IlyasMoutawwakil's picture
Upload cuda_inference_transformers_token-classification_microsoft/deberta-v3-base/benchmark.json with huggingface_hub
c07173f verified
raw
history blame
7.89 kB
{
"config": {
"name": "cuda_inference_transformers_token-classification_microsoft/deberta-v3-base",
"backend": {
"name": "pytorch",
"version": "2.2.2+rocm5.7",
"_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
"task": "token-classification",
"library": "transformers",
"model": "microsoft/deberta-v3-base",
"processor": "microsoft/deberta-v3-base",
"device": "cuda",
"device_ids": "0",
"seed": 42,
"inter_op_num_threads": null,
"intra_op_num_threads": null,
"model_kwargs": {},
"processor_kwargs": {},
"hub_kwargs": {},
"no_weights": true,
"device_map": null,
"torch_dtype": null,
"eval_mode": true,
"to_bettertransformer": false,
"low_cpu_mem_usage": null,
"attn_implementation": null,
"cache_implementation": null,
"autocast_enabled": false,
"autocast_dtype": null,
"torch_compile": false,
"torch_compile_target": "forward",
"torch_compile_config": {},
"quantization_scheme": null,
"quantization_config": {},
"deepspeed_inference": false,
"deepspeed_inference_config": {},
"peft_type": null,
"peft_config": {}
},
"scenario": {
"name": "inference",
"_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario",
"iterations": 1,
"duration": 1,
"warmup_runs": 1,
"input_shapes": {
"batch_size": 1,
"num_choices": 2,
"sequence_length": 2
},
"new_tokens": null,
"latency": true,
"memory": true,
"energy": false,
"forward_kwargs": {},
"generate_kwargs": {
"max_new_tokens": 2,
"min_new_tokens": 2
},
"call_kwargs": {
"num_inference_steps": 2
}
},
"launcher": {
"name": "process",
"_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
"device_isolation": true,
"device_isolation_action": "error",
"start_method": "spawn"
},
"environment": {
"cpu": " AMD EPYC 7763 64-Core Processor",
"cpu_count": 128,
"cpu_ram_mb": 1082015.236096,
"system": "Linux",
"machine": "x86_64",
"platform": "Linux-5.15.0-84-generic-x86_64-with-glibc2.35",
"processor": "x86_64",
"python_version": "3.10.12",
"gpu": [
"Advanced Micro Devices, Inc. [AMD/ATI]"
],
"gpu_count": 1,
"gpu_vram_mb": 68702699520,
"optimum_benchmark_version": "0.2.1",
"optimum_benchmark_commit": "48414f58841d7ba7c7fd42d74fd524d1d23c3081",
"transformers_version": "4.40.2",
"transformers_commit": null,
"accelerate_version": "0.30.1",
"accelerate_commit": null,
"diffusers_version": "0.27.2",
"diffusers_commit": null,
"optimum_version": null,
"optimum_commit": null,
"timm_version": "1.0.3",
"timm_commit": null,
"peft_version": null,
"peft_commit": null
}
},
"report": {
"forward": {
"memory": {
"unit": "MB",
"max_ram": 1026.895872,
"max_global_vram": 2103.242752,
"max_process_vram": 260912.68096,
"max_reserved": 773.849088,
"max_allocated": 745.087488
},
"latency": {
"unit": "s",
"count": 78,
"total": 0.9987952957153322,
"mean": 0.012805067893786309,
"stdev": 0.0005555674611556774,
"p50": 0.012673464298248291,
"p90": 0.013242840957641602,
"p95": 0.013540809154510497,
"p99": 0.014645286273956308,
"values": [
0.012653303146362305,
0.01337874412536621,
0.01296594524383545,
0.013183704376220703,
0.013331544876098634,
0.013227865219116211,
0.01310146427154541,
0.012972023963928223,
0.013099063873291015,
0.012851384162902832,
0.012796664237976074,
0.012686102867126466,
0.012828344345092774,
0.012702584266662598,
0.012806743621826171,
0.012668984413146973,
0.012834423065185547,
0.012924504280090333,
0.013049304008483887,
0.012895064353942871,
0.013060824394226074,
0.012977624893188476,
0.012997464179992676,
0.016378589630126953,
0.012775544166564942,
0.012396503448486328,
0.01246994400024414,
0.012372022628784179,
0.012487222671508789,
0.012641142845153809,
0.012998584747314454,
0.01303170394897461,
0.01245538330078125,
0.01255506420135498,
0.012684983253479004,
0.012379222869873047,
0.012480342864990234,
0.01257938289642334,
0.012338422775268554,
0.01255234432220459,
0.012391222953796386,
0.012402583122253417,
0.012579063415527343,
0.012396822929382325,
0.01252578353881836,
0.012563702583312988,
0.012402902603149414,
0.012408343315124512,
0.012662103652954101,
0.012434423446655274,
0.012383703231811524,
0.012682264328002929,
0.012512022972106934,
0.012505462646484375,
0.012488022804260254,
0.012525782585144044,
0.01270978355407715,
0.012404183387756347,
0.012443543434143067,
0.012409462928771972,
0.012408502578735351,
0.012698904037475586,
0.01267794418334961,
0.014127546310424805,
0.013101304054260254,
0.013213305473327637,
0.013515705108642579,
0.014078105926513672,
0.013683065414428711,
0.013179864883422852,
0.01327778434753418,
0.012447862625122071,
0.01268802261352539,
0.012443222999572755,
0.012431862831115723,
0.012423221588134765,
0.012484983444213867,
0.012512823104858399
]
},
"throughput": {
"unit": "samples/s",
"value": 78.09408027311221
},
"energy": null,
"efficiency": null
}
}
}