65B + exllamav1 + no_weights: false + quantization_scheme: gptq + quantization_config: + exllama_config: + version: 1 + +hydra: + sweeper: + params: + model: TheBloke/LLaMa-7B-GPTQ,TheBloke/LLaMa-13B-GPTQ,TheBloke/LLaMa-65B-GPTQ diff --git a/examples/running-llamas/configs/fp16+gptq+exllamav2+dp=2.yaml b/examples/running-llamas/configs/fp16+gptq+exllamav2+dp=2.yaml new file mode 100644 index 00000000..fdb85109 --- /dev/null +++ b/examples/running-llamas/configs/fp16+gptq+exllamav2+dp=2.yaml @@ -0,0 +1,27 @@ +defaults: + - _base_ + - _self_ + - override launcher: torchrun + +experiment_name: fp16+gptq+exllamav2+dp=2 + +launcher: + nproc_per_node: 2 + rdzv_endpoint: localhost:29533 + +backend: + # for some reason core gets dumped + # with dummy weights + exllamav2 + no_weights: false + quantization_scheme: gptq + quantization_config: + exllama_config: + version: 2 + +hydra: + job: + env_set: + CUDA_VISIBLE_DEVICES: 0,1 + sweeper: + params: + model: TheBloke/LLaMa-7B-GPTQ,TheBloke/LLaMa-13B-GPTQ,TheBloke/LLaMa-65B-GPTQ diff --git a/examples/running-llamas/configs/fp16+gptq+exllamav2.yaml b/examples/running-llamas/configs/fp16+gptq+exllamav2.yaml new file mode 100644 index 00000000..dd314d5d --- /dev/null +++ b/examples/running-llamas/configs/fp16+gptq+exllamav2.yaml @@ -0,0 +1,20 @@ +defaults: + - _base_ + - _self_ + - override launcher: process + +experiment_name: fp16+gptq+exllamav2 + +backend: + # for some reason core gets dumped + # with dummy weights + exllamav2 + no_weights: false + quantization_scheme: gptq + quantization_config: + exllama_config: + version: 2 + +hydra: + sweeper: + params: + model: TheBloke/LLaMa-7B-GPTQ,TheBloke/LLaMa-13B-GPTQ,TheBloke/LLaMa-65B-GPTQ diff --git a/examples/running-llamas/configs/fp16+tp=2.yaml b/examples/running-llamas/configs/fp16+tp=2.yaml new file mode 100644 index 00000000..712149df --- /dev/null +++ b/examples/running-llamas/configs/fp16+tp=2.yaml @@ -0,0 +1,21 @@ +defaults: + - _base_ + - _self_ + - override launcher: torchrun + +experiment_name: fp16+tp=2 + +launcher: + nproc_per_node: 2 + rdzv_endpoint: localhost:29544 + +backend: + deepspeed_inference: true + deepspeed_inference_config: + tensor_parallel: + tp_size: 2 + +hydra: + job: + env_set: + CUDA_VISIBLE_DEVICES: 0,1 diff --git a/examples/running-llamas/configs/fp16.yaml b/examples/running-llamas/configs/fp16.yaml new file mode 100644 index 00000000..432d986f --- /dev/null +++ b/examples/running-llamas/configs/fp16.yaml @@ -0,0 +1,6 @@ +defaults: + - _base_ + - _self_ + - override launcher: process + +experiment_name: fp16 diff --git a/examples/running-llamas/configs/gptq.yaml b/examples/running-llamas/configs/gptq.yaml deleted file mode 100644 index 3f15bdd5..00000000 --- a/examples/running-llamas/configs/gptq.yaml +++ /dev/null @@ -1,6 +0,0 @@ -defaults: - - _base_ - - _self_ - -experiment_name: gptq-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: TheBloke/Llama-2-7B-GPTQ diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/config.yaml deleted file mode 100644 index d2cd4143..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 1 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: fp16-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: meta-llama/Llama-2-7b-hf -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/hydra.yaml deleted file mode 100644 index 41af721d..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=1 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=1 - id: '0' - num: 0 - config_name: _base_ - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/overrides.yaml deleted file mode 100644 index 989520ff..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=1 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/hydra_config.yaml deleted file mode 100644 index 6d8478b5..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 1 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: fp16-batch_size(1)-sequence_length(256)-new_tokens(512) -model: meta-llama/Llama-2-7b-hf -device: cuda -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/inference_results.csv deleted file mode 100644 index 8161550f..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(1)-sequence_length(256)-new_tokens(512)/0/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.0328,30.5,15153,13738,13767,13.5,37.9,15866,14356,14480 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/config.yaml deleted file mode 100644 index 88fed34b..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 16 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: fp16-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: meta-llama/Llama-2-7b-hf -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/hydra.yaml deleted file mode 100644 index 1b047280..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=16 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=16 - id: '4' - num: 4 - config_name: _base_ - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/overrides.yaml deleted file mode 100644 index fdb7f01d..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=16 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/hydra_config.yaml deleted file mode 100644 index 64882a0b..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 16 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: fp16-batch_size(16)-sequence_length(256)-new_tokens(512) -model: meta-llama/Llama-2-7b-hf -device: cuda:0 -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/inference_results.csv deleted file mode 100644 index bad3d7ca..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(16)-sequence_length(256)-new_tokens(512)/4/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.402,39.8,19165,16520,17779,17.4,471.0,27988,26442,84511 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/config.yaml deleted file mode 100644 index f4197a4f..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 2 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: fp16-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: meta-llama/Llama-2-7b-hf -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/hydra.yaml deleted file mode 100644 index 7ef5862d..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=2 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=2 - id: '1' - num: 1 - config_name: _base_ - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/overrides.yaml deleted file mode 100644 index 8211b85f..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=2 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/hydra_config.yaml deleted file mode 100644 index 1de85dc8..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 2 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: fp16-batch_size(2)-sequence_length(256)-new_tokens(512) -model: meta-llama/Llama-2-7b-hf -device: cuda -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/inference_results.csv deleted file mode 100644 index 42a8985a..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/1/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.0579,34.5,15392,13924,14006,13.6,75.3,17003,15162,15617 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/multirun.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/multirun.yaml deleted file mode 100644 index 6de5aaf7..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(2)-sequence_length(256)-new_tokens(512)/multirun.yaml +++ /dev/null @@ -1,246 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: [] - job: - name: experiment - chdir: true - override_dirname: '' - id: ??? - num: ??? - config_name: _base_ - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: ??? - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 2 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: fp16-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: meta-llama/Llama-2-7b-hf -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/config.yaml deleted file mode 100644 index 589d9f13..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 4 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: fp16-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: meta-llama/Llama-2-7b-hf -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/hydra.yaml deleted file mode 100644 index 8e3abfc7..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=4 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=4 - id: '2' - num: 2 - config_name: _base_ - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/overrides.yaml deleted file mode 100644 index eef8c9ca..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=4 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/hydra_config.yaml deleted file mode 100644 index eb07905d..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 4 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: fp16-batch_size(4)-sequence_length(256)-new_tokens(512) -model: meta-llama/Llama-2-7b-hf -device: cuda -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/inference_results.csv deleted file mode 100644 index 3a40d093..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(4)-sequence_length(256)-new_tokens(512)/2/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.107,37.4,16022,14295,14636,13.9,147.0,26346,16774,24960 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/config.yaml deleted file mode 100644 index ff7402ca..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 8 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: fp16-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: meta-llama/Llama-2-7b-hf -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/hydra.yaml deleted file mode 100644 index ed654ac1..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=8 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=8 - id: '3' - num: 3 - config_name: _base_ - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/overrides.yaml deleted file mode 100644 index 8cd14374..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=8 diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/hydra_config.yaml deleted file mode 100644 index a180796d..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 8 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: fp16-batch_size(8)-sequence_length(256)-new_tokens(512) -model: meta-llama/Llama-2-7b-hf -device: cuda -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/inference_results.csv deleted file mode 100644 index 7fdc7a5f..00000000 --- a/examples/running-llamas/experiments/A100-80GB/fp16-batch_size(8)-sequence_length(256)-new_tokens(512)/3/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.204,39.2,17087,15037,15701,14.1,290.0,64889,19997,63503 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/config.yaml deleted file mode 100644 index 03090426..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 1 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: gptq-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/hydra.yaml deleted file mode 100644 index 65926c1f..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=1 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=1 - id: '0' - num: 0 - config_name: gptq - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/overrides.yaml deleted file mode 100644 index 989520ff..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=1 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/hydra_config.yaml deleted file mode 100644 index 256e0e54..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 1 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: gptq-batch_size(1)-sequence_length(256)-new_tokens(512) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/inference_results.csv deleted file mode 100644 index da04a0c3..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(1)-sequence_length(256)-new_tokens(512)/0/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.0458,21.8,6746,4298,4450,14.8,34.6,7606,4916,5309 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/config.yaml deleted file mode 100644 index 58457ece..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 16 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: gptq-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/hydra.yaml deleted file mode 100644 index c9e56066..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=16 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=16 - id: '4' - num: 4 - config_name: gptq - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/overrides.yaml deleted file mode 100644 index fdb7f01d..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=16 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/hydra_config.yaml deleted file mode 100644 index ad91270b..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 16 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: gptq-batch_size(16)-sequence_length(256)-new_tokens(512) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda:0 -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/inference_results.csv deleted file mode 100644 index 0b114e75..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(16)-sequence_length(256)-new_tokens(512)/4/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.415,38.6,10900,7080,8604,24.6,333.0,65676,17002,83596 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/config.yaml deleted file mode 100644 index 90ddbb6e..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 2 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: gptq-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/hydra.yaml deleted file mode 100644 index 77d220f4..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=2 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=2 - id: '1' - num: 1 - config_name: gptq - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/overrides.yaml deleted file mode 100644 index 8211b85f..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=2 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/hydra_config.yaml deleted file mode 100644 index d946b75c..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 2 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: gptq-batch_size(2)-sequence_length(256)-new_tokens(512) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/inference_results.csv deleted file mode 100644 index 1797a299..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/1/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.0706,28.3,6872,4484,4575,15.4,66.5,8822,5722,6526 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/multirun.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/multirun.yaml deleted file mode 100644 index 667d738e..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(2)-sequence_length(256)-new_tokens(512)/multirun.yaml +++ /dev/null @@ -1,246 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: [] - job: - name: experiment - chdir: true - override_dirname: '' - id: ??? - num: ??? - config_name: gptq - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: ??? - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 2 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: gptq-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/config.yaml deleted file mode 100644 index 97f81007..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 4 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: gptq-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/hydra.yaml deleted file mode 100644 index d5efb914..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=4 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=4 - id: '2' - num: 2 - config_name: gptq - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/overrides.yaml deleted file mode 100644 index eef8c9ca..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=4 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/hydra_config.yaml deleted file mode 100644 index eb2c9cbd..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 4 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: gptq-batch_size(4)-sequence_length(256)-new_tokens(512) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/inference_results.csv deleted file mode 100644 index e54a036c..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(4)-sequence_length(256)-new_tokens(512)/2/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.122,32.8,7761,4855,5465,15.3,134.0,18085,7335,15789 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/config.yaml deleted file mode 100644 index 3a4085f7..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/config.yaml +++ /dev/null @@ -1,73 +0,0 @@ -backend: - name: pytorch - version: ${pytorch_version:} - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: ${is_inference:${benchmark.name}} - eval_mode: ${is_inference:${benchmark.name}} - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 8 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: ${can_diffuse:${task}} - can_generate: ${can_generate:${task}} - forward_kwargs: {} - generate_kwargs: {} -experiment_name: gptq-batch_size(${benchmark.input_shapes.batch_size})-sequence_length(${benchmark.input_shapes.sequence_length})-new_tokens(${benchmark.new_tokens}) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda:0 -task: ${infer_task:${model}} -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/hydra.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/hydra.yaml deleted file mode 100644 index 5f8fa193..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/hydra.yaml +++ /dev/null @@ -1,174 +0,0 @@ -hydra: - run: - dir: experiments/${experiment_name} - sweep: - dir: experiments/${experiment_name} - subdir: ${hydra.job.num} - launcher: - _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher - sweeper: - _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper - max_batch_size: null - params: - benchmark.input_shapes.batch_size: 1,2,4,8,16 - help: - app_name: ${hydra.job.name} - header: '${hydra.help.app_name} is powered by Hydra. - - ' - footer: 'Powered by Hydra (https://hydra.cc) - - Use --hydra-help to view Hydra specific help - - ' - template: '${hydra.help.header} - - == Configuration groups == - - Compose your configuration from those groups (group=option) - - - $APP_CONFIG_GROUPS - - - == Config == - - Override anything in the config (foo.bar=value) - - - $CONFIG - - - ${hydra.help.footer} - - ' - hydra_help: - template: 'Hydra (${hydra.runtime.version}) - - See https://hydra.cc for more info. - - - == Flags == - - $FLAGS_HELP - - - == Configuration groups == - - Compose your configuration from those groups (For example, append hydra/job_logging=disabled - to command line) - - - $HYDRA_CONFIG_GROUPS - - - Use ''--cfg hydra'' to Show the Hydra config. - - ' - hydra_help: ??? - hydra_logging: - version: 1 - formatters: - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s' - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - root: - level: INFO - handlers: - - console - disable_existing_loggers: false - job_logging: - version: 1 - formatters: - simple: - format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' - colorlog: - (): colorlog.ColoredFormatter - format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s] - - %(message)s' - log_colors: - DEBUG: purple - INFO: green - WARNING: yellow - ERROR: red - CRITICAL: red - handlers: - console: - class: logging.StreamHandler - formatter: colorlog - stream: ext://sys.stdout - file: - class: logging.FileHandler - formatter: simple - filename: ${hydra.job.name}.log - root: - level: INFO - handlers: - - console - - file - disable_existing_loggers: false - env: {} - mode: MULTIRUN - searchpath: [] - callbacks: {} - output_subdir: .hydra - overrides: - hydra: - - hydra.mode=MULTIRUN - task: - - benchmark.input_shapes.batch_size=8 - job: - name: experiment - chdir: true - override_dirname: benchmark.input_shapes.batch_size=8 - id: '3' - num: 3 - config_name: gptq - env_set: - CUDA_VISIBLE_DEVICES: '3' - CUDA_DEVICE_ORDER: PCI_BUS_ID - env_copy: [] - config: - override_dirname: - kv_sep: '=' - item_sep: ',' - exclude_keys: [] - runtime: - version: 1.3.2 - version_base: '1.3' - cwd: /workspace/optimum-benchmark/examples/running-llamas - config_sources: - - path: hydra.conf - schema: pkg - provider: hydra - - path: optimum_benchmark - schema: pkg - provider: main - - path: hydra_plugins.hydra_colorlog.conf - schema: pkg - provider: hydra-colorlog - - path: /workspace/optimum-benchmark/examples/running-llamas/configs - schema: file - provider: command-line - - path: '' - schema: structured - provider: schema - output_dir: /workspace/optimum-benchmark/examples/running-llamas/experiments/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3 - choices: - benchmark: inference - backend: pytorch - hydra/env: default - hydra/callbacks: null - hydra/job_logging: colorlog - hydra/hydra_logging: colorlog - hydra/hydra_help: default - hydra/help: default - hydra/sweeper: basic - hydra/launcher: basic - hydra/output: default - verbose: false diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/overrides.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/overrides.yaml deleted file mode 100644 index 8cd14374..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/.hydra/overrides.yaml +++ /dev/null @@ -1 +0,0 @@ -- benchmark.input_shapes.batch_size=8 diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/hydra_config.yaml b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/hydra_config.yaml deleted file mode 100644 index 06e20479..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/hydra_config.yaml +++ /dev/null @@ -1,79 +0,0 @@ -backend: - name: pytorch - version: 2.1.0+cu118 - _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend - seed: 42 - inter_op_num_threads: null - intra_op_num_threads: null - initial_isolation_check: false - continous_isolation_check: false - delete_cache: false - no_weights: false - device_map: null - torch_dtype: float16 - disable_grad: true - eval_mode: true - amp_autocast: false - amp_dtype: null - torch_compile: false - torch_compile_config: {} - bettertransformer: false - quantization_scheme: null - quantization_config: {} - use_ddp: false - ddp_config: {} - peft_strategy: null - peft_config: {} -benchmark: - name: inference - _target_: optimum_benchmark.benchmarks.inference.benchmark.InferenceBenchmark - duration: 10 - warmup_runs: 10 - memory: true - energy: false - input_shapes: - batch_size: 8 - sequence_length: 256 - num_choices: 1 - feature_size: 80 - nb_max_frames: 3000 - audio_sequence_length: 16000 - new_tokens: 512 - can_diffuse: false - can_generate: true - forward_kwargs: {} - generate_kwargs: - max_new_tokens: 512 - min_new_tokens: 512 - do_sample: false - use_cache: true - pad_token_id: 0 - num_beams: 1 -experiment_name: gptq-batch_size(8)-sequence_length(256)-new_tokens(512) -model: TheBloke/Llama-2-7B-GPTQ -device: cuda -task: text-generation -hub_kwargs: - revision: main - cache_dir: null - force_download: false - local_files_only: false -environment: - optimum_version: 1.13.2 - optimum_commit: null - transformers_version: 4.34.1 - transformers_commit: null - accelerate_version: 0.24.1 - accelerate_commit: null - diffusers_version: null - diffusers_commit: null - python_version: 3.10.12 - system: Linux - cpu: ' AMD EPYC 7742 64-Core Processor' - cpu_count: 128 - cpu_ram_mb: 540684 - gpus: - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB - - NVIDIA A100-SXM4-80GB diff --git a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/inference_results.csv b/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/inference_results.csv deleted file mode 100644 index 5c52e357..00000000 --- a/examples/running-llamas/experiments/A100-80GB/gptq-batch_size(8)-sequence_length(256)-new_tokens(512)/3/inference_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -forward.latency(s),forward.throughput(samples/s),forward.max_memory_used(MB),forward.max_memory_allocated(MB),forward.max_memory_reserved(MB),generate.latency(s),generate.throughput(tokens/s),generate.max_memory_used(MB),generate.max_memory_allocated(MB),generate.max_memory_reserved(MB) -0.223,35.9,8826,5597,6530,19.9,206.0,56629,10557,54333 diff --git a/examples/running-llamas/report.py b/examples/running-llamas/report.py index eccd2d65..316f5bc1 100644 --- a/examples/running-llamas/report.py +++ b/examples/running-llamas/report.py @@ -1,30 +1,34 @@ from argparse import ArgumentParser from pathlib import Path +from typing import List import matplotlib.pyplot as plt +import numpy as np import pandas as pd from flatten_dict import flatten from omegaconf import OmegaConf from pandas import DataFrame -from rich.console import Console -from rich.table import Table -from rich.terminal_theme import MONOKAI -def gather_full_report(root_folder: Path, report_folder: str = "artifacts") -> DataFrame: +def gather_full_report(root_folders: List[Path], report_folder: str = "artifacts") -> DataFrame: # key is path to inference file as string, value is dataframe - inference_dfs = { - f.parent.absolute().as_posix(): pd.read_csv(f) for f in root_folder.glob("**/inference_results.csv") - } - # key is path to config file as string, value is flattened dict - config_dfs = { - f.parent.absolute() - .as_posix(): pd.DataFrame.from_dict(flatten(OmegaConf.load(f), reducer="dot"), orient="index") - .T - for f in root_folder.glob("**/hydra_config.yaml") - if f.parent.absolute().as_posix() in inference_dfs.keys() - } + config_dfs = {} + inference_dfs = {} + + for root_folder in root_folders: + inference_dfs.update( + {f.parent.absolute().as_posix(): pd.read_csv(f) for f in root_folder.glob("**/inference_results.csv")} + ) + config_dfs.update( + { + f.parent.absolute() + .as_posix(): pd.DataFrame.from_dict(flatten(OmegaConf.load(f), reducer="dot"), orient="index") + .T + for f in root_folder.glob("**/hydra_config.yaml") + if f.parent.absolute().as_posix() in inference_dfs.keys() + } + ) if len(inference_dfs) == 0 or len(config_dfs) == 0: raise ValueError(f"No results found in {root_folder}") @@ -36,9 +40,6 @@ def gather_full_report(root_folder: Path, report_folder: str = "artifacts") -> D # Concatenate all reports inference_report = pd.concat(inference_reports, axis=0, ignore_index=True) - inference_report.set_index("experiment_name", inplace=True) - - inference_report.sort_values(by="forward.throughput(samples/s)", ascending=False, inplace=True) inference_report.to_csv(f"{report_folder}/full_report.csv") return inference_report @@ -46,225 +47,205 @@ def gather_full_report(root_folder: Path, report_folder: str = "artifacts") -> D def get_short_report(full_report, report_folder: str = "artifacts"): short_columns = { - "environment.gpus": "GPU", - "benchmark.input_shapes.batch_size": "Batch Size", - "forward.latency(s)": "Forward Latency (s)", - "forward.throughput(samples/s)": "Forward Throughput (samples/s)", - "forward.max_memory_used(MB)": "Forward Max Memory Used (MB)", - "forward.max_memory_allocated(MB)": "Forward Max Memory Allocated (MB)", - "forward.max_memory_reserved(MB)": "Forward Max Memory Reserved (MB)", - "generate.throughput(tokens/s)": "Generate Throughput (tokens/s)", - "generate.max_memory_used(MB)": "Generate Max Memory Used (MB)", + "model": "Model", + "environment.gpus": "GPUs", + "experiment_name": "Experiment Name", + "benchmark.input_shapes.batch_size": "Per Process Batch Size", + "benchmark.input_shapes.sequence_length": "Sequence Length", + # + "decode.latency(s)": "Decode Latency (s)", + "forward.latency(s)": "Prefill Latency (s)", + # + "decode.throughput(tokens/s)": "Decode Throughput (tokens/s)", + "forward.throughput(samples/s)": "Prefill Throughput (samples/s)", + # "generate.max_memory_allocated(MB)": "Generate Max Memory Allocated (MB)", "generate.max_memory_reserved(MB)": "Generate Max Memory Reserved (MB)", } short_report = full_report[list(short_columns.keys())].rename(columns=short_columns) - short_report["Quantization Scheme"] = full_report.index.str.split("-").str[0] - short_report["Quantization Scheme"].fillna("unquantized", inplace=True) - short_report["Quantization Scheme"].replace("bnb", "BnB", inplace=True) - short_report["Quantization Scheme"].replace("gptq", "GPTQ", inplace=True) - short_report["Quantization Scheme"].replace("gptq+triton", "GPTQ+Triton", inplace=True) - short_report["Quantization Scheme"].replace("gptq+cuda_old", "GPTQ+CUDA_old", inplace=True) - - short_report["GPU"] = short_report["GPU"].str[0] - short_report["GPU"].replace("AMD INSTINCT MI250 (MCM) OAM AC MBA", "MI250", inplace=True) - short_report["GPU"].replace("NVIDIA A100-SXM4-80GB", "A100", inplace=True) - - short_report["Group"] = short_report["GPU"] + "-" + short_report["Quantization Scheme"] + short_report["GPU Name"] = short_report["GPUs"].str[0] + short_report["Num GPUs"] = short_report["GPUs"].str.len() + short_report["GPU Name"].replace("NVIDIA A100-SXM4-80GB", "1xA100", inplace=True) + short_report["GPU Name"].replace("AMD INSTINCT MI250 (MCM) OAM AC MBA", "1xMI250", inplace=True) + short_report["Effective Batch Size"] = short_report["Per Process Batch Size"] * short_report["Num GPUs"] + short_report["Group"] = short_report["GPU Name"] + "-" + short_report["Experiment Name"] short_report.to_csv(f"{report_folder}/short_report.csv") return short_report -def get_plots(short_report, memory: str = "allocated", report_folder: str = "artifacts"): - # for each quantization scheme we plot the throughput vs batch size +def get_batch_plots(short_report, report_folder, plot="bar", memory=True): fig1, ax1 = plt.subplots() fig2, ax2 = plt.subplots() fig3, ax3 = plt.subplots() fig4, ax4 = plt.subplots() - for group in short_report["Group"].unique(): - mask = short_report["Group"] == group + batch_column = "Effective Batch Size" + short_report = short_report.sort_values(by="Group", ascending=True) + groups = short_report["Group"].unique().tolist() + x = np.arange(len(short_report[batch_column].unique())) + width = 0.8 / len(short_report["Group"].unique().tolist()) + offset = -(width * (len(groups) - 1) / 2) - forward_latency = short_report[mask][["Batch Size", "Forward Latency (s)"]].sort_values(by="Batch Size") - generate_throughput = short_report[mask][["Batch Size", "Generate Throughput (tokens/s)"]].sort_values( - by="Batch Size" - ) - forward_memory = short_report[mask][["Batch Size", "Forward Max Memory Used (MB)"]].sort_values( - by="Batch Size" - ) - forward_pytorch_max_memory_allocated = short_report[mask][ - ["Batch Size", "Forward Max Memory Allocated (MB)"] - ].sort_values(by="Batch Size") - forward_pytorch_max_memory_reserved = short_report[mask][ - ["Batch Size", "Forward Max Memory Reserved (MB)"] - ].sort_values(by="Batch Size") - generate_memory = short_report[mask][["Batch Size", "Generate Max Memory Used (MB)"]].sort_values( - by="Batch Size" - ) - generate_pytorch_max_memory_allocated = short_report[mask][ - ["Batch Size", "Generate Max Memory Allocated (MB)"] - ].sort_values(by="Batch Size") - generate_pytorch_max_memory_reserved = short_report[mask][ - ["Batch Size", "Generate Max Memory Reserved (MB)"] - ].sort_values(by="Batch Size") - - ax1.plot( - forward_latency["Batch Size"], - forward_latency["Forward Latency (s)"], - label=group, - marker="o", - ) - ax2.plot( - generate_throughput["Batch Size"], - generate_throughput["Generate Throughput (tokens/s)"], - label=group, - marker="o", + for group in groups: + mask = short_report["Group"] == group + group_report = short_report[mask].sort_values(by=batch_column) + x_ = np.arange( + group_report[batch_column].min() - 1, + len(group_report[batch_column].unique()) + (group_report[batch_column].min() - 1), ) - if "used" in memory: - ax3.plot( - forward_memory["Batch Size"], - forward_memory["Forward Max Memory Used (MB)"], - label=group + "-used", - marker="^", + if plot == "bar": + ax1.bar( + x_ + offset, + group_report["Prefill Latency (s)"], + label=group, + width=width, ) - ax4.plot( - generate_memory["Batch Size"], - generate_memory["Generate Max Memory Used (MB)"], - label=group + "-used", - marker="^", + ax2.bar( + x_ + offset, + group_report["Decode Throughput (tokens/s)"], + label=group, + width=width, ) - if "reserved" in memory: - ax3.plot( - forward_pytorch_max_memory_reserved["Batch Size"], - forward_pytorch_max_memory_reserved["Forward Max Memory Reserved (MB)"], - label=group + "-reserved", - marker=".", + ax3.bar( + x_ + offset, + group_report["Generate Max Memory Allocated (MB)"], + label=group, + width=width, ) - ax4.plot( - generate_pytorch_max_memory_reserved["Batch Size"], - generate_pytorch_max_memory_reserved["Generate Max Memory Reserved (MB)"], - label=group + "-reserved", - marker=".", + ax4.bar( + x_ + offset, + group_report["Generate Max Memory Reserved (MB)"], + label=group, + width=width, + ) + offset += width + elif plot == "line": + ax1.plot( + x_, + group_report["Prefill Latency (s)"], + label=group, + marker="o", + ) + ax2.plot( + x_, + group_report["Decode Throughput (tokens/s)"], + label=group, + marker="o", ) - if "allocated" in memory: ax3.plot( - forward_pytorch_max_memory_allocated["Batch Size"], - forward_pytorch_max_memory_allocated["Forward Max Memory Allocated (MB)"], - label=group + "-allocated", - marker="*", + x_, + group_report["Generate Max Memory Allocated (MB)"], + label=group, + marker="o", ) ax4.plot( - generate_pytorch_max_memory_allocated["Batch Size"], - generate_pytorch_max_memory_allocated["Generate Max Memory Allocated (MB)"], - label=group + "-allocated", - marker="*", + x_, + group_report["Generate Max Memory Reserved (MB)"], + label=group, + marker="o", ) - ax1.set_xlabel("Batch Size") - ax1.set_ylabel("Forward Latency (s)") - ax1.set_title("Forward Latency per Batch Size") - - ax2.set_xlabel("Batch Size") - ax2.set_ylabel("Generate Throughput (tokens/s)") - ax2.set_title("Generate Throughput per Batch Size") - - ax3.set_xlabel("Batch Size") - ax3.set_ylabel("Forward Max Memory Used (MB)") - ax3.set_title("Forward Max Memory Used per Batch Size") - - ax4.set_xlabel("Batch Size") - ax4.set_ylabel("Generate Max Memory Used (MB)") - ax4.set_title("Generate Max Memory Used per Batch Size") - + ax1.set_xticks(x) + ax1.set_ylim(bottom=0) + ax1.set_xticklabels(short_report[batch_column].sort_values().unique().tolist()) + ax1.set_xlabel(batch_column) + ax1.set_ylabel("Prefill Latency (s)") + ax1.set_title(f"Prefill Latency per Batch Size ({short_report['Model'].unique()[0]})") ax1.legend(fancybox=True, shadow=True) + + ax2.set_xticks(x) + ax2.set_ylim(bottom=0) + ax2.set_xticklabels(short_report[batch_column].sort_values().unique().tolist()) + ax2.set_xlabel(batch_column) + ax2.set_ylabel("Effective Decode Throughput (tokens/s)") + ax2.set_title(f"Decode Throughput per Batch Size ({short_report['Model'].unique()[0]})") ax2.legend(fancybox=True, shadow=True) + + ax3.set_xticks(x) + ax3.set_ylim(bottom=0) + ax3.set_xticklabels(short_report[batch_column].sort_values().unique().tolist()) + ax3.set_xlabel(batch_column) + ax3.set_ylabel("Generate Max Memory Allocated (MB)") + ax3.set_title(f"Generate Max Memory Allocated per Batch Size ({short_report['Model'].unique()[0]})") ax3.legend(fancybox=True, shadow=True) + + ax4.set_xticks(x) + ax4.set_ylim(bottom=0) + ax4.set_xticklabels(short_report[batch_column].sort_values().unique().tolist()) + ax4.set_xlabel(batch_column) + ax4.set_ylabel("Generate Max Memory Reserved (MB)") + ax4.set_title(f"Generate Max Memory Reserved per Batch Size ({short_report['Model'].unique()[0]})") ax4.legend(fancybox=True, shadow=True) - fig1.savefig(f"{report_folder}/forward_latency_plot.png") - fig2.savefig(f"{report_folder}/generate_throughput_plot.png") - fig3.savefig(f"{report_folder}/forward_memory_plot.png") - fig4.savefig(f"{report_folder}/generate_memory_plot.png") - - return fig1, fig2, fig3, fig4 - - -def style_element(element, style=""): - if style: - return f"[{style}]{element}[/{style}]" - else: - return element - - -def format_element(element, style=""): - if isinstance(element, float): - if element != element: # nan - formated_element = "" - elif abs(element) >= 1: - formated_element = f"{element:.2f}" - elif abs(element) > 1e-6: - formated_element = f"{element:.2e}" - else: - formated_element = f"{element}" - elif element is None: - formated_element = "" - elif isinstance(element, bool): - if element: - formated_element = style_element("✔", style="green") - else: - formated_element = style_element("✘", style="red") - else: - formated_element = str(element) - - return style_element(formated_element, style=style) - - -def format_row(row, style=""): - formated_row = [] - for element in row: - formated_row.append(format_element(element, style=style)) - return formated_row - - -def get_rich_table(short_report, report_folder: str = "artifacts"): - # create rich table - rich_table = Table(show_header=True, show_lines=True) - # we add a column for the index - rich_table.add_column("Experiment Name", justify="left", header_style="") - # we populate the table with values - for column in short_report.columns: - rich_table.add_column(column, justify="right", header_style="bold") - # we add rows - for index, row in short_report.iterrows(): - rich_table.add_row(index, *format_row(row.values, style="")) - - console = Console(record=True) - console.print(rich_table, justify="center") - console.save_svg(f"{report_folder}/rich_table.svg", theme=MONOKAI, title="Inference Report") - - return rich_table + legend = plt.legend(loc="upper center") + legend.get_frame().set_facecolor((0, 0, 1, 0.1)) + legend.get_frame().set_alpha(None) + plt.tight_layout() + + fig1.savefig(f"{report_folder}/prefill_latency_{plot}_plot.png") + fig2.savefig(f"{report_folder}/decode_throughput_{plot}_plot.png") + + if memory: + fig3.savefig(f"{report_folder}/generate_max_memory_allocated_{plot}_plot.png") + fig4.savefig(f"{report_folder}/generate_max_memory_reserved_{plot}_plot.png") + return fig1, fig2, fig3, fig4 + + return fig1, fig2 + + +def get_peak_decode_throughput_plot(short_report, report_folder): + # a bar plot with one bar per group, representing the max attainable throughput in tokens/s + fig, ax = plt.subplots() + + # + max_decode_throughput = short_report.groupby("Group")["Decode Throughput (tokens/s)"].max().reset_index() + max_decode_throughput = ( + short_report.merge(max_decode_throughput, on=["Group", "Decode Throughput (tokens/s)"]) + .sort_values(by="Decode Throughput (tokens/s)", ascending=True) + .reset_index() + ) + + ax.bar( + max_decode_throughput["Group"], + max_decode_throughput["Decode Throughput (tokens/s)"], + color=plt.cm.Paired(np.arange(len(max_decode_throughput))), + ) + + # add batch size on top of each bar + for i, v in enumerate(max_decode_throughput["Effective Batch Size"]): + ax.text( + i, + max_decode_throughput["Decode Throughput (tokens/s)"].iloc[i], + f"bs={v}", + ha="center", + va="bottom", + ) + + ax.set_xlabel("Group") + ax.set_ylabel("Peak Decode Throughput (tokens/s)") + ax.set_title(f"Peak Decode Throughput ({short_report['Model'].unique()[0]})") + ax.set_ylim(top=max_decode_throughput["Decode Throughput (tokens/s)"].max() * 1.1) + + plt.xticks(rotation=45, ha="right") + plt.tight_layout() + + fig.savefig(f"{report_folder}/peak_decode_throughput_bar_plot.png") + + return fig def generate_report(): parser = ArgumentParser() parser.add_argument( - "--experiments", + "--experiments-folders", "-e", type=Path, + nargs="+", required=True, help="The folder containing the results of experiments.", ) - parser.add_argument( - "--memory", - "-m", - nargs="*", - type=str, - required=False, - help="choose memory metric", - choices=["used", "reserved", "allocated"], - ) parser.add_argument( "--report-name", "-r", @@ -276,20 +257,32 @@ def generate_report(): args = parser.parse_args() report_folder = args.report_name - experiments_folders = args.experiments + experiments_folders = args.experiments_folders Path(report_folder).mkdir(parents=True, exist_ok=True) - if args.memory is None: - memory = ["used", "reserved", "allocated"] - else: - memory = args.memory - # gather experiments results - full_report = gather_full_report(experiments_folders, report_folder=report_folder) - short_report = get_short_report(full_report, report_folder=report_folder) - figs = get_plots(short_report, memory=memory, report_folder=report_folder) - rich_table = get_rich_table(short_report, report_folder=report_folder) + full_report = gather_full_report( + root_folders=experiments_folders, + report_folder=report_folder, + ) + short_report = get_short_report( + full_report, + report_folder=report_folder, + ) + for plot in ["bar", "line"]: + _ = get_batch_plots( + short_report, + report_folder, + plot=plot, + memory=True, + ) + + _ = get_peak_decode_throughput_plot( + short_report, + report_folder, + ) + print("Report generated successfully!") if __name__ == "__main__": diff --git a/optimum_benchmark/backends/isolation_utils.py b/optimum_benchmark/backends/isolation_utils.py index 447fc787..90c39f2e 100644 --- a/optimum_benchmark/backends/isolation_utils.py +++ b/optimum_benchmark/backends/isolation_utils.py @@ -3,8 +3,9 @@ import signal import time from logging import getLogger -from typing import Dict, List +from typing import Dict, Set +import psutil from omegaconf import OmegaConf from ..env_utils import is_nvidia_system, is_rocm_system @@ -13,13 +14,13 @@ LOGGER = getLogger("isolation") -def check_cuda_isolation(isolated_devices: List[int], permitted_pids: List[int]) -> None: +def check_cuda_isolation(isolated_devices: Set[int], permitted_pids: Set[int]) -> None: """ - Raises a RuntimeError if any process other than the permitted ones is running on the specified CUDA devices. + Returns a set of pids that are running on the specified CUDA devices and are not in the permitted_pids set. """ - pids: Dict[int, set] = {} + devices_pids: Dict[int, set] = {} for device_id in isolated_devices: - pids[device_id] = set() + devices_pids[device_id] = set() if is_nvidia_system(): if not is_py3nvml_available(): @@ -38,7 +39,7 @@ def check_cuda_isolation(isolated_devices: List[int], permitted_pids: List[int]) LOGGER.warning(f"Found unexpected process {device_process.pid} on device {device_id}.") LOGGER.warning(f"Process info: {device_process}") - pids[device_id].add(device_process.pid) + devices_pids[device_id].add(device_process.pid) nvml.nvmlShutdown() elif is_rocm_system(): @@ -78,7 +79,7 @@ def check_cuda_isolation(isolated_devices: List[int], permitted_pids: List[int]) LOGGER.warning(f"Found unexpected process {info['pid']} on device {device_id}.") LOGGER.warning(f"Process info: {info}") - pids[device_id].add(info["pid"]) + devices_pids[device_id].add(info["pid"]) else: devices_handles = amdsmi.amdsmi_get_device_handles() for device_id in isolated_devices: @@ -103,22 +104,19 @@ def check_cuda_isolation(isolated_devices: List[int], permitted_pids: List[int]) LOGGER.warning(f"Found unexpected process {info['pid']} on device {device_id}.") LOGGER.warning(f"Process info: {info}") - pids[device_id].add(info["pid"]) + devices_pids[device_id].add(info["pid"]) amdsmi.amdsmi_shut_down() else: raise ValueError("check_no_process_is_running_on_cuda_device is only supported on NVIDIA and AMD GPUs.") - all_pids = set() - for device_id in isolated_devices: - all_pids |= pids[device_id] - other_pids = all_pids - set(permitted_pids) + all_devices_pids = set() + for device_pids in devices_pids.values(): + all_devices_pids = all_devices_pids.union(device_pids) - if len(other_pids) > 0: - error_message = ( - f"Expected only process(se) {permitted_pids} on device(s) {isolated_devices}, but found {other_pids}." - ) - raise RuntimeError(error_message) + non_permitted_pids = all_devices_pids - permitted_pids + + return non_permitted_pids def check_cuda_continuous_isolation(isolated_pid: int, isolation_check_interval: int = 1) -> None: @@ -126,16 +124,14 @@ def check_cuda_continuous_isolation(isolated_pid: int, isolation_check_interval: Kills the isolated process if any other process than the permitted ones is running on the specified CUDA devices. """ - hydra_conf = OmegaConf.load(".hydra/hydra.yaml") - logging.config.dictConfig(OmegaConf.to_container(hydra_conf.hydra.job_logging, resolve=True)) - # distributed setting is tricky if os.environ.get("LOCAL_WORLD_SIZE", None) is not None: from torch.distributed import TCPStore local_rank = os.environ["LOCAL_RANK"] - all_isolated_keys = [f"isolated_{other_rank}" for other_rank in range(int(os.environ["LOCAL_WORLD_SIZE"]))] - all_isolators_keys = [f"isolator_{other_rank}" for other_rank in range(int(os.environ["LOCAL_WORLD_SIZE"]))] + local_world_size = os.environ["LOCAL_WORLD_SIZE"] + all_isolated_keys = [f"isolated_{other_rank}" for other_rank in range(int(local_world_size))] + all_isolators_keys = [f"isolator_{other_rank}" for other_rank in range(int(local_world_size))] store = TCPStore(host_name=os.environ["MASTER_ADDR"], port=int(os.environ["MASTER_PORT"])) @@ -146,24 +142,35 @@ def check_cuda_continuous_isolation(isolated_pid: int, isolation_check_interval: all_isolated_pids = [int(store.get(name)) for name in all_isolated_keys] all_isolators_pids = [int(store.get(name)) for name in all_isolators_keys] permitted_pids = all_isolated_pids + all_isolators_pids - assert len(permitted_pids) == len(set(permitted_pids)), "Found duplicated pids in the distributed setting" else: isolator_pid = os.getpid() - permitted_pids = [isolator_pid, isolated_pid] - - isolated_devices = [int(device) for device in os.environ["CUDA_VISIBLE_DEVICES"].split(",")] - - LOGGER.info( - f"Continuously checking only process(es) {permitted_pids} is/are running on device(s) {isolated_devices}" - ) + all_isolated_pids = [isolated_pid] + all_isolators_pids = [isolator_pid] + + permitted_pids = all_isolated_pids + all_isolators_pids + assert len(permitted_pids) == len(set(permitted_pids)), "Found duplicated pids in the non-distributed setting" + permitted_pids = set(permitted_pids) + + # TODO: make backend only spawn one process per local world + if os.environ.get("LOCAL_RANK", "0") == "0": + hydra_conf = OmegaConf.load(".hydra/hydra.yaml") + logging.config.dictConfig(OmegaConf.to_container(hydra_conf.hydra.job_logging, resolve=True)) + isolated_devices = {int(device) for device in os.environ["CUDA_VISIBLE_DEVICES"].split(",")} + LOGGER.info( + f"Continuously checking only permitted process(es) {permitted_pids} " + f"are running on isolated device(s) {isolated_devices}" + ) + else: + return while True: - try: - check_cuda_isolation(isolated_devices, permitted_pids) + non_permitted_pids = check_cuda_isolation(isolated_devices, permitted_pids) + if len(non_permitted_pids) > 0: + LOGGER.error(f"Found non permitted process(es) {non_permitted_pids} running on isolated device(s).") + for pid in all_isolated_pids: + if psutil.pid_exists(pid): + LOGGER.error(f"Terminating isolated process {pid}.") + os.kill(pid, signal.SIGTERM) + exit(1) + else: time.sleep(isolation_check_interval) - except RuntimeError as e: - LOGGER.error("Error while checking CUDA isolation:") - LOGGER.error(e) - LOGGER.error("Killing isolated process...") - os.kill(isolated_pid, signal.SIGTERM) # graceful kill, will trigger the backend cleanup - e.with_traceback() diff --git a/optimum_benchmark/backends/pytorch/backend.py b/optimum_benchmark/backends/pytorch/backend.py index 15884c57..f6e960e4 100644 --- a/optimum_benchmark/backends/pytorch/backend.py +++ b/optimum_benchmark/backends/pytorch/backend.py @@ -29,15 +29,26 @@ def configure(self, config: PyTorchConfig) -> None: LOGGER.info(f"\t+ Inferred AutoModel class {automodel} for task {self.task} and model_type {self.model_type}") # for now we rely on this env variable to know if we're in a distributed setting - if os.environ.get("LOCAL_WORLD_SIZE", None) is not None: - LOGGER.info(f"\t+ Detected local world size: {os.environ['LOCAL_WORLD_SIZE']}") + if os.environ.get("WORLD_SIZE", None) is not None: + LOGGER.info("\t+ Detected distributed CUDA environment") + + visible_devices = os.environ["CUDA_VISIBLE_DEVICES"].split(",") + LOGGER.info(f"\t+ Detected cuda visible devices: {visible_devices}") + + world_size = int(os.environ["WORLD_SIZE"]) + LOGGER.info(f"\t+ Detected world size: {world_size}") + + local_world_size = int(os.environ["LOCAL_WORLD_SIZE"]) + LOGGER.info(f"\t+ Detected local world size: {local_world_size}") + + rank = int(os.environ["RANK"]) + LOGGER.info(f"\t+ Detected rank: {rank}") + local_rank = int(os.environ["LOCAL_RANK"]) LOGGER.info(f"\t+ Detected local rank: {local_rank}") - available_devices = list(map(int, os.environ.get("CUDA_VISIBLE_DEVICES", "0").split(","))) - LOGGER.info(f"\t+ Detected available devices: {available_devices}") - default_device = available_devices[local_rank] - LOGGER.info(f"\t+ Setting default device to: {default_device}") - torch.cuda.set_device(default_device) + + LOGGER.info("\t+ Setting default cuda device to local rank") + torch.cuda.set_device(local_rank) # Gradients options if self.config.disable_grad: diff --git a/optimum_benchmark/backends/pytorch/config.py b/optimum_benchmark/backends/pytorch/config.py index 3f43678c..f1cbbc95 100644 --- a/optimum_benchmark/backends/pytorch/config.py +++ b/optimum_benchmark/backends/pytorch/config.py @@ -18,8 +18,8 @@ TORCH_DTYPES = ["bfloat16", "float16", "float32", "auto"] QUANTIZATION_CONFIGS = { - "gptq": {"dataset": ["lorem ipsum dolor sit amet consectetur"]}, "bnb": {"llm_int8_threshold": 0.0}, + "gptq": {}, "awq": {}, } COMPILE_CONFIG = { @@ -43,7 +43,7 @@ class PyTorchConfig(BackendConfig): device_map: Optional[str] = None torch_dtype: Optional[str] = None - # inference options + # inference/training options eval_mode: bool = "${is_inference:${benchmark.name}}" disable_grad: bool = "${is_inference:${benchmark.name}}" diff --git a/optimum_benchmark/benchmarks/inference/benchmark.py b/optimum_benchmark/benchmarks/inference/benchmark.py index f2f3e08a..288d4e71 100644 --- a/optimum_benchmark/benchmarks/inference/benchmark.py +++ b/optimum_benchmark/benchmarks/inference/benchmark.py @@ -174,6 +174,7 @@ def run_generate_energy_tracking(self, backend: "Backend") -> None: num_generated_tokens = ( num_generate_passes * self.config.generate_kwargs["min_new_tokens"] + * self.config.generate_kwargs["num_return_sequences"] * self.config.input_shapes["batch_size"] ) self.generate_energy = extract_three_significant_digits( @@ -215,7 +216,7 @@ def forward_latency(self) -> float: @property @three_significant_digits_wrapper def forward_throughput(self) -> float: - return self.config.input_shapes["batch_size"] / self.forward_latency + return self.config.input_shapes["batch_size"] * int(os.environ.get("WORLD_SIZE", "1")) / self.forward_latency ## Generation pass metrics @property @@ -228,10 +229,28 @@ def generate_latency(self) -> float: def generate_throughput(self) -> float: return ( self.config.generate_kwargs["min_new_tokens"] + * self.config.generate_kwargs["num_return_sequences"] * self.config.input_shapes["batch_size"] + * int(os.environ.get("WORLD_SIZE", "1")) / self.generate_latency ) + @property + @three_significant_digits_wrapper + def decode_latency(self) -> float: + return self.generate_latency - self.forward_latency + + @property + @three_significant_digits_wrapper + def decode_throughput(self) -> float: + return ( + (self.config.generate_kwargs["min_new_tokens"] - 1) + * self.config.generate_kwargs["num_return_sequences"] + * self.config.input_shapes["batch_size"] + * int(os.environ.get("WORLD_SIZE", "1")) + / self.decode_latency + ) + ## Diffusion pass metrics @property @three_significant_digits_wrapper @@ -239,6 +258,7 @@ def diffusion_throughput(self) -> float: return ( self.config.input_shapes["batch_size"] * self.config.forward_kwargs["num_images_per_prompt"] + * int(os.environ.get("WORLD_SIZE", "1")) / self.forward_latency ) @@ -252,10 +272,6 @@ def get_results_df(self) -> DataFrame: results_dict["diffusion.throughput(images/s)"] = self.diffusion_throughput if self.config.memory: - LOGGER.warning( - "forward.peak_memory(MB) is deprecated and will be removed in a future release" - " please use forward.max_memory_used(MB) instead" - ) results_dict["forward.peak_memory(MB)"] = self.forward_max_memory_used results_dict["forward.max_memory_used(MB)"] = self.forward_max_memory_used results_dict["forward.max_memory_allocated(MB)"] = self.forward_max_memory_allocated @@ -269,11 +285,10 @@ def get_results_df(self) -> DataFrame: results_dict["generate.latency(s)"] = self.generate_latency results_dict["generate.throughput(tokens/s)"] = self.generate_throughput + results_dict["decode.latency(s)"] = self.decode_latency + results_dict["decode.throughput(tokens/s)"] = self.decode_throughput + if self.config.memory: - LOGGER.warning( - "generate.peak_memory(MB) is deprecated and will be removed in a future release" - " please use generate.max_memory_used(MB) instead" - ) results_dict["generate.peak_memory(MB)"] = self.generate_max_memory_used results_dict["generate.max_memory_used(MB)"] = self.generate_max_memory_used results_dict["generate.max_memory_allocated(MB)"] = self.generate_max_memory_allocated @@ -286,7 +301,8 @@ def get_results_df(self) -> DataFrame: return DataFrame(results_dict, index=[0]) def save(self) -> None: - if os.environ.get("LOCAL_RANK", "0") == "0": + # TODO: handle this by merging the results of all processes instead of only saving the results of the main process + if os.environ.get("RANK", "0") == "0": LOGGER.info("Saving results") results_df = self.get_results_df() results_df.to_csv("inference_results.csv", index=False) diff --git a/optimum_benchmark/experiment.py b/optimum_benchmark/experiment.py index bdb3179e..b761e4ac 100644 --- a/optimum_benchmark/experiment.py +++ b/optimum_benchmark/experiment.py @@ -22,6 +22,7 @@ optimum_version, transformers_version, ) +from .launchers.inline.config import InlineConfig from .launchers.process.config import ProcessConfig from .launchers.torchrun.config import TorchrunConfig from .task_utils import infer_task_from_model_name_or_path @@ -29,7 +30,7 @@ if TYPE_CHECKING: from .backends.base import Backend from .benchmarks.base import Benchmark - from .launchers.base import Launcher, LauncherConfig + from .launchers.base import Launcher LOGGER = getLogger("experiment") @@ -122,13 +123,17 @@ def __post_init__(self) -> None: # Register configurations cs = ConfigStore.instance() cs.store(name="experiment", node=ExperimentConfig) +# cs.store(group="backend", name="openvino", node=OVConfig) cs.store(group="backend", name="pytorch", node=PyTorchConfig) cs.store(group="backend", name="onnxruntime", node=ORTConfig) cs.store(group="backend", name="neural-compressor", node=INCConfig) cs.store(group="backend", name="text-generation-inference", node=TGIConfig) +# cs.store(group="benchmark", name="inference", node=InferenceConfig) cs.store(group="benchmark", name="training", node=TrainingConfig) +# +cs.store(group="launcher", name="inline", node=InlineConfig) cs.store(group="launcher", name="process", node=ProcessConfig) cs.store(group="launcher", name="torchrun", node=TorchrunConfig) @@ -180,11 +185,11 @@ def run(experiment: "ExperimentConfig") -> "Benchmark": def run_with_launcher(experiment: DictConfig): # instead of emplimenting hydra/launcher plugins, we handle the launcher ourselves - # thsi allows us to use spawn with torchrun, to gather outputs from parallel processes, + # this allows us to use spawn with torchrun, to gather outputs from parallel processes, # and to handle errors gracefully # Instantiate the experiment config to trigger __post_init__ - experiment.launcher: LauncherConfig = OmegaConf.to_object(experiment.launcher) + experiment.launcher = OmegaConf.to_object(experiment.launcher) launcher_factory: Type["Launcher"] = get_class(experiment.launcher._target_) launcher: "Launcher" = launcher_factory() diff --git a/optimum_benchmark/launchers/inline/__init__.py b/optimum_benchmark/launchers/inline/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/optimum_benchmark/launchers/inline/config.py b/optimum_benchmark/launchers/inline/config.py new file mode 100644 index 00000000..db263b5f --- /dev/null +++ b/optimum_benchmark/launchers/inline/config.py @@ -0,0 +1,12 @@ +from dataclasses import dataclass +from logging import getLogger + +from ..base import LauncherConfig + +LOGGER = getLogger("inline") + + +@dataclass +class InlineConfig(LauncherConfig): + name: str = "inline" + _target_: str = "optimum_benchmark.launchers.inline.launcher.InlineLauncher" diff --git a/optimum_benchmark/launchers/inline/launcher.py b/optimum_benchmark/launchers/inline/launcher.py new file mode 100644 index 00000000..36140338 --- /dev/null +++ b/optimum_benchmark/launchers/inline/launcher.py @@ -0,0 +1,20 @@ +from logging import getLogger +from typing import Callable + +from ..base import Launcher +from .config import InlineConfig + +LOGGER = getLogger("inline") + + +class InlineLauncher(Launcher[InlineConfig]): + NAME = "inline" + + def __init__(self) -> None: + super().__init__() + + def configure(self, config: InlineConfig) -> None: + super().configure(config) + + def launch(self, worker: Callable, *worker_args): + worker(*worker_args) diff --git a/optimum_benchmark/launchers/process/launcher.py b/optimum_benchmark/launchers/process/launcher.py index 5c8f17bc..ac1312ca 100644 --- a/optimum_benchmark/launchers/process/launcher.py +++ b/optimum_benchmark/launchers/process/launcher.py @@ -30,6 +30,9 @@ def launch(self, worker: Callable, *worker_args): process = Process( target=target, args=(worker, *worker_args), + # daemon=True + # TODO: move isolation process to the launcher and make this daemon + # which is currently not possible because daemon process cannot have children ) process.start() @@ -47,7 +50,10 @@ def launch(self, worker: Callable, *worker_args): process.join() if process.exitcode != 0: - raise RuntimeError(f"Process exited with code {process.exitcode}") + exit_code = process.exitcode + LOGGER.error(f"\t+ Process exited with code {exit_code}, closing it.") + process.close() + raise RuntimeError(f"Process exited with code {exit_code}") LOGGER.info("\t+ Process exited successfully, closing it.") process.close() diff --git a/optimum_benchmark/trackers/memory.py b/optimum_benchmark/trackers/memory.py index af18b8a7..af08e496 100644 --- a/optimum_benchmark/trackers/memory.py +++ b/optimum_benchmark/trackers/memory.py @@ -95,8 +95,12 @@ def _cuda_memory(self): raise ValueError("Could not measure GPU memory usage for a system different than NVIDIA or AMD RoCm.") for device_index in self.pytorch_device_ids: - self.max_memory_allocated += torch.cuda.max_memory_allocated(device=device_index) - self.max_memory_reserved += torch.cuda.max_memory_reserved(device=device_index) + self.max_memory_allocated += torch.cuda.max_memory_allocated(device=device_index) * int( + os.environ.get("WORLD_SIZE", "1") + ) + self.max_memory_reserved += torch.cuda.max_memory_reserved(device=device_index) * int( + os.environ.get("WORLD_SIZE", "1") + ) LOGGER.debug(f"Pytorch max memory allocated: {self.get_max_memory_allocated()} MB") LOGGER.debug(f"Pytorch max memory reserved: {self.get_max_memory_reserved()} MB")