The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 3 new columns ({'decode', 'prefill', 'per_token'}) and 1 missing columns ({'forward'}). This happened while the json dataset builder was generating data using hf://datasets/AIEnergyScore/results_debug/text_generation/distilbert/distilgpt2/benchmark_report.json (at revision b5ac8f8eb1c28abba4b8d3f5d172ad89598d521e) 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 prefill: struct<memory: null, latency: null, throughput: null, energy: struct<unit: string, cpu: double, ram: double, gpu: double, total: double>, efficiency: struct<unit: string, value: double>, measures: list<item: struct<unit: string, cpu: double, ram: double, gpu: double, total: double>>> child 0, memory: null child 1, latency: null child 2, throughput: null child 3, energy: struct<unit: string, cpu: double, ram: double, gpu: double, total: double> child 0, unit: string child 1, cpu: double child 2, ram: double child 3, gpu: double child 4, total: double child 4, efficiency: struct<unit: string, value: double> child 0, unit: string child 1, value: double child 5, measures: list<item: struct<unit: string, cpu: double, ram: double, gpu: double, total: double>> child 0, item: struct<unit: string, cpu: double, ram: double, gpu: double, total: double> child 0, unit: string child 1, cpu: double child 2, ram: double child 3, gpu: double child 4, total: double decode: struct<memory: null, latency: null, throughput: null, energy: struct<unit: string, cpu: double, ram: double, gpu: double, total: double>, efficiency: struct<unit: string, value: double>, measures: list<item: struct<unit: string, cpu: double, ram: double, gpu: double, total: double>>> child 0, memory: null child 1, latency: null child 2, throughput: null child 3, energy: struct<unit: string, cpu: doub ... ouble child 2, ram: double child 3, gpu: double child 4, total: double child 4, efficiency: struct<unit: string, value: double> child 0, unit: string child 1, value: double child 5, measures: list<item: struct<unit: string, cpu: double, ram: double, gpu: double, total: double>> child 0, item: struct<unit: string, cpu: double, ram: double, gpu: double, total: double> child 0, unit: string child 1, cpu: double child 2, ram: double child 3, gpu: double child 4, total: double per_token: struct<memory: null, latency: null, throughput: null, energy: null, efficiency: null, measures: null> child 0, memory: null child 1, latency: null child 2, throughput: null child 3, energy: null child 4, efficiency: null child 5, measures: null preprocess: struct<memory: null, latency: null, throughput: null, energy: struct<unit: string, cpu: double, ram: double, gpu: double, total: double>, efficiency: struct<unit: string, value: double>, measures: null> child 0, memory: null child 1, latency: null child 2, throughput: null child 3, energy: struct<unit: string, cpu: double, ram: double, gpu: double, total: double> child 0, unit: string child 1, cpu: double child 2, ram: double child 3, gpu: double child 4, total: double child 4, efficiency: struct<unit: string, value: double> child 0, unit: string child 1, value: double child 5, measures: null to {'forward': {'memory': Value(dtype='null', id=None), 'latency': Value(dtype='null', id=None), 'throughput': Value(dtype='null', id=None), 'energy': {'unit': Value(dtype='string', id=None), 'cpu': Value(dtype='float64', id=None), 'ram': Value(dtype='float64', id=None), 'gpu': Value(dtype='float64', id=None), 'total': Value(dtype='float64', id=None)}, 'efficiency': {'unit': Value(dtype='string', id=None), 'value': Value(dtype='float64', id=None)}, 'measures': [{'unit': Value(dtype='string', id=None), 'cpu': Value(dtype='float64', id=None), 'ram': Value(dtype='float64', id=None), 'gpu': Value(dtype='float64', id=None), 'total': Value(dtype='float64', id=None)}]}, 'preprocess': {'memory': Value(dtype='null', id=None), 'latency': Value(dtype='null', id=None), 'throughput': Value(dtype='null', id=None), 'energy': {'unit': Value(dtype='string', id=None), 'cpu': Value(dtype='float64', id=None), 'ram': Value(dtype='float64', id=None), 'gpu': Value(dtype='float64', id=None), 'total': Value(dtype='float64', id=None)}, 'efficiency': {'unit': Value(dtype='string', id=None), 'value': Value(dtype='float64', id=None)}, 'measures': Value(dtype='null', 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 3 new columns ({'decode', 'prefill', 'per_token'}) and 1 missing columns ({'forward'}). This happened while the json dataset builder was generating data using hf://datasets/AIEnergyScore/results_debug/text_generation/distilbert/distilgpt2/benchmark_report.json (at revision b5ac8f8eb1c28abba4b8d3f5d172ad89598d521e) 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.
forward
dict | preprocess
dict |
---|---|
{
"memory": null,
"latency": null,
"throughput": null,
"energy": {
"unit": "kWh",
"cpu": 0.00006839747347951036,
"ram": 5.716461813904849e-7,
"gpu": 0.000382609833865466,
"total": 0.00045157895352636676
},
"efficiency": {
"unit": "samples/kWh",
"value": 2214452.1842548894
},
"measures": [
{
"unit": "kWh",
"cpu": 0.00007601991918499052,
"ram": 6.350748954336861e-7,
"gpu": 0.00042098005900470525,
"total": 0.0004976350530851295
},
{
"unit": "kWh",
"cpu": 0.00007583578112349237,
"ram": 6.33827477982181e-7,
"gpu": 0.0004204228363402507,
"total": 0.0004968924449417253
},
{
"unit": "kWh",
"cpu": 0.00007556888686105799,
"ram": 6.316784804254393e-7,
"gpu": 0.00042907617659437847,
"total": 0.0005052767419358617
},
{
"unit": "kWh",
"cpu": 0.00007576498450592533,
"ram": 6.333213018100752e-7,
"gpu": 0.0004229906161690167,
"total": 0.0004993889219767522
},
{
"unit": "kWh",
"cpu": 0.00007616183489016193,
"ram": 6.36331055219782e-7,
"gpu": 0.00042316006075004964,
"total": 0.0004999582266954311
},
{
"unit": "kWh",
"cpu": 0.00007604929099385723,
"ram": 6.357059671153966e-7,
"gpu": 0.00041981228029364104,
"total": 0.0004964972772546136
},
{
"unit": "kWh",
"cpu": 0,
"ram": 0,
"gpu": 0,
"total": 0
},
{
"unit": "kWh",
"cpu": 0.0000765197290076079,
"ram": 6.394718976904407e-7,
"gpu": 0.00042124783699826196,
"total": 0.0004984070379035598
},
{
"unit": "kWh",
"cpu": 0.0000753602428510122,
"ram": 6.299462761465285e-7,
"gpu": 0.0004321947901999579,
"total": 0.000508184979327116
},
{
"unit": "kWh",
"cpu": 0.00007669406537699818,
"ram": 6.411044620813194e-7,
"gpu": 0.0004362136823043983,
"total": 0.0005135488521434781
}
]
} | {
"memory": null,
"latency": null,
"throughput": null,
"energy": {
"unit": "kWh",
"cpu": 0.0000062763785492279575,
"ram": 4.131239601138592e-8,
"gpu": 0.00001020028593679001,
"total": 0.000016517976882029355
},
"efficiency": {
"unit": "samples/kWh",
"value": 60540101.680850804
},
"measures": null
} |
{
"memory": null,
"latency": null,
"throughput": null,
"energy": {
"unit": "kWh",
"cpu": 0.00004243539444782477,
"ram": 3.4324948022090887e-7,
"gpu": 0.00017660489128377144,
"total": 0.00021938353521181714
},
"efficiency": {
"unit": "samples/kWh",
"value": 4558227.21169339
},
"measures": [
{
"unit": "kWh",
"cpu": 0.000047222357336391315,
"ram": 3.8155070117616626e-7,
"gpu": 0.00019075626371556353,
"total": 0.00023836017175313102
},
{
"unit": "kWh",
"cpu": 0.00004749673211893726,
"ram": 3.8421861573893824e-7,
"gpu": 0.0001927887653425664,
"total": 0.00024066971607724258
},
{
"unit": "kWh",
"cpu": 0.00004727033817184242,
"ram": 3.824102089456082e-7,
"gpu": 0.00019460265568183033,
"total": 0.00024225540406261836
},
{
"unit": "kWh",
"cpu": 0.00004696179368572,
"ram": 3.7991487817287554e-7,
"gpu": 0.000195100711636087,
"total": 0.00024244242019998
},
{
"unit": "kWh",
"cpu": 0.00004711608263912947,
"ram": 3.811678262399994e-7,
"gpu": 0.00019722265777799564,
"total": 0.0002447199082433651
},
{
"unit": "kWh",
"cpu": 0.00004749006321977099,
"ram": 3.84198376740525e-7,
"gpu": 0.0001978812694156673,
"total": 0.00024575553101217895
},
{
"unit": "kWh",
"cpu": 0,
"ram": 0,
"gpu": 0,
"total": 0
},
{
"unit": "kWh",
"cpu": 0.00004676308327078812,
"ram": 3.783082290670676e-7,
"gpu": 0.00020036432695791362,
"total": 0.00024750571845776905
},
{
"unit": "kWh",
"cpu": 0.000047063339466775565,
"ram": 3.8074053523091197e-7,
"gpu": 0.00020111793867227945,
"total": 0.00024856201867428556
},
{
"unit": "kWh",
"cpu": 0.000046970154568892536,
"ram": 3.799854308969965e-7,
"gpu": 0.0001962143236378111,
"total": 0.00024356446363760047
}
]
} | {
"memory": null,
"latency": null,
"throughput": null,
"energy": {
"unit": "kWh",
"cpu": 0.000005021590097264077,
"ram": 3.2065012868845376e-8,
"gpu": 0.000008134450951935435,
"total": 0.000013188106062068357
},
"efficiency": {
"unit": "samples/kWh",
"value": 75825899.13165781
},
"measures": null
} |
{
"memory": null,
"latency": null,
"throughput": null,
"energy": {
"unit": "kWh",
"cpu": 0.000042217974067077905,
"ram": 3.4266514207536644e-7,
"gpu": 0.00016691743908938683,
"total": 0.0002094780782985401
},
"efficiency": {
"unit": "samples/kWh",
"value": 4773769.208321829
},
"measures": [
{
"unit": "kWh",
"cpu": 0.00004712305867267585,
"ram": 3.8216822757675777e-7,
"gpu": 0.0001815407007876857,
"total": 0.0002290459276879383
},
{
"unit": "kWh",
"cpu": 0.00004649759695045457,
"ram": 3.7759060137763195e-7,
"gpu": 0.00017852986504651724,
"total": 0.00022540505259834942
},
{
"unit": "kWh",
"cpu": 0.00004660298317394335,
"ram": 3.7828696183161236e-7,
"gpu": 0.00018714348304760264,
"total": 0.00023412475318337764
},
{
"unit": "kWh",
"cpu": 0.00004666898457540407,
"ram": 3.788229137558605e-7,
"gpu": 0.0001820537567538416,
"total": 0.0002291015642430016
},
{
"unit": "kWh",
"cpu": 0.00004666899602715502,
"ram": 3.786127892940303e-7,
"gpu": 0.00018817042831420494,
"total": 0.00023521803713065406
},
{
"unit": "kWh",
"cpu": 0.0000471413553121238,
"ram": 3.8257066211415975e-7,
"gpu": 0.00018559625958802783,
"total": 0.0002331201855622657
},
{
"unit": "kWh",
"cpu": 0,
"ram": 0,
"gpu": 0,
"total": 0
},
{
"unit": "kWh",
"cpu": 0.00004720459533531942,
"ram": 3.8334632359225455e-7,
"gpu": 0.00018755015003968367,
"total": 0.0002351380916985953
},
{
"unit": "kWh",
"cpu": 0.000047043672874941777,
"ram": 3.820426281902338e-7,
"gpu": 0.0001894573737883931,
"total": 0.00023688308929152514
},
{
"unit": "kWh",
"cpu": 0.00004722849774876117,
"ram": 3.8321031302112333e-7,
"gpu": 0.00018913237352791157,
"total": 0.00023674408158969387
}
]
} | {
"memory": null,
"latency": null,
"throughput": null,
"energy": {
"unit": "kWh",
"cpu": 0.000004999329341282849,
"ram": 3.206474578014428e-8,
"gpu": 0.000009661952173889432,
"total": 0.000014693346260952426
},
"efficiency": {
"unit": "samples/kWh",
"value": 68058016.3456367
},
"measures": null
} |
{
"memory": null,
"latency": null,
"throughput": null,
"energy": {
"unit": "kWh",
"cpu": 0.00006158239596826162,
"ram": 5.070663343322509e-7,
"gpu": 0.0002979319883453971,
"total": 0.0003600214506479909
},
"efficiency": {
"unit": "samples/kWh",
"value": 2777612.27338019
},
"measures": [
{
"unit": "kWh",
"cpu": 0.00006822910836250017,
"ram": 5.613364414570755e-7,
"gpu": 0.0003167471978419989,
"total": 0.0003855376426459562
},
{
"unit": "kWh",
"cpu": 0.00006820300116735641,
"ram": 5.61543031495337e-7,
"gpu": 0.00032964804149598903,
"total": 0.00039841258569484083
},
{
"unit": "kWh",
"cpu": 0.0000678087703173579,
"ram": 5.583760945256067e-7,
"gpu": 0.00033585471312799764,
"total": 0.00040422185953988097
},
{
"unit": "kWh",
"cpu": 0.00006862520428957674,
"ram": 5.651467433811671e-7,
"gpu": 0.00033427304519600964,
"total": 0.00040346339622896756
},
{
"unit": "kWh",
"cpu": 0.0000681000235965213,
"ram": 5.608086534726602e-7,
"gpu": 0.0003381977705580047,
"total": 0.0004068586028079988
},
{
"unit": "kWh",
"cpu": 0.00006813676398471983,
"ram": 5.611252489269231e-7,
"gpu": 0.00032909554105398087,
"total": 0.0003977934302876276
},
{
"unit": "kWh",
"cpu": 0,
"ram": 0,
"gpu": 0,
"total": 0
},
{
"unit": "kWh",
"cpu": 0.00006892202110207616,
"ram": 5.675694510437125e-7,
"gpu": 0.00033062554227798746,
"total": 0.00040011513283110716
},
{
"unit": "kWh",
"cpu": 0.00006908210467153266,
"ram": 5.68854032743356e-7,
"gpu": 0.00033529832379400326,
"total": 0.00040494928249827904
},
{
"unit": "kWh",
"cpu": 0.00006871696219097503,
"ram": 5.659036462766713e-7,
"gpu": 0.0003295797081079993,
"total": 0.00039886257394525096
}
]
} | {
"memory": null,
"latency": null,
"throughput": null,
"energy": {
"unit": "kWh",
"cpu": 0.000005220544721525914,
"ram": 3.343040007944655e-8,
"gpu": 0.000007783617337997484,
"total": 0.000013037592459602845
},
"efficiency": {
"unit": "samples/kWh",
"value": 76701277.71661167
},
"measures": null
} |