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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 2 new columns ({'config.backend.half', 'config.backend.reshape'}) and 95 missing columns ({'report.decode.energy.total', 'report.decode.latency.unit', 'report.load.memory.max_process_vram', 'config.backend.auto_calibration', 'report.prefill.memory.max_reserved', 'report.per_token.latency.p95', 'report.load.energy', 'report.decode.efficiency.unit', 'report.per_token.energy', 'report.load.memory.max_global_vram', 'report.prefill.latency.p95', 'report.prefill.latency.stdev', 'report.prefill.throughput.value', 'report.decode.latency.values', 'report.decode.energy.ram', 'report.load.latency.count', 'report.decode.latency.p95', 'report.prefill.latency.stdev_', 'report.load.latency.values', 'report.load.latency.p99', 'report.per_token.latency.stdev_', 'report.decode.latency.count', 'report.load.latency.unit', 'report.decode.memory.unit', 'report.decode.latency.stdev', 'report.decode.throughput.value', 'report.per_token.latency.count', 'report.load.latency.p95', 'report.load.latency.p90', 'report.decode.energy.cpu', 'report.per_token.throughput.value', 'report.prefill.energy.unit', 'report.per_token.latency.p50', 'report.decode.energy.gpu', 'report.per_token.efficiency', 'report.load.efficiency', 'report.per_token.latency.p90', 'report.prefill.latency.unit', 'report.load.throughput', 'report.per_token.latency.p99', 'report.decode.memory.max_reserved', 'report.load.latency.stdev_', 'report.prefill.latency.p99', 'report.decode.latency.stdev_', 'report.load.latency.mean', 'report.load.memory.max_allocated', 'report.decode.energy.unit', 'report.prefill.energy.gpu', 'report.pr
...
'report.per_token.memory', 'report.load.latency.stdev', 'config.backend.optimization', 'report.load.memory.max_reserved', 'report.prefill.memory.max_ram', 'report.prefill.latency.values', 'report.per_token.throughput.unit', 'report.prefill.memory.unit', 'report.prefill.energy.total', 'report.prefill.latency.p50', 'report.prefill.efficiency.value', 'report.per_token.latency.total', 'report.prefill.memory.max_process_vram', 'report.prefill.latency.mean', 'report.prefill.memory.max_allocated', 'report.prefill.latency.total', 'report.per_token.latency.unit', 'report.decode.memory.max_global_vram', 'config.backend.use_io_binding', 'report.prefill.energy.ram', 'report.decode.latency.mean', 'report.load.latency.total', 'report.decode.throughput.unit', 'report.decode.latency.p50', 'report.decode.latency.p99', 'report.prefill.memory.max_global_vram', 'report.load.memory.max_ram', 'report.decode.latency.p90', 'report.prefill.latency.p90', 'report.decode.latency.total', 'config.backend.torch_dtype', 'config.backend.auto_quantization', 'report.prefill.throughput.unit', 'report.per_token.latency.stdev', 'report.load.latency.p50', 'report.load.memory.unit', 'report.decode.efficiency.value', 'report.prefill.efficiency.unit', 'report.decode.memory.max_ram', 'config.backend.auto_optimization', 'report.per_token.latency.mean', 'config.backend.provider', 'report.decode.memory.max_allocated', 'report.decode.memory.max_process_vram', 'report.prefill.energy.cpu', 'report.per_token.latency.values'}).

This happened while the csv dataset builder was generating data using

hf://datasets/optimum-benchmark/llm-perf-leaderboard/data/perf-df-openvino-cpu-unquantized-32vCPU-C7i.csv (at revision 94a9713e1842c87029a1dcc829e0003533a6d275)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              config.name: string
              config.backend.name: string
              config.backend.version: string
              config.backend._target_: string
              config.backend.task: string
              config.backend.library: string
              config.backend.model_type: string
              config.backend.model: string
              config.backend.processor: string
              config.backend.device: string
              config.backend.device_ids: int64
              config.backend.seed: int64
              config.backend.inter_op_num_threads: double
              config.backend.intra_op_num_threads: double
              config.backend.model_kwargs.trust_remote_code: bool
              config.backend.no_weights: bool
              config.backend.export: bool
              config.backend.use_cache: bool
              config.backend.use_merged: bool
              config.backend.half: bool
              config.backend.reshape: bool
              config.backend.quantization: bool
              config.backend.calibration: bool
              config.scenario.name: string
              config.scenario._target_: string
              config.scenario.iterations: int64
              config.scenario.duration: int64
              config.scenario.warmup_runs: int64
              config.scenario.input_shapes.batch_size: int64
              config.scenario.input_shapes.num_choices: double
              config.scenario.input_shapes.sequence_length: int64
              config.scenario.new_tokens: double
              config.scenario.memory: bool
              config.scenario.latency: bool
              config.scenario.energy: bool
              config.scenario.generate_kwargs.max_new_tokens: int64
              config.scenario.generate_kwargs.min_new_tokens: int64
              config.launcher.name: string
              config.launcher._target_: string
              config.launcher.device_isolation: bool
              config.launcher.device_isolation_action: double
              config.launcher.numactl: bool
              config.launcher.start_method: string
              config.environment.cpu: string
              config.environment.cpu_count: int64
              config.environment.cpu_ram_mb: double
              config.environment.system: string
              config.environment.machine: string
              config.environment.platform: string
              config.environment.processor: string
              config.environment.python_version: string
              config.environment.optimum_benchmark_version: string
              config.environment.optimum_benchmark_commit: double
              config.environment.transformers_version: string
              config.environment.transformers_commit: double
              config.environment.accelerate_version: string
              config.environment.accelerate_commit: double
              config.environment.diffusers_version: double
              config.environment.diffusers_commit: double
              config.environment.optimum_version: string
              config.environment.optimum_commit: double
              config.environment.timm_version: double
              config.environment.timm_commit: double
              config.environment.peft_version: double
              config.environment.peft_commit: double
              config.print_report: bool
              config.log_report: bool
              report.traceback: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 10798
              to
              {'config.name': Value(dtype='string', id=None), 'config.backend.name': Value(dtype='string', id=None), 'config.backend.version': Value(dtype='string', id=None), 'config.backend._target_': Value(dtype='string', id=None), 'config.backend.task': Value(dtype='string', id=None), 'config.backend.library': Value(dtype='string', id=None), 'config.backend.model_type': Value(dtype='string', id=None), 'config.backend.model': Value(dtype='string', id=None), 'config.backend.processor': Value(dtype='string', id=None), 'config.backend.device': Value(dtype='string', id=None), 'config.backend.device_ids': Value(dtype='int64', id=None), 'config.backend.seed': Value(dtype='int64', id=None), 'config.backend.inter_op_num_threads': Value(dtype='float64', id=None), 'config.backend.intra_op_num_threads': Value(dtype='float64', id=None), 'config.backend.model_kwargs.trust_remote_code': Value(dtype='bool', id=None), 'config.backend.no_weights': Value(dtype='bool', id=None), 'config.backend.export': Value(dtype='bool', id=None), 'config.backend.use_cache': Value(dtype='bool', id=None), 'config.backend.use_merged': Value(dtype='bool', id=None), 'config.backend.torch_dtype': Value(dtype='string', id=None), 'config.backend.provider': Value(dtype='string', id=None), 'config.backend.use_io_binding': Value(dtype='bool', id=None), 'config.backend.auto_optimization': Value(dtype='float64', id=None), 'config.backend.auto_quantization': Value(dtype='float64', id=None), 'config.backend.auto_calibration': Value(dt
              ...
              ', id=None), 'report.decode.energy.unit': Value(dtype='string', id=None), 'report.decode.energy.cpu': Value(dtype='float64', id=None), 'report.decode.energy.ram': Value(dtype='float64', id=None), 'report.decode.energy.gpu': Value(dtype='float64', id=None), 'report.decode.energy.total': Value(dtype='float64', id=None), 'report.decode.efficiency.unit': Value(dtype='string', id=None), 'report.decode.efficiency.value': Value(dtype='float64', id=None), 'report.per_token.memory': Value(dtype='float64', id=None), 'report.per_token.latency.unit': Value(dtype='string', id=None), 'report.per_token.latency.values': Value(dtype='string', id=None), 'report.per_token.latency.count': Value(dtype='float64', id=None), 'report.per_token.latency.total': Value(dtype='float64', id=None), 'report.per_token.latency.mean': Value(dtype='float64', id=None), 'report.per_token.latency.p50': Value(dtype='float64', id=None), 'report.per_token.latency.p90': Value(dtype='float64', id=None), 'report.per_token.latency.p95': Value(dtype='float64', id=None), 'report.per_token.latency.p99': Value(dtype='float64', id=None), 'report.per_token.latency.stdev': Value(dtype='float64', id=None), 'report.per_token.latency.stdev_': Value(dtype='float64', id=None), 'report.per_token.throughput.unit': Value(dtype='string', id=None), 'report.per_token.throughput.value': Value(dtype='float64', id=None), 'report.per_token.energy': Value(dtype='float64', id=None), 'report.per_token.efficiency': Value(dtype='float64', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 2 new columns ({'config.backend.half', 'config.backend.reshape'}) and 95 missing columns ({'report.decode.energy.total', 'report.decode.latency.unit', 'report.load.memory.max_process_vram', 'config.backend.auto_calibration', 'report.prefill.memory.max_reserved', 'report.per_token.latency.p95', 'report.load.energy', 'report.decode.efficiency.unit', 'report.per_token.energy', 'report.load.memory.max_global_vram', 'report.prefill.latency.p95', 'report.prefill.latency.stdev', 'report.prefill.throughput.value', 'report.decode.latency.values', 'report.decode.energy.ram', 'report.load.latency.count', 'report.decode.latency.p95', 'report.prefill.latency.stdev_', 'report.load.latency.values', 'report.load.latency.p99', 'report.per_token.latency.stdev_', 'report.decode.latency.count', 'report.load.latency.unit', 'report.decode.memory.unit', 'report.decode.latency.stdev', 'report.decode.throughput.value', 'report.per_token.latency.count', 'report.load.latency.p95', 'report.load.latency.p90', 'report.decode.energy.cpu', 'report.per_token.throughput.value', 'report.prefill.energy.unit', 'report.per_token.latency.p50', 'report.decode.energy.gpu', 'report.per_token.efficiency', 'report.load.efficiency', 'report.per_token.latency.p90', 'report.prefill.latency.unit', 'report.load.throughput', 'report.per_token.latency.p99', 'report.decode.memory.max_reserved', 'report.load.latency.stdev_', 'report.prefill.latency.p99', 'report.decode.latency.stdev_', 'report.load.latency.mean', 'report.load.memory.max_allocated', 'report.decode.energy.unit', 'report.prefill.energy.gpu', 'report.pr
              ...
              'report.per_token.memory', 'report.load.latency.stdev', 'config.backend.optimization', 'report.load.memory.max_reserved', 'report.prefill.memory.max_ram', 'report.prefill.latency.values', 'report.per_token.throughput.unit', 'report.prefill.memory.unit', 'report.prefill.energy.total', 'report.prefill.latency.p50', 'report.prefill.efficiency.value', 'report.per_token.latency.total', 'report.prefill.memory.max_process_vram', 'report.prefill.latency.mean', 'report.prefill.memory.max_allocated', 'report.prefill.latency.total', 'report.per_token.latency.unit', 'report.decode.memory.max_global_vram', 'config.backend.use_io_binding', 'report.prefill.energy.ram', 'report.decode.latency.mean', 'report.load.latency.total', 'report.decode.throughput.unit', 'report.decode.latency.p50', 'report.decode.latency.p99', 'report.prefill.memory.max_global_vram', 'report.load.memory.max_ram', 'report.decode.latency.p90', 'report.prefill.latency.p90', 'report.decode.latency.total', 'config.backend.torch_dtype', 'config.backend.auto_quantization', 'report.prefill.throughput.unit', 'report.per_token.latency.stdev', 'report.load.latency.p50', 'report.load.memory.unit', 'report.decode.efficiency.value', 'report.prefill.efficiency.unit', 'report.decode.memory.max_ram', 'config.backend.auto_optimization', 'report.per_token.latency.mean', 'config.backend.provider', 'report.decode.memory.max_allocated', 'report.decode.memory.max_process_vram', 'report.prefill.energy.cpu', 'report.per_token.latency.values'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/optimum-benchmark/llm-perf-leaderboard/data/perf-df-openvino-cpu-unquantized-32vCPU-C7i.csv (at revision 94a9713e1842c87029a1dcc829e0003533a6d275)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

config.name
string
config.backend.name
string
config.backend.version
string
config.backend._target_
string
config.backend.task
string
config.backend.library
string
config.backend.model_type
string
config.backend.model
string
config.backend.processor
string
config.backend.device
string
config.backend.device_ids
int64
config.backend.seed
int64
config.backend.inter_op_num_threads
null
config.backend.intra_op_num_threads
null
config.backend.model_kwargs.trust_remote_code
bool
config.backend.no_weights
bool
config.backend.export
bool
config.backend.use_cache
bool
config.backend.use_merged
bool
config.backend.torch_dtype
string
config.backend.provider
string
config.backend.use_io_binding
bool
config.backend.auto_optimization
null
config.backend.auto_quantization
null
config.backend.auto_calibration
null
config.backend.optimization
bool
config.backend.quantization
bool
config.backend.calibration
bool
config.scenario.name
string
config.scenario._target_
string
config.scenario.iterations
int64
config.scenario.duration
int64
config.scenario.warmup_runs
int64
config.scenario.input_shapes.batch_size
int64
config.scenario.input_shapes.num_choices
int64
config.scenario.input_shapes.sequence_length
int64
config.scenario.new_tokens
null
config.scenario.memory
bool
config.scenario.latency
bool
config.scenario.energy
bool
config.scenario.generate_kwargs.max_new_tokens
int64
config.scenario.generate_kwargs.min_new_tokens
int64
config.launcher.name
string
config.launcher._target_
string
config.launcher.device_isolation
bool
config.launcher.device_isolation_action
null
config.launcher.numactl
bool
config.launcher.start_method
string
config.environment.cpu
string
config.environment.cpu_count
int64
config.environment.cpu_ram_mb
float64
config.environment.system
string
config.environment.machine
string
config.environment.platform
string
config.environment.processor
string
config.environment.python_version
string
config.environment.optimum_benchmark_version
string
config.environment.optimum_benchmark_commit
string
config.environment.transformers_version
string
config.environment.transformers_commit
null
config.environment.accelerate_version
string
config.environment.accelerate_commit
null
config.environment.diffusers_version
null
config.environment.diffusers_commit
null
config.environment.optimum_version
string
config.environment.optimum_commit
null
config.environment.timm_version
null
config.environment.timm_commit
null
config.environment.peft_version
null
config.environment.peft_commit
null
config.print_report
bool
config.log_report
bool
report.traceback
string
report.load.memory.unit
null
report.load.memory.max_ram
null
report.load.memory.max_global_vram
null
report.load.memory.max_process_vram
null
report.load.memory.max_reserved
null
report.load.memory.max_allocated
null
report.load.latency.unit
null
report.load.latency.values
null
report.load.latency.count
null
report.load.latency.total
null
report.load.latency.mean
null
report.load.latency.p50
null
report.load.latency.p90
null
report.load.latency.p95
null
report.load.latency.p99
null
report.load.latency.stdev
null
report.load.latency.stdev_
null
report.load.throughput
null
report.load.energy
null
report.load.efficiency
null
report.prefill.memory.unit
null
report.prefill.memory.max_ram
null
report.prefill.memory.max_global_vram
null
report.prefill.memory.max_process_vram
null
report.prefill.memory.max_reserved
null
report.prefill.memory.max_allocated
null
report.prefill.latency.unit
null
report.prefill.latency.values
null
report.prefill.latency.count
null
report.prefill.latency.total
null
report.prefill.latency.mean
null
report.prefill.latency.p50
null
report.prefill.latency.p90
null
report.prefill.latency.p95
null
report.prefill.latency.p99
null
report.prefill.latency.stdev
null
report.prefill.latency.stdev_
null
report.prefill.throughput.unit
null
report.prefill.throughput.value
null
report.prefill.energy.unit
null
report.prefill.energy.cpu
null
report.prefill.energy.ram
null
report.prefill.energy.gpu
null
report.prefill.energy.total
null
report.prefill.efficiency.unit
null
report.prefill.efficiency.value
null
report.decode.memory.unit
null
report.decode.memory.max_ram
null
report.decode.memory.max_global_vram
null
report.decode.memory.max_process_vram
null
report.decode.memory.max_reserved
null
report.decode.memory.max_allocated
null
report.decode.latency.unit
null
report.decode.latency.values
null
report.decode.latency.count
null
report.decode.latency.total
null
report.decode.latency.mean
null
report.decode.latency.p50
null
report.decode.latency.p90
null
report.decode.latency.p95
null
report.decode.latency.p99
null
report.decode.latency.stdev
null
report.decode.latency.stdev_
null
report.decode.throughput.unit
null
report.decode.throughput.value
null
report.decode.energy.unit
null
report.decode.energy.cpu
null
report.decode.energy.ram
null
report.decode.energy.gpu
null
report.decode.energy.total
null
report.decode.efficiency.unit
null
report.decode.efficiency.value
null
report.per_token.memory
null
report.per_token.latency.unit
null
report.per_token.latency.values
null
report.per_token.latency.count
null
report.per_token.latency.total
null
report.per_token.latency.mean
null
report.per_token.latency.p50
null
report.per_token.latency.p90
null
report.per_token.latency.p95
null
report.per_token.latency.p99
null
report.per_token.latency.stdev
null
report.per_token.latency.stdev_
null
report.per_token.throughput.unit
null
report.per_token.throughput.value
null
report.per_token.energy
null
report.per_token.efficiency
null
float32-sdpa-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B
meta-llama/Meta-Llama-3-8B
cpu
0
42
null
null
true
true
true
true
false
float32
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float16-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-8B-Instruct
meta-llama/Llama-3.1-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
float16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
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null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float32-sdpa-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B-Instruct
meta-llama/Meta-Llama-3-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
float32
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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bfloat16-sdpa-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-405B
meta-llama/Llama-3.1-405B
cpu
0
42
null
null
true
true
true
true
false
bfloat16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 57, in launch raise RuntimeError(f"Isolated process exited with non-zero code {isolated_process.exitcode}") RuntimeError: Isolated process exited with non-zero code -9
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null
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null
bfloat16-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B-Instruct
meta-llama/Meta-Llama-3-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
bfloat16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float32-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-405B
meta-llama/Llama-3.1-405B
cpu
0
42
null
null
true
true
true
true
false
float32
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
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null
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null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 57, in launch raise RuntimeError(f"Isolated process exited with non-zero code {isolated_process.exitcode}") RuntimeError: Isolated process exited with non-zero code -9
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float16-sdpa-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B-Instruct
meta-llama/Meta-Llama-3-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
float16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float16-sdpa-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B
meta-llama/Meta-Llama-3-8B
cpu
0
42
null
null
true
true
true
true
false
float16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float16-sdpa-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-8B-Instruct
meta-llama/Llama-3.1-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
float16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float16-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B-Instruct
meta-llama/Meta-Llama-3-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
float16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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null
float32-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B-Instruct
meta-llama/Meta-Llama-3-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
float32
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
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false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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bfloat16-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-8B-Instruct
meta-llama/Llama-3.1-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
bfloat16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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bfloat16-sdpa-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-8B-Instruct
meta-llama/Llama-3.1-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
bfloat16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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bfloat16-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-405B
meta-llama/Llama-3.1-405B
cpu
0
42
null
null
true
true
true
true
false
bfloat16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 57, in launch raise RuntimeError(f"Isolated process exited with non-zero code {isolated_process.exitcode}") RuntimeError: Isolated process exited with non-zero code -9
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null
float32-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B
meta-llama/Meta-Llama-3-8B
cpu
0
42
null
null
true
true
true
true
false
float32
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float32-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-8B-Instruct
meta-llama/Llama-3.1-8B-Instruct
cpu
0
42
null
null
true
true
true
true
false
float32
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
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null
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null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float16-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B
meta-llama/Meta-Llama-3-8B
cpu
0
42
null
null
true
true
true
true
false
float16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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float32-sdpa-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Llama-3.1-405B
meta-llama/Llama-3.1-405B
cpu
0
42
null
null
true
true
true
true
false
float32
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 57, in launch raise RuntimeError(f"Isolated process exited with non-zero code {isolated_process.exitcode}") RuntimeError: Isolated process exited with non-zero code -9
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null
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null
bfloat16-eager-onnxruntime
onnxruntime
ort:1.19.2
optimum_benchmark.backends.onnxruntime.backend.ORTBackend
text-generation
transformers
llama
meta-llama/Meta-Llama-3-8B
meta-llama/Meta-Llama-3-8B
cpu
0
42
null
null
true
true
true
true
false
bfloat16
CPUExecutionProvider
true
null
null
null
false
false
false
inference
optimum_benchmark.scenarios.inference.scenario.InferenceScenario
10
10
10
1
2
256
null
true
true
true
64
64
process
optimum_benchmark.launchers.process.launcher.ProcessLauncher
false
null
false
spawn
Intel(R) Xeon(R) Platinum 8488C
32
66,326.188032
Linux
x86_64
Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.35
x86_64
3.10.12
0.5.0.dev0
08c9f59440cf4e5a5d6711ec19e8329ab2de652d
4.45.2
null
1.0.1
null
null
null
1.23.2
null
null
null
null
null
false
true
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 "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 51, in launch report = launcher.launch(worker=Benchmark.run, worker_args=[config]) File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 66, in launch raise ChildProcessError(response["traceback"]) ChildProcessError: Traceback (most recent call last): File "/workspace/src/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 103, in target report = worker(*worker_args) File "/workspace/src/optimum-benchmark/optimum_benchmark/benchmark/base.py", line 78, in run report = scenario.run(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 89, in run self.run_model_loading_tracking(backend) File "/workspace/src/optimum-benchmark/optimum_benchmark/scenarios/inference/scenario.py", line 168, in run_model_loading_tracking backend.load() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 86, in load self.load_ortmodel_with_no_weights() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 133, in load_ortmodel_with_no_weights self.load_ortmodel_from_pretrained() File "/workspace/src/optimum-benchmark/optimum_benchmark/backends/onnxruntime/backend.py", line 118, in load_ortmodel_from_pretrained self.pretrained_model = self.ort_model_loader.from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_ort.py", line 737, in from_pretrained return super().from_pretrained( File "/usr/local/lib/python3.10/dist-packages/optimum/modeling_base.py", line 438, in from_pretrained return from_pretrained_method( File "/usr/local/lib/python3.10/dist-packages/optimum/onnxruntime/modeling_decoder.py", line 653, in _from_transformers main_export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/__main__.py", line 373, in main_export onnx_export_from_model( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 1193, in onnx_export_from_model _, onnx_outputs = export_models( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 783, in export_models export( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 888, in export export_output = export_pytorch( File "/usr/local/lib/python3.10/dist-packages/optimum/exporters/onnx/convert.py", line 584, in export_pytorch onnx_export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/__init__.py", line 375, in export export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 502, in export _export( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1564, in _export graph, params_dict, torch_out = _model_to_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 1117, in _model_to_graph graph = _optimize_graph( File "/usr/local/lib/python3.10/dist-packages/torch/onnx/utils.py", line 663, in _optimize_graph _C._jit_pass_onnx_graph_shape_type_inference( RuntimeError: The serialized model is larger than the 2GiB limit imposed by the protobuf library. Therefore the output file must be a file path, so that the ONNX external data can be written to the same directory. Please specify the output file name.
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