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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 3 new columns ({'prefill', 'decode', '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 9d560f3886e4a5c62e7abcd2e5bcebf24d256d2f)
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 ({'prefill', 'decode', '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 9d560f3886e4a5c62e7abcd2e5bcebf24d256d2f)
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
},
... | {
"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
... |
{
"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
},
... | {
"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
... |
{
"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
},
... | {
"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
},... |
{
"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
},
"m... | {
"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
}... |
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