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	/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
	warnings.warn(
	Downloading readme: 0%\| \| 0.00/271 [00:00<?, ?B/s] Downloading readme: 100%\|██████████\| 271/271 [00:00<00:00, 1.92MB/s]


	Downloading data: 0%\| \| 0.00/453k [00:00<?, ?B/s][A[A

	Downloading data: 100%\|██████████\| 453k/453k [00:00<00:00, 2.17MB/s][A[A Downloading data: 100%\|██████████\| 453k/453k [00:00<00:00, 2.17MB/s]
	Generating train split: 0%\| \| 0/1000 [00:00<?, ? examples/s] Generating train split: 100%\|██████████\| 1000/1000 [00:00<00:00, 213624.53 examples/s]
	[codecarbon INFO @ 19:58:06] [setup] RAM Tracking...
	[codecarbon INFO @ 19:58:06] [setup] GPU Tracking...
	[codecarbon INFO @ 19:58:06] Tracking Nvidia GPU via pynvml
	[codecarbon DEBUG @ 19:58:06] GPU available. Starting setup
	[codecarbon INFO @ 19:58:06] [setup] CPU Tracking...
	[codecarbon DEBUG @ 19:58:06] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
	[codecarbon DEBUG @ 19:58:06] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
	[codecarbon DEBUG @ 19:58:06] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
	[codecarbon WARNING @ 19:58:06] No CPU tracking mode found. Falling back on CPU constant mode.
	[codecarbon WARNING @ 19:58:07] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
	[codecarbon INFO @ 19:58:07] CPU Model on constant consumption mode: AMD EPYC 7R32
	[codecarbon INFO @ 19:58:07] >>> Tracker's metadata:
	[codecarbon INFO @ 19:58:07] Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
	[codecarbon INFO @ 19:58:07] Python version: 3.9.20
	[codecarbon INFO @ 19:58:07] CodeCarbon version: 2.5.1
	[codecarbon INFO @ 19:58:07] Available RAM : 186.705 GB
	[codecarbon INFO @ 19:58:07] CPU count: 48
	[codecarbon INFO @ 19:58:07] CPU model: AMD EPYC 7R32
	[codecarbon INFO @ 19:58:07] GPU count: 1
	[codecarbon INFO @ 19:58:07] GPU model: 1 x NVIDIA A10G
	[codecarbon DEBUG @ 19:58:08] Not running on AWS
	[codecarbon DEBUG @ 19:58:09] Not running on Azure
	[codecarbon DEBUG @ 19:58:10] Not running on GCP
	[codecarbon INFO @ 19:58:10] Saving emissions data to file /runs/codecarbon.csv
	[codecarbon DEBUG @ 19:58:10] EmissionsData(timestamp='2024-10-07T19:58:10', project_name='codecarbon', run_id='2d39c1fa-c60c-4a42-ae21-7478b6ecb362', duration=0.0021433930087368935, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
	Filter: 0%\| \| 0/1000 [00:00<?, ? examples/s] Filter: 100%\|██████████\| 1000/1000 [00:00<00:00, 159321.74 examples/s]
	Running tokenizer on dataset: 0%\| \| 0/1000 [00:00<?, ? examples/s] Running tokenizer on dataset: 100%\|██████████\| 1000/1000 [00:00<00:00, 2713.82 examples/s] Running tokenizer on dataset: 100%\|██████████\| 1000/1000 [00:00<00:00, 2691.36 examples/s]
	[codecarbon INFO @ 19:58:11] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.27332639694213867 W
	[codecarbon DEBUG @ 19:58:11] RAM : 0.27 W during 0.40 s [measurement time: 0.0006]
	[codecarbon INFO @ 19:58:11] Energy consumed for all GPUs : 0.000008 kWh. Total GPU Power : 67.79598290555053 W
	[codecarbon DEBUG @ 19:58:11] GPU : 67.80 W during 0.41 s [measurement time: 0.0022]
	[codecarbon INFO @ 19:58:11] Energy consumed for all CPUs : 0.000005 kWh. Total CPU Power : 42.5 W
	[codecarbon DEBUG @ 19:58:11] CPU : 42.50 W during 0.41 s [measurement time: 0.0000]
	[codecarbon INFO @ 19:58:11] 0.000012 kWh of electricity used since the beginning.
	[codecarbon DEBUG @ 19:58:11] last_duration=0.4047611999849323
	------------------------
	[codecarbon DEBUG @ 19:58:11] EmissionsData(timestamp='2024-10-07T19:58:11', project_name='codecarbon', run_id='2d39c1fa-c60c-4a42-ae21-7478b6ecb362', duration=0.4079224629967939, emissions=4.6080039089515136e-06, emissions_rate=1.129627399064741e-05, cpu_power=42.5, gpu_power=67.79598290555053, ram_power=0.27332639694213867, cpu_energy=4.814476511859943e-06, gpu_energy=7.638061666259688e-06, ram_energy=3.073128944384957e-08, energy_consumed=1.248326946756348e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
	[codecarbon DEBUG @ 19:58:11] EmissionsData(timestamp='2024-10-07T19:58:11', project_name='codecarbon', run_id='2d39c1fa-c60c-4a42-ae21-7478b6ecb362', duration=0.0022866150247864425, emissions=4.6080039089515136e-06, emissions_rate=0.0020152075705799563, cpu_power=42.5, gpu_power=67.79598290555053, ram_power=0.27332639694213867, cpu_energy=4.814476511859943e-06, gpu_energy=7.638061666259688e-06, ram_energy=3.073128944384957e-08, energy_consumed=1.248326946756348e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
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	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [97,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [98,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [99,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [100,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [101,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [102,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [103,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [104,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [105,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [106,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [107,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [108,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [109,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
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	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [521,0,0], thread: [28,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [521,0,0], thread: [29,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [521,0,0], thread: [30,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [521,0,0], thread: [31,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
	2%\|▏ \| 22/1000 [00:00<00:07, 122.27it/s]
	Error executing job with overrides: ['backend.model=cardiffnlp/twitter-roberta-base-sentiment-latest', 'backend.processor=cardiffnlp/twitter-roberta-base-sentiment-latest']
	Traceback (most recent call last):
	File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
	benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
	File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
	raise error
	File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
	report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
	File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
	while not process_context.join():
	File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
	raise ProcessRaisedException(msg, error_index, failed_process.pid)
	torch.multiprocessing.spawn.ProcessRaisedException:

	-- Process 0 terminated with the following error:
	Traceback (most recent call last):
	File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
	fn(i, *args)
	File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
	worker_output = worker(*worker_args)
	File "/optimum-benchmark/optimum_benchmark/experiment.py", line 62, in run
	benchmark.run(backend)
	File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 178, in run
	self.run_inference_energy_tracking(backend)
	File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 262, in run_inference_energy_tracking
	inputs = backend.prepare_inputs(inputs)
	File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 338, in prepare_inputs
	inputs[key] = value.to(self.config.device)
	RuntimeError: CUDA error: device-side assert triggered
	CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
	For debugging consider passing CUDA_LAUNCH_BLOCKING=1
	Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.



	Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.