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perf-df-bnb-1xA10.csv

@@ -5376,7 +5376,7 @@ ChildProcessError: Traceback (most recent call last):
     w_4bit, quant_state = bnb.functional.quantize_4bit(
   File ""/usr/local/lib/python3.10/dist-packages/bitsandbytes/functional.py"", line 1196, in quantize_4bit
     out = torch.zeros(((n + 1) // mod, 1), dtype=quant_storage, device=A.device)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 416.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 22.50 MiB is free. Process 24609 has 22.16 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 41.40 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 416.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 22.50 MiB is free. Process 24828 has 22.16 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 41.40 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)
 
 ",,,,,
 8bit-bnb-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-405B,meta-llama/Llama-3.1-405B,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,bnb,0.0,True,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-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Traceback (most recent call last):
@@ -5432,7 +5432,7 @@ ChildProcessError: Traceback (most recent call last):
     w_4bit, quant_state = bnb.functional.quantize_4bit(
   File ""/usr/local/lib/python3.10/dist-packages/bitsandbytes/functional.py"", line 1196, in quantize_4bit
     out = torch.zeros(((n + 1) // mod, 1), dtype=quant_storage, device=A.device)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 416.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 22.50 MiB is free. Process 26762 has 22.16 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 41.40 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 416.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 22.50 MiB is free. Process 27024 has 22.16 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 41.40 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)
 
 ",,,,,
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@@ -5494,7 +5494,7 @@ ChildProcessError: Traceback (most recent call last):
     w_4bit, quant_state = bnb.functional.quantize_4bit(
   File ""/usr/local/lib/python3.10/dist-packages/bitsandbytes/functional.py"", line 1196, in quantize_4bit
     out = torch.zeros(((n + 1) // mod, 1), dtype=quant_storage, device=A.device)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 416.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 22.50 MiB is free. Process 22569 has 22.16 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 41.40 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 416.00 MiB. GPU 0 has a total capacity of 22.18 GiB of which 22.50 MiB is free. Process 22688 has 22.16 GiB memory in use. Of the allocated memory 21.83 GiB is allocated by PyTorch, and 41.40 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)
 
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@@ -9250,7 +9250,7 @@ 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 1688, in _check_and_enable_flash_attn_2
     raise ValueError(
-ValueError: BloomForCausalLM 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/tmpqwin1efw/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new
+ValueError: BloomForCausalLM 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/tmplclp5l26/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new
 
 ",,,,,
 8bit-bnb-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,bloom,bigscience/bloomz-560m,bigscience/bloomz-560m,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,bnb,0.0,True,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-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['NVIDIA A10G'],1,24146608128,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Traceback (most recent call last):
@@ -9285,7 +9285,7 @@ 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 1688, in _check_and_enable_flash_attn_2
     raise ValueError(
-ValueError: BloomForCausalLM 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/tmp9zra44ll/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new
+ValueError: BloomForCausalLM 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/tmp0ezktujl/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new
 
 ",,,,,
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