diff --git "a/perf-df-gptq-1xA10.csv" "b/perf-df-gptq-1xA10.csv" --- "a/perf-df-gptq-1xA10.csv" +++ "b/perf-df-gptq-1xA10.csv" @@ -103,7 +103,7 @@ If this is a private repository, make sure to pass a token having permission to 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-4B,,cuda,0,42,,,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-72B,Qwen/Qwen1.5-72B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -148,11 +148,11 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 36974 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 36506 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/pythia-1.4b,,cuda,0,42,,,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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+4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-7.5B,facebook/xglm-7.5B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -184,7 +184,7 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmplwzg56mu/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp5atr_fwq/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,huggyllama/llama-30b,huggyllama/llama-30b,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.289728,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpyxf8g0mt/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpd3efrvad/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-125m,,cuda,0,42,,,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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Please req 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,stabilityai/stablelm-2-12b,stabilityai/stablelm-2-12b,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.2.1,,4.41.0,,0.30.1,,,,1.19.2,,,,0.11.1,,,MB,2304.897024,9284.616192,0.0,8638.169088,8363.057664,s,10,5.4696609497070305,0.546966094970703,0.00026571478623493513,0.5469190979003906,0.5471485473632812,0.5474143615722655,0.547627012939453,"[0.54768017578125, 0.5469967651367188, 0.5468720703125, 0.5467206420898437, 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A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-72B,Qwen/Qwen-72B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -545,7 +545,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: FalconForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp12pq3sg7/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-14B,Qwen/Qwen-14B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-14B,Qwen/Qwen-14B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File 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+4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,databricks/dbrx-base,databricks/dbrx-base,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -1412,7 +1412,7 @@ torch.cuda.OutOfMemoryError: CUDA out of memory. 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-4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen2-beta-72B,Qwen/Qwen2-beta-72B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen2-beta-72B,Qwen/Qwen2-beta-72B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -1457,7 +1457,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 54039 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 53629 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,meta-llama/Llama-2-70b-hf,meta-llama/Llama-2-70b-hf,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -1644,7 +1644,7 @@ If this is a private repository, make sure to pass a token having permission to ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,huggyllama/llama-13b,huggyllama/llama-13b,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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-4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciCoder-1b,Deci/DeciCoder-1b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciCoder-1b,Deci/DeciCoder-1b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -1687,7 +1687,7 @@ ChildProcessError: Traceback (most recent call last): AttributeError: 'DeciCoderAttention' object has no attribute '_init_rope' ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,llama,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,google/recurrentgemma-2b,google/recurrentgemma-2b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,google/recurrentgemma-2b,google/recurrentgemma-2b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -1719,7 +1719,7 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: RecurrentGemmaForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpffc61kue/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: RecurrentGemmaForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp7n7w_k42/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,recurrent_gemma,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,v,v,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -1793,7 +1793,7 @@ If this is a private repository, make sure to pass a token having permission to ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/pythia-2.7b,,cuda,0,42,,,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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-4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -1876,7 +1876,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 75.50 MiB is free. Process 68614 has 22.11 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 32.08 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 68.50 MiB is free. Process 67239 has 22.11 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 32.08 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,0,0,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -1949,7 +1949,7 @@ OSError: 0 is not a local folder and is not a valid model identifier listed on ' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-4.5B,facebook/xglm-4.5B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-4.5B,facebook/xglm-4.5B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -1981,11 +1981,11 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp6g3zdad4/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpuhq9cjmc/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,TencentARC/Mistral_Pro_8B_v0.1,TencentARC/Mistral_Pro_8B_v0.1,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: CodeGenForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpt5umlfhh/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: CodeGenForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpvkhq66tk/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,codegen,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 17.50 MiB is free. Process 41922 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 10.50 MiB is free. Process 41472 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,B,B,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -2210,7 +2210,7 @@ If this is a private repository, make sure to pass a token having 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A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Salesforce/codegen-16B-nl,Salesforce/codegen-16B-nl,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2242,7 +2242,7 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: CodeGenForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp95_sgifa/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: CodeGenForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpht7jqs1_/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,codegen,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-6.7b,facebook/opt-6.7b,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2395,11 +2395,11 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 35574 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 35125 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/pythia-1.4b,EleutherAI/pythia-1.4b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.218-208.862.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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-4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-7.5B,facebook/xglm-7.5B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-7.5B,facebook/xglm-7.5B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2511,7 +2511,7 @@ OSError: We couldn't connect to 'https://huggingface.co' to load this file, coul Checkout your internet connection or see how to run the library in offline mode at 'https://huggingface.co/docs/transformers/installation#offline-mode'. ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciLM-7B,Deci/DeciLM-7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciLM-7B,Deci/DeciLM-7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2546,7 +2546,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: DeciLMForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,deci,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-2.7b,facebook/opt-2.7b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-2.7b,facebook/opt-2.7b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2582,7 +2582,7 @@ ValueError: OPTForCausalLM does not support an attention implementation through ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,huggyllama/llama-7b,huggyllama/llama-7b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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0.2749798278808594, 0.2751068115234375, 0.27494503784179686]",tokens/s,3.578290079338431,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-564M,facebook/xglm-564M,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-564M,facebook/xglm-564M,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2754,7 +2754,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: XGLMForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-125m,EleutherAI/gpt-neo-125m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-125m,EleutherAI/gpt-neo-125m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2789,7 +2789,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: GPTNeoForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,gpt_neo,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-j-6b,EleutherAI/gpt-j-6b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-j-6b,EleutherAI/gpt-j-6b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2827,7 +2827,7 @@ ValueError: GPTJForCausalLM does not support an attention implementation through 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,stabilityai/stablelm-2-12b,stabilityai/stablelm-2-12b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.2.1,,4.41.0,,0.30.1,,,,1.19.2,,,,0.11.1,,,MB,2295.332864,9284.616192,0.0,8638.169088,8363.057664,s,10,5.480043090820312,0.5480043090820312,0.00023767958050638718,0.547921142578125,0.5482332153320313,0.5484350891113281,0.5485965881347656,"[0.548636962890625, 0.5479285278320313, 0.5478641967773438, 0.5479214477539063, 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A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-72B,Qwen/Qwen-72B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -2962,7 +2962,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: FalconForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-14B,Qwen/Qwen-14B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-14B,Qwen/Qwen-14B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -3000,7 +3000,7 @@ ImportError: This modeling file requires the following packages that were not fo 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,stabilityai/stablelm-2-1_6b,stabilityai/stablelm-2-1_6b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.2.1,,4.41.0,,0.30.1,,,,1.19.2,,,,0.11.1,,,MB,1443.536896,2426.929152,0.0,1780.482048,1621.410304,s,10,0.7068105316162109,0.07068105316162109,0.00033069583366084575,0.07070081710815429,0.07103355484008789,0.07120412101745605,0.07134057395935059,"[0.07069222259521485, 0.0702221450805664, 0.07099565124511718, 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benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -3210,7 +3210,7 @@ KeyError: 'sdpa' ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,internlm/internlm2-20b,internlm/internlm2-20b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.217-205.860.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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-4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-30b,facebook/opt-30b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-30b,facebook/opt-30b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -3245,7 +3245,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: OPTForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-MoE-A2.7B,Qwen/Qwen1.5-MoE-A2.7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-MoE-A2.7B,Qwen/Qwen1.5-MoE-A2.7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -3345,7 +3345,7 @@ torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. 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+4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,databricks/dbrx-base,databricks/dbrx-base,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -3496,7 +3496,7 @@ Traceback (most recent call last): OSError: Incorrect path_or_model_id: '-'. Please provide either the path to a local folder or the repo_id of a model on the Hub. ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-350m,facebook/opt-350m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-350m,facebook/opt-350m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -3963,7 +3963,7 @@ torch.cuda.OutOfMemoryError: CUDA out of memory. 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+4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen2-beta-72B,Qwen/Qwen2-beta-72B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4008,7 +4008,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 52608 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 52222 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,meta-llama/Llama-2-70b-hf,meta-llama/Llama-2-70b-hf,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -4195,7 +4195,7 @@ If this is a private repository, make sure to 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-4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciCoder-1b,Deci/DeciCoder-1b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciCoder-1b,Deci/DeciCoder-1b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4238,7 +4238,7 @@ ChildProcessError: Traceback (most recent call last): AttributeError: 'DeciCoderAttention' object has no attribute '_init_rope' ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,llama,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,google/recurrentgemma-2b,google/recurrentgemma-2b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,google/recurrentgemma-2b,google/recurrentgemma-2b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4344,7 +4344,7 @@ If this is a private repository, make sure to pass a token having permission to ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/pythia-2.7b,EleutherAI/pythia-2.7b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.218-208.862.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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0.2396979217529297]",tokens/s,4.106255475461544,,,main,False,False,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-2.7B,EleutherAI/gpt-neo-2.7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-2.7B,EleutherAI/gpt-neo-2.7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4416,7 +4416,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: GPTNeoForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,gpt_neo,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4521,7 +4521,7 @@ OSError: 0 is not a local folder and is not a valid model identifier listed on ' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-4.5B,facebook/xglm-4.5B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-4.5B,facebook/xglm-4.5B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4557,7 +4557,7 @@ ValueError: XGLMForCausalLM does not support an attention implementation through ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,TencentARC/Mistral_Pro_8B_v0.1,TencentARC/Mistral_Pro_8B_v0.1,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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0.37286911010742185, 0.3729459228515625, 0.37285888671875]",tokens/s,2.6391354854994153,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Salesforce/codegen-6B-nl,Salesforce/codegen-6B-nl,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Salesforce/codegen-6B-nl,Salesforce/codegen-6B-nl,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4592,7 +4592,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: CodeGenForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,codegen,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4627,7 +4627,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: OPTForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-110B,Qwen/Qwen1.5-110B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-110B,Qwen/Qwen1.5-110B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4672,7 +4672,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 17.50 MiB is free. Process 40245 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 10.50 MiB is free. Process 39783 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,B,B,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -4816,7 +4816,7 @@ If this is a private repository, make sure to pass a token having permission to ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-sdpa,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,stabilityai/stablelm-base-alpha-3b,stabilityai/stablelm-base-alpha-3b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.218-208.862.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Salesforce/codegen-16B-nl,Salesforce/codegen-16B-nl,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4851,7 +4851,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: CodeGenForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,codegen,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-6.7b,facebook/opt-6.7b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v2-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-6.7b,facebook/opt-6.7b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -4990,7 +4990,7 @@ If this is a private repository, make sure to pass a 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-4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-72B,Qwen/Qwen1.5-72B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-72B,Qwen/Qwen1.5-72B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5035,11 +5035,11 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 34875 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 34392 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. 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-4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-7.5B,facebook/xglm-7.5B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-7.5B,facebook/xglm-7.5B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5151,7 +5151,7 @@ OSError: We couldn't connect to 'https://huggingface.co' to load this file, coul Checkout your internet connection or see how to run the library in offline mode at 'https://huggingface.co/docs/transformers/installation#offline-mode'. ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciLM-7B,Deci/DeciLM-7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciLM-7B,Deci/DeciLM-7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5186,7 +5186,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: DeciLMForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,deci,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-2.7b,facebook/opt-2.7b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-2.7b,facebook/opt-2.7b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5222,7 +5222,7 @@ ValueError: OPTForCausalLM does not support an attention implementation through ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-sdpa,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,huggyllama/llama-7b,huggyllama/llama-7b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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0.275009521484375, 0.27514163208007814, 0.27507302856445315, 0.27506585693359376, 0.27519384765625, 0.2751242370605469]",tokens/s,3.577803959884384,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-564M,facebook/xglm-564M,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-564M,facebook/xglm-564M,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5394,7 +5394,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: XGLMForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-125m,EleutherAI/gpt-neo-125m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-125m,EleutherAI/gpt-neo-125m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5429,7 +5429,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: GPTNeoForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,gpt_neo,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-j-6b,EleutherAI/gpt-j-6b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-j-6b,EleutherAI/gpt-j-6b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5467,7 +5467,7 @@ ValueError: GPTJForCausalLM does not support an 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A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-72B,Qwen/Qwen-72B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5602,7 +5602,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: FalconForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-14B,Qwen/Qwen-14B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-14B,Qwen/Qwen-14B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5640,7 +5640,7 @@ ImportError: This modeling file requires the following 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+4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-30b,facebook/opt-30b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5885,7 +5885,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: OPTForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-MoE-A2.7B,Qwen/Qwen1.5-MoE-A2.7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-MoE-A2.7B,Qwen/Qwen1.5-MoE-A2.7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -5985,7 +5985,7 @@ torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. 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-4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,databricks/dbrx-base,databricks/dbrx-base,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,databricks/dbrx-base,databricks/dbrx-base,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -6136,7 +6136,7 @@ Traceback (most recent call last): OSError: Incorrect path_or_model_id: '-'. Please provide either the path to a local folder or the repo_id of a model on the Hub. ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-350m,facebook/opt-350m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-350m,facebook/opt-350m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -6603,7 +6603,7 @@ torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. 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+4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen2-beta-72B,Qwen/Qwen2-beta-72B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -6648,7 +6648,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 51900 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 51467 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-sdpa,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,meta-llama/Llama-2-70b-hf,meta-llama/Llama-2-70b-hf,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -6835,7 +6835,7 @@ If this is a private repository, make sure to pass a token having permission to ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-sdpa,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,huggyllama/llama-13b,huggyllama/llama-13b,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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+4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciCoder-1b,Deci/DeciCoder-1b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -6878,7 +6878,7 @@ ChildProcessError: Traceback (most recent call last): AttributeError: 'DeciCoderAttention' object has no attribute '_init_rope' ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,llama,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,google/recurrentgemma-2b,google/recurrentgemma-2b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,google/recurrentgemma-2b,google/recurrentgemma-2b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -6984,7 +6984,7 @@ If this is a private repository, make 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7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-7B,Qwen/Qwen-7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in 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+4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-2.7B,EleutherAI/gpt-neo-2.7B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7056,7 +7056,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: GPTNeoForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,gpt_neo,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7161,7 +7161,7 @@ OSError: 0 is not a local folder and is not a valid model identifier listed on ' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-4.5B,facebook/xglm-4.5B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-4.5B,facebook/xglm-4.5B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7197,7 +7197,7 @@ ValueError: XGLMForCausalLM does not support an attention implementation through ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-sdpa,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,TencentARC/Mistral_Pro_8B_v0.1,TencentARC/Mistral_Pro_8B_v0.1,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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0.37287628173828125, 0.37280767822265626, 0.37277081298828124, 0.3730196533203125, 0.37287628173828125, 0.37285784912109377, 0.3729295349121094, 0.3729520568847656]",tokens/s,2.639289530705313,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Salesforce/codegen-6B-nl,Salesforce/codegen-6B-nl,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Salesforce/codegen-6B-nl,Salesforce/codegen-6B-nl,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7232,7 +7232,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: CodeGenForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,codegen,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7267,7 +7267,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: OPTForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-110B,Qwen/Qwen1.5-110B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-110B,Qwen/Qwen1.5-110B,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7312,7 +7312,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 17.50 MiB is free. Process 39352 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 10.50 MiB is free. Process 38923 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-sdpa,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,B,B,cuda,0,42,,,True,True,True,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -7456,7 +7456,7 @@ If this is a private repository, make sure to pass a token having permission to 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7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Salesforce/codegen-16B-nl,Salesforce/codegen-16B-nl,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7491,7 +7491,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: CodeGenForCausalLM does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=""eager""` meanwhile. Example: `model = AutoModel.from_pretrained(""openai/whisper-tiny"", attn_implementation=""eager"")` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,codegen,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-6.7b,facebook/opt-6.7b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-6.7b,facebook/opt-6.7b,cuda,0,42,,,True,,,True,,float16,True,False,,sdpa,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7630,7 +7630,7 @@ If this is a private repository, make sure to pass a 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+4bit-gptq-exllama-v2-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-72B,Qwen/Qwen1.5-72B,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7675,7 +7675,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 34173 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 33670 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-eager,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/pythia-1.4b,,cuda,0,42,,,,,True,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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+4bit-gptq-exllama-v2-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-72B,Qwen/Qwen-72B,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -7976,7 +7976,7 @@ If this is a private repository, make sure to pass a token 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memory. 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+4bit-gptq-exllama-v2-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen2-beta-72B,Qwen/Qwen2-beta-72B,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -8944,7 +8944,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 51187 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 50713 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-eager,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,meta-llama/Llama-2-70b-hf,meta-llama/Llama-2-70b-hf,cuda,0,42,,,True,True,True,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -9131,7 +9131,7 @@ If this is a private repository, make sure 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+4bit-gptq-exllama-v2-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -9329,7 +9329,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 75.50 MiB is free. Process 66445 has 22.11 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 32.08 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 68.50 MiB is free. Process 65103 has 22.11 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 32.08 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-eager,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,0,0,cuda,0,42,,,True,True,True,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -9406,7 +9406,7 @@ If this is a private repository, make sure to pass a token having permission to 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+4bit-gptq-exllama-v2-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-110B,Qwen/Qwen1.5-110B,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -9451,7 +9451,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 17.50 MiB is free. Process 38552 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 10.50 MiB is free. Process 38131 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v2-eager,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,B,B,cuda,0,42,,,True,True,True,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,2,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -9701,7 +9701,7 @@ If this is a private repository, make sure to pass a token having permission to 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+4bit-gptq-exllama-v1-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-72B,Qwen/Qwen1.5-72B,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -9746,7 +9746,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 33488 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 32929 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-eager,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/pythia-1.4b,,cuda,0,42,,,,,True,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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-4bit-gptq-exllama-v1-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,databricks/dbrx-base,databricks/dbrx-base,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,databricks/dbrx-base,databricks/dbrx-base,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -10970,7 +10970,7 @@ torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. 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+4bit-gptq-exllama-v1-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen2-beta-72B,Qwen/Qwen2-beta-72B,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -11015,7 +11015,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 50447 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 49973 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-eager,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,meta-llama/Llama-2-70b-hf,meta-llama/Llama-2-70b-hf,cuda,0,42,,,True,True,True,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -11202,7 +11202,7 @@ If this is a private repository, make sure 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+4bit-gptq-exllama-v1-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -11400,7 +11400,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 75.50 MiB is free. Process 65795 has 22.11 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 32.08 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 68.50 MiB is free. Process 64427 has 22.11 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 32.08 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-eager,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,0,0,cuda,0,42,,,True,True,True,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -11477,7 +11477,7 @@ If this is a private repository, make sure to pass a token having permission to 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+4bit-gptq-exllama-v1-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-110B,Qwen/Qwen1.5-110B,cuda,0,42,,,True,,,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -11522,7 +11522,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 17.50 MiB is free. Process 37677 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 10.50 MiB is free. Process 37232 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-eager,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,B,B,cuda,0,42,,,True,True,True,True,,float16,True,False,,eager,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -11772,7 +11772,7 @@ If this is a private repository, make sure to pass a token having permission to 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7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen1.5-72B,Qwen/Qwen1.5-72B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -11817,11 +11817,11 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 36225 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 35776 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/pythia-1.4b,,cuda,0,42,,,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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-4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-7.5B,facebook/xglm-7.5B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-7.5B,facebook/xglm-7.5B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -11853,7 +11853,7 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpuzhti6qz/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpjburfit5/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,huggyllama/llama-30b,huggyllama/llama-30b,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.289728,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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+4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-564M,facebook/xglm-564M,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -12071,7 +12071,7 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp3w3_2szr/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp3chc_9oh/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/gpt-neo-125m,,cuda,0,42,,,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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+4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-72B,Qwen/Qwen-72B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -12214,7 +12214,7 @@ ChildProcessError: Traceback (most recent call last): ValueError: FalconForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpxjmjhv59/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-14B,Qwen/Qwen-14B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen-14B,Qwen/Qwen-14B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File 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""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -12497,7 +12497,7 @@ torch.cuda.OutOfMemoryError: CUDA out of memory. 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-4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,databricks/dbrx-base,databricks/dbrx-base,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,databricks/dbrx-base,databricks/dbrx-base,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -13081,7 +13081,7 @@ torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. 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+4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Qwen/Qwen2-beta-72B,Qwen/Qwen2-beta-72B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -13126,7 +13126,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 63.50 MiB is free. Process 53335 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 56.50 MiB is free. Process 52897 has 22.12 GiB memory in use. Of the allocated memory 21.87 GiB is allocated by PyTorch, and 10.15 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,meta-llama/Llama-2-70b-hf,meta-llama/Llama-2-70b-hf,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -13313,7 +13313,7 @@ If this is a private repository, make sure to pass a token having permission to ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,huggyllama/llama-13b,huggyllama/llama-13b,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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-4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciCoder-1b,Deci/DeciCoder-1b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Deci/DeciCoder-1b,Deci/DeciCoder-1b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -13356,7 +13356,7 @@ ChildProcessError: Traceback (most recent call last): AttributeError: 'DeciCoderAttention' object has no attribute '_init_rope' ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,llama,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,google/recurrentgemma-2b,google/recurrentgemma-2b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,google/recurrentgemma-2b,google/recurrentgemma-2b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -13388,7 +13388,7 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: RecurrentGemmaForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpph_egh1z/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: RecurrentGemmaForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp3jshxvg5/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,recurrent_gemma,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,v,v,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -13462,7 +13462,7 @@ If this is a private repository, make sure to pass a token having permission to ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,EleutherAI/pythia-2.7b,,cuda,0,42,,,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -13500,7 +13500,7 @@ ImportError: This modeling file requires the following packages that were not fo 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,microsoft/rho-math-1b-v0.1,microsoft/rho-math-1b-v0.1,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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+4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-66b,facebook/opt-66b,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -13545,7 +13545,7 @@ ChildProcessError: Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 75.50 MiB is free. Process 67978 has 22.11 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 32.08 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 68.50 MiB is free. Process 66572 has 22.11 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 32.08 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,opt,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,0,0,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -13618,7 +13618,7 @@ OSError: 0 is not a local folder and is not a valid model identifier listed on ' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=` ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-4.5B,facebook/xglm-4.5B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/xglm-4.5B,facebook/xglm-4.5B,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -13650,11 +13650,11 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp6kkvbs9u/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: XGLMForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpadd5of5r/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,xglm,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,TencentARC/Mistral_Pro_8B_v0.1,TencentARC/Mistral_Pro_8B_v0.1,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: CodeGenForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpx2v0vskd/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: CodeGenForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpyfeakhuu/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,codegen,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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Traceback (most recent call last): self._buffers[key] = fn(buf) File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1160, in convert return t.to( -torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.19 GiB of which 17.50 MiB is free. Process 41083 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) +torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 10.50 MiB is free. Process 40606 has 22.17 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 19.39 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,qwen2,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.1+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,B,B,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.293824,Linux,x86_64,Linux-5.10.219-208.866.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.3.1,,4.42.4,,0.32.1,,,,1.21.2,,,,0.11.1,,"Traceback (most recent call last): @@ -13879,7 +13879,7 @@ If this is a private repository, make sure to pass a token having 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7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.0,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): +4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,Salesforce/codegen-16B-nl,Salesforce/codegen-16B-nl,cuda,0,42,,,True,,,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,False,spawn, AMD EPYC 7R32,16,66697.261056,Linux,x86_64,Linux-5.10.223-212.873.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.4.0,,4.44.2,,0.34.2,,,,1.21.4,,,,0.12.0,,"Traceback (most recent call last): File ""/workspace/llm_perf/update_llm_perf_cuda_pytorch.py"", line 148, in benchmark_cuda_pytorch benchmark_report = Benchmark.launch(benchmark_config) File ""/workspace/optimum_benchmark/benchmark/base.py"", line 47, in launch @@ -13911,7 +13911,7 @@ ChildProcessError: Traceback (most recent call last): cls._check_and_enable_flash_attn_2( File ""/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py"", line 1647, in _check_and_enable_flash_attn_2 raise ValueError( -ValueError: CodeGenForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmp4r_jebju/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new +ValueError: CodeGenForCausalLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co//tmp/tmpyazfjjua/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,codegen,,,,,,,,,,,,,,,,,,,,,,, 4bit-gptq-exllama-v1-flash_attention_2,pytorch,2.3.0+cu121,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,facebook/opt-6.7b,facebook/opt-6.7b,cuda,0,42,,,True,True,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,gptq,4,True,1,256,False,,inference,optimum_benchmark.scenarios.inference.scenario.InferenceScenario,10,10,10,1,2,256,,True,True,True,64,64,process,optimum_benchmark.launchers.process.launcher.ProcessLauncher,True,kill,,spawn, AMD EPYC 7R32,16,66697.29792,Linux,x86_64,Linux-5.10.215-203.850.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA 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