diff --git "a/perf-df-unquantized-1xT4.csv" "b/perf-df-unquantized-1xT4.csv"
--- "a/perf-df-unquantized-1xT4.csv"
+++ "b/perf-df-unquantized-1xT4.csv"
@@ -507,7 +507,7 @@ bfloat16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.Py
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-bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gpt2,distilbert/distilgpt2,distilbert/distilgpt2,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gpt2,distilbert/distilgpt2,distilbert/distilgpt2,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -529,9 +529,9 @@ ChildProcessError: Traceback (most recent call last):
     return self.pretrained_model.generate(**inputs, **kwargs)
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py"", line 116, in decorate_context
     return func(*args, **kwargs)
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2048, in generate
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2047, in generate
     result = self._sample(
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3008, in _sample
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3007, in _sample
     outputs = self(**model_inputs, return_dict=True)
   File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1553, in _wrapped_call_impl
     return self._call_impl(*args, **kwargs)
@@ -571,7 +571,7 @@ RuntimeError: FlashAttention only supports Ampere GPUs or newer.
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
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+float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gpt2,distilbert/distilgpt2,distilbert/distilgpt2,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -593,9 +593,9 @@ ChildProcessError: Traceback (most recent call last):
     return self.pretrained_model.generate(**inputs, **kwargs)
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py"", line 116, in decorate_context
     return func(*args, **kwargs)
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2048, in generate
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2047, in generate
     result = self._sample(
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3008, in _sample
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3007, in _sample
     outputs = self(**model_inputs, return_dict=True)
   File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1553, in _wrapped_call_impl
     return self._call_impl(*args, **kwargs)
@@ -2992,7 +2992,7 @@ ValueError: RecurrentGemmaForCausalLM does not support an attention implementati
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
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-bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gemma2,google/gemma-2-2b,google/gemma-2-2b,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gemma2,google/gemma-2-2b,google/gemma-2-2b,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -3014,9 +3014,9 @@ ChildProcessError: Traceback (most recent call last):
     return self.pretrained_model.generate(**inputs, **kwargs)
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py"", line 116, in decorate_context
     return func(*args, **kwargs)
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2048, in generate
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2047, in generate
     result = self._sample(
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3008, in _sample
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3007, in _sample
     outputs = self(**model_inputs, return_dict=True)
   File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1553, in _wrapped_call_impl
     return self._call_impl(*args, **kwargs)
@@ -3124,7 +3124,7 @@ ChildProcessError: Traceback (most recent call last):
 ValueError: RecurrentGemmaForCausalLM 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"")`
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gemma2,google/gemma-2-2b,google/gemma-2-2b,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gemma2,google/gemma-2-2b,google/gemma-2-2b,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -3146,9 +3146,9 @@ ChildProcessError: Traceback (most recent call last):
     return self.pretrained_model.generate(**inputs, **kwargs)
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py"", line 116, in decorate_context
     return func(*args, **kwargs)
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2048, in generate
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2047, in generate
     result = self._sample(
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3008, in _sample
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3007, in _sample
     outputs = self(**model_inputs, return_dict=True)
   File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1553, in _wrapped_call_impl
     return self._call_impl(*args, **kwargs)
@@ -10183,7 +10183,7 @@ ChildProcessError: Traceback (most recent call last):
 RuntimeError: FlashAttention only supports Ampere GPUs or newer.
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float32-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,float32,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float32-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,float32,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -11114,7 +11114,7 @@ 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"")`
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-bfloat16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,bfloat16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,bfloat16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -11573,7 +11573,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 50.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 8.12 MiB is free. Process 400267 has 14.73 GiB memory in use. Of the allocated memory 14.61 GiB is allocated by PyTorch, and 3.97 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,float16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,float16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -12093,7 +12093,7 @@ ChildProcessError: Traceback (most recent call last):
 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/tmp733kqmbw/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -12115,9 +12115,9 @@ ChildProcessError: Traceback (most recent call last):
     return self.pretrained_model.generate(**inputs, **kwargs)
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py"", line 116, in decorate_context
     return func(*args, **kwargs)
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2048, in generate
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2047, in generate
     result = self._sample(
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3008, in _sample
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3007, in _sample
     outputs = self(**model_inputs, return_dict=True)
   File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1553, in _wrapped_call_impl
     return self._call_impl(*args, **kwargs)
@@ -12392,7 +12392,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 162.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 120.12 MiB is free. Process 408206 has 14.62 GiB memory in use. Of the allocated memory 14.51 GiB is allocated by PyTorch, and 2.29 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,opt,facebook/opt-125m,facebook/opt-125m,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -12414,9 +12414,9 @@ ChildProcessError: Traceback (most recent call last):
     return self.pretrained_model.generate(**inputs, **kwargs)
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py"", line 116, in decorate_context
     return func(*args, **kwargs)
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2048, in generate
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2047, in generate
     result = self._sample(
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3008, in _sample
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3007, in _sample
     outputs = self(**model_inputs, return_dict=True)
   File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1553, in _wrapped_call_impl
     return self._call_impl(*args, **kwargs)
@@ -17490,7 +17490,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 896.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 598.12 MiB is free. Process 504428 has 14.15 GiB memory in use. Of the allocated memory 14.04 GiB is allocated by PyTorch, and 1.81 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float32-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float32,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float32-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float32,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -17530,7 +17530,7 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 224.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 106.12 MiB is free. Process 27077 has 14.63 GiB memory in use. Of the allocated memory 14.52 GiB is allocated by PyTorch, and 1.52 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 224.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 106.12 MiB is free. Process 27185 has 14.63 GiB memory in use. Of the allocated memory 14.52 GiB is allocated by PyTorch, and 1.52 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Meta-Llama-3-8B,meta-llama/Meta-Llama-3-8B,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.224-212.876.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.4.0,,4.44.2,,0.34.2,,,,1.22.0,,,,0.12.0,,"Traceback (most recent call last):
@@ -17865,7 +17865,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.62 GiB. GPU 0 has a total capacity of 14.74 GiB of which 470.12 MiB is free. Process 34685 has 14.28 GiB memory in use. Of the allocated memory 14.16 GiB is allocated by PyTorch, and 1.94 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float16-eager,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,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-eager,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,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -17905,7 +17905,7 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.62 GiB. GPU 0 has a total capacity of 14.74 GiB of which 470.12 MiB is free. Process 32804 has 14.28 GiB memory in use. Of the allocated memory 14.16 GiB is allocated by PyTorch, and 1.94 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 1.62 GiB. GPU 0 has a total capacity of 14.74 GiB of which 470.12 MiB is free. Process 32833 has 14.28 GiB memory in use. Of the allocated memory 14.16 GiB is allocated by PyTorch, and 1.94 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 float16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Meta-Llama-3-70B,meta-llama/Meta-Llama-3-70B,cuda,0,42,,,True,True,,float16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.224-212.876.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.4.0,,4.44.2,,0.34.2,,,,1.22.0,,,,0.12.0,,"Traceback (most recent call last):
@@ -18057,7 +18057,7 @@ ChildProcessError: Traceback (most recent call last):
 RuntimeError: FlashAttention only supports Ampere GPUs or newer.
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-bfloat16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,bfloat16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,bfloat16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -18089,7 +18089,7 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 28107 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 28188 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Meta-Llama-3-8B-Instruct,meta-llama/Meta-Llama-3-8B-Instruct,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
@@ -18326,7 +18326,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 896.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 342.12 MiB is free. Process 498393 has 14.40 GiB memory in use. Of the allocated memory 14.29 GiB is allocated by PyTorch, and 1.75 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -18358,7 +18358,7 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 29094 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 29069 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 bfloat16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-2-7b-hf,meta-llama/Llama-2-7b-hf,cuda,0,42,,,True,True,,bfloat16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.224-212.876.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla 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@@ -18604,7 +18604,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 37037 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float32-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float32,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float32-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float32,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -18644,7 +18644,7 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 224.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 106.12 MiB is free. Process 25672 has 14.63 GiB memory in use. Of the allocated memory 14.52 GiB is allocated by PyTorch, and 1.52 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 224.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 106.12 MiB is free. Process 25816 has 14.63 GiB memory in use. Of the allocated memory 14.52 GiB is allocated by PyTorch, and 1.52 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 bfloat16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-2-13b-hf,meta-llama/Llama-2-13b-hf,cuda,0,42,,,True,True,,bfloat16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.224-212.876.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.4.0,,4.44.2,,0.34.2,,,,1.22.0,,,,0.12.0,,"Traceback (most recent call last):
@@ -18690,7 +18690,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 50.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 18.12 MiB is free. Process 496038 has 14.72 GiB memory in use. Of the allocated memory 14.60 GiB is allocated by PyTorch, and 3.02 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -18722,7 +18722,7 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 28627 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 28611 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 float16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Meta-Llama-3-8B-Instruct,meta-llama/Meta-Llama-3-8B-Instruct,cuda,0,42,,,True,True,,float16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
@@ -18838,7 +18838,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 44272 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -18870,10 +18870,10 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 26191 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 26306 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,float16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -18905,10 +18905,10 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 27636 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 27710 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float32-eager,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,,float32,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float32-eager,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,,float32,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -18948,7 +18948,7 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 3.25 GiB. GPU 0 has a total capacity of 14.74 GiB of which 1.42 GiB is free. Process 32319 has 13.32 GiB memory in use. Of the allocated memory 13.20 GiB is allocated by PyTorch, and 2.00 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 3.25 GiB. GPU 0 has a total capacity of 14.74 GiB of which 1.42 GiB is free. Process 32290 has 13.32 GiB memory in use. Of the allocated memory 13.20 GiB is allocated by PyTorch, and 2.00 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 float16-sdpa,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-2-7b-hf,meta-llama/Llama-2-7b-hf,cuda,0,42,,,True,True,,float16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.224-212.876.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla 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@@ -19202,7 +19202,7 @@ ChildProcessError: Traceback (most recent call last):
 torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 3.25 GiB. GPU 0 has a total capacity of 14.74 GiB of which 1.42 GiB is free. Process 33754 has 13.32 GiB memory in use. Of the allocated memory 13.20 GiB is allocated by PyTorch, and 2.00 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-bfloat16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,bfloat16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-8B-Instruct,cuda,0,42,,,True,True,,bfloat16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -19234,7 +19234,7 @@ ChildProcessError: Traceback (most recent call last):
     self.weight = Parameter(torch.empty((out_features, in_features), **factory_kwargs))
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_device.py"", line 79, in __torch_function__
     return func(*args, **kwargs)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 26633 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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 1002.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 532.12 MiB is free. Process 26752 has 14.22 GiB memory in use. Of the allocated memory 13.98 GiB is allocated by PyTorch, and 129.48 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,llama,meta-llama/Llama-2-7b-hf,meta-llama/Llama-2-7b-hf,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.224-212.876.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.4.0,,4.44.2,,0.34.2,,,,1.22.0,,,,0.12.0,,"Traceback (most recent call last):
@@ -29652,7 +29652,7 @@ torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 50.00 MiB. GPU 0 h
 float16-eager,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gpt2,openai-community/gpt2,openai-community/gpt2,cuda,0,42,,,True,True,,float16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.224-212.876.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla 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-float16-sdpa,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,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-sdpa,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,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -29685,7 +29685,7 @@ ChildProcessError: Traceback (most recent call last):
 ValueError: BloomForCausalLM 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"")`
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float32-sdpa,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,,float32,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float32-sdpa,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,,float32,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -29718,7 +29718,7 @@ ChildProcessError: Traceback (most recent call last):
 ValueError: BloomForCausalLM 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"")`
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-float16-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,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+float16-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,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -29748,10 +29748,10 @@ 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/tmp57k283vf/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/tmp4ly39q4p/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-bfloat16-sdpa,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,,bfloat16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-sdpa,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,,bfloat16,True,False,,sdpa,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -29785,7 +29785,7 @@ ValueError: BloomForCausalLM does not support an attention implementation throug
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
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-bfloat16-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,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-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,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -29815,7 +29815,7 @@ 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/tmp779fqudr/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/tmpyzqt5fff/no_weights_model/discussions/new or in the Transformers GitHub repo: https://github.com/huggingface/transformers/issues/new
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
 bfloat16-eager,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,,bfloat16,True,False,,eager,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla 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+float16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gpt2,openai-community/gpt2,openai-community/gpt2,cuda,0,42,,,True,True,,float16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -38625,9 +38625,9 @@ ChildProcessError: Traceback (most recent call last):
     return self.pretrained_model.generate(**inputs, **kwargs)
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py"", line 116, in decorate_context
     return func(*args, **kwargs)
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2048, in generate
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2047, in generate
     result = self._sample(
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3008, in _sample
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3007, in _sample
     outputs = self(**model_inputs, return_dict=True)
   File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1553, in _wrapped_call_impl
     return self._call_impl(*args, **kwargs)
@@ -38668,7 +38668,7 @@ RuntimeError: FlashAttention only supports Ampere GPUs or newer.
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
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-bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gpt2,openai-community/gpt2,openai-community/gpt2,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.1,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
+bfloat16-flash_attention_2,pytorch,2.4.1+cu124,optimum_benchmark.backends.pytorch.backend.PyTorchBackend,text-generation,transformers,gpt2,openai-community/gpt2,openai-community/gpt2,cuda,0,42,,,True,True,,bfloat16,True,False,,flash_attention_2,,False,,False,forward,,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, Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz,8,33163.759616,Linux,x86_64,Linux-5.10.225-213.878.amzn2.x86_64-x86_64-with-glibc2.35,x86_64,3.10.12,['Tesla T4'],1,16106127360,0.5.0,,4.45.2,,0.34.2,,,,1.22.0,,,,0.13.0,,"Traceback (most recent call last):
   File ""/workspace/src/common/benchmark_runner.py"", line 118, in execute_and_log_benchmark
     benchmark_report = Benchmark.launch(benchmark_config)
   File ""/usr/local/lib/python3.10/dist-packages/optimum_benchmark/benchmark/base.py"", line 47, in launch
@@ -38690,9 +38690,9 @@ ChildProcessError: Traceback (most recent call last):
     return self.pretrained_model.generate(**inputs, **kwargs)
   File ""/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py"", line 116, in decorate_context
     return func(*args, **kwargs)
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2048, in generate
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 2047, in generate
     result = self._sample(
-  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3008, in _sample
+  File ""/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py"", line 3007, in _sample
     outputs = self(**model_inputs, return_dict=True)
   File ""/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py"", line 1553, in _wrapped_call_impl
     return self._call_impl(*args, **kwargs)