Dataset Preview
Full Screen
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 }
README.md exists but content is empty. Use the Edit dataset card button to edit it.
Downloads last month
97

Space using AIEnergyScore/results_debug 1