xuzhuo0417/openacm-gnn-8bit
Tabular Regression • Updated • 33
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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 32 new columns ({'0', '0.7', '0.15', '0.1875', '0.8', '0.0625', '0.10', '0.24', '0.18', '0.5625', '0.13', '0.9', '0.25', '0.20', '0.1875.1', '0.16', '0.4', '0.12', '0.5', '0.3', '0.27', '0.17', '0.6', '0.11', '0.22', '0.19', '0.21', '0.14', '0.26', '0.2', '0.1', '0.23'}) and 20 missing columns ({'nmed', 'power_normalized', 'area', 'area_normalized', 'power', 'config_0', 'config_5', 'delay', 'delay_normalized', 'config_6', 'config_4', 'config_2', 'sample_id', 'config_3', 'mred', 'config_7', 'config_8', 'mred_normalized', 'config_1', 'nmed_normalized'}).
This happened while the csv dataset builder was generating data using
hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset/metadata/FEATURE.csv (at revision 4da9ea1a75b163ea2f230fd5d575deacaff26946), ['hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/data/configs_ppa.csv', 'hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/metadata/FEATURE.csv', 'hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/metadata/graph_edges.csv', 'hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/model/FEATURE.csv', 'hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/raw/Graph.csv']
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 "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
0.5625: double
0.1875: double
0.1875.1: double
0.0625: double
0: double
0.1: double
0.2: double
0.3: double
0.4: double
0.5: double
0.6: double
0.7: double
0.8: double
0.9: double
0.10: double
0.11: double
0.12: double
0.13: double
0.14: double
0.15: double
0.16: double
0.17: double
0.18: double
0.19: double
0.20: double
0.21: double
0.22: double
0.23: double
0.24: double
0.25: double
0.26: double
0.27: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3762
to
{'sample_id': Value('int64'), 'config_0': Value('int64'), 'config_1': Value('int64'), 'config_2': Value('int64'), 'config_3': Value('int64'), 'config_4': Value('int64'), 'config_5': Value('int64'), 'config_6': Value('int64'), 'config_7': Value('int64'), 'config_8': Value('int64'), 'mred_normalized': Value('float64'), 'nmed_normalized': Value('float64'), 'delay_normalized': Value('float64'), 'area_normalized': Value('float64'), 'power_normalized': Value('float64'), 'mred': Value('float64'), 'nmed': Value('float64'), 'delay': Value('float64'), 'area': Value('float64'), 'power': Value('float64')}
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 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
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 32 new columns ({'0', '0.7', '0.15', '0.1875', '0.8', '0.0625', '0.10', '0.24', '0.18', '0.5625', '0.13', '0.9', '0.25', '0.20', '0.1875.1', '0.16', '0.4', '0.12', '0.5', '0.3', '0.27', '0.17', '0.6', '0.11', '0.22', '0.19', '0.21', '0.14', '0.26', '0.2', '0.1', '0.23'}) and 20 missing columns ({'nmed', 'power_normalized', 'area', 'area_normalized', 'power', 'config_0', 'config_5', 'delay', 'delay_normalized', 'config_6', 'config_4', 'config_2', 'sample_id', 'config_3', 'mred', 'config_7', 'config_8', 'mred_normalized', 'config_1', 'nmed_normalized'}).
This happened while the csv dataset builder was generating data using
hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset/metadata/FEATURE.csv (at revision 4da9ea1a75b163ea2f230fd5d575deacaff26946), ['hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/data/configs_ppa.csv', 'hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/metadata/FEATURE.csv', 'hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/metadata/graph_edges.csv', 'hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/model/FEATURE.csv', 'hf://datasets/xuzhuo0417/openacm-gnn-8bit-dataset@4da9ea1a75b163ea2f230fd5d575deacaff26946/raw/Graph.csv']
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.
sample_id int64 | config_0 int64 | config_1 int64 | config_2 int64 | config_3 int64 | config_4 int64 | config_5 int64 | config_6 int64 | config_7 int64 | config_8 int64 | mred_normalized float64 | nmed_normalized float64 | delay_normalized float64 | area_normalized float64 | power_normalized float64 | mred float64 | nmed float64 | delay float64 | area float64 | power float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 2 | 2 | 1 | 6 | 7 | 0 | 6 | 5 | 3 | 0.352023 | 0.443003 | 1 | 0.489297 | 0.339148 | 0.057259 | 0.001438 | 1.31 | 460.4477 | 0.000147 |
1 | 7 | 2 | 7 | 2 | 1 | 4 | 1 | 4 | 1 | 0.429264 | 0.393559 | 1 | 0.517821 | 0.624483 | 0.069663 | 0.001288 | 1.31 | 461.8985 | 0.000157 |
2 | 5 | 2 | 0 | 1 | 3 | 5 | 0 | 5 | 2 | 0.094055 | 0.249326 | 1 | 0.57573 | 0.413365 | 0.015834 | 0.00085 | 1.31 | 464.8439 | 0.00015 |
3 | 1 | 0 | 0 | 1 | 4 | 6 | 3 | 5 | 4 | 0.112413 | 0.220633 | 1 | 0.611548 | 0.56919 | 0.018782 | 0.000763 | 1.31 | 466.6657 | 0.000155 |
4 | 3 | 2 | 0 | 4 | 5 | 3 | 2 | 1 | 0 | 0.108322 | 0.12004 | 1 | 0.615299 | 0.612064 | 0.018125 | 0.000458 | 1.31 | 466.8565 | 0.000156 |
5 | 7 | 5 | 0 | 3 | 5 | 0 | 6 | 5 | 1 | 0.451941 | 0.433707 | 1 | 0.431771 | 0.494678 | 0.073304 | 0.00141 | 1.31 | 457.5218 | 0.000152 |
6 | 5 | 0 | 5 | 2 | 1 | 3 | 6 | 3 | 3 | 0.501949 | 0.524899 | 1 | 0.428332 | 0.602011 | 0.081335 | 0.001686 | 1.31 | 457.3469 | 0.000156 |
7 | 1 | 2 | 3 | 4 | 7 | 3 | 5 | 1 | 0 | 0.404055 | 0.337564 | 1 | 0.478497 | 0.739208 | 0.065615 | 0.001118 | 1.31 | 459.8984 | 0.000161 |
8 | 5 | 3 | 3 | 3 | 2 | 4 | 1 | 5 | 1 | 0.808875 | 0.579393 | 1 | 0.406692 | 0.655825 | 0.130622 | 0.001852 | 1.31 | 456.2462 | 0.000158 |
9 | 7 | 2 | 5 | 1 | 7 | 6 | 1 | 3 | 7 | 0.560324 | 0.573404 | 1 | 0.294898 | 0.58013 | 0.090709 | 0.001833 | 1.31 | 450.5601 | 0.000155 |
10 | 3 | 4 | 3 | 4 | 3 | 6 | 2 | 6 | 2 | 0.432184 | 0.405736 | 1 | 0.428332 | 0.505027 | 0.070132 | 0.001325 | 1.31 | 457.3469 | 0.000153 |
11 | 5 | 1 | 5 | 1 | 7 | 2 | 3 | 7 | 2 | 0.281389 | 0.469728 | 1 | 0.370526 | 0.637493 | 0.045917 | 0.001519 | 1.31 | 454.4067 | 0.000157 |
12 | 0 | 0 | 1 | 7 | 4 | 4 | 1 | 3 | 1 | 0.482106 | 0.402687 | 1 | 0.622214 | 0.626257 | 0.078148 | 0.001315 | 1.31 | 467.2082 | 0.000157 |
13 | 3 | 2 | 3 | 4 | 7 | 7 | 3 | 0 | 2 | 0.461114 | 0.397181 | 1 | 0.377893 | 0.548196 | 0.074777 | 0.001299 | 1.31 | 454.7814 | 0.000154 |
14 | 0 | 5 | 1 | 4 | 7 | 1 | 0 | 4 | 3 | 0.338435 | 0.381737 | 1 | 0.553951 | 0.561502 | 0.055077 | 0.001252 | 1.31 | 463.7362 | 0.000155 |
15 | 3 | 0 | 7 | 4 | 2 | 6 | 6 | 1 | 2 | 0.416509 | 0.420854 | 1 | 0.528831 | 0.462153 | 0.067615 | 0.001371 | 1.31 | 462.4585 | 0.000151 |
16 | 7 | 1 | 0 | 2 | 1 | 3 | 5 | 7 | 5 | 0.287936 | 0.490549 | 1 | 0.406481 | 0.55618 | 0.046968 | 0.001582 | 1.31 | 456.2355 | 0.000154 |
17 | 7 | 6 | 5 | 5 | 1 | 0 | 2 | 4 | 6 | 0.206885 | 0.596997 | 1 | 0.460464 | 0.494973 | 0.033953 | 0.001905 | 1.31 | 458.9812 | 0.000152 |
18 | 3 | 2 | 5 | 5 | 2 | 4 | 7 | 2 | 1 | 0.214499 | 0.576473 | 1 | 0.442575 | 0.5411 | 0.035175 | 0.001843 | 1.31 | 458.0713 | 0.000154 |
19 | 1 | 0 | 1 | 5 | 2 | 3 | 7 | 3 | 1 | 0.275205 | 0.429267 | 1 | 0.507225 | 0.756653 | 0.044924 | 0.001396 | 1.31 | 461.3596 | 0.000161 |
20 | 1 | 6 | 7 | 6 | 7 | 1 | 4 | 3 | 1 | 0.490833 | 0.435019 | 1 | 0.39196 | 0.67327 | 0.07955 | 0.001414 | 1.31 | 455.4969 | 0.000158 |
21 | 1 | 1 | 5 | 1 | 2 | 5 | 6 | 1 | 4 | 0.097373 | 0.344282 | 1 | 0.56826 | 0.719397 | 0.016367 | 0.001138 | 1.31 | 464.464 | 0.00016 |
22 | 2 | 5 | 7 | 0 | 0 | 1 | 3 | 2 | 7 | 0.44442 | 0.560462 | 1 | 0.510837 | 0.492904 | 0.072097 | 0.001794 | 1.31 | 461.5433 | 0.000152 |
23 | 2 | 4 | 1 | 7 | 6 | 6 | 6 | 6 | 4 | 0.365168 | 0.377386 | 1 | 0.446011 | 0.371969 | 0.05937 | 0.001239 | 1.31 | 458.2461 | 0.000148 |
24 | 1 | 6 | 6 | 4 | 4 | 2 | 2 | 0 | 4 | 0.025924 | 0.172672 | 1 | 0.640309 | 0.428149 | 0.004893 | 0.000618 | 1.31 | 468.1286 | 0.00015 |
25 | 3 | 3 | 6 | 4 | 2 | 4 | 3 | 0 | 2 | 0.247614 | 0.321507 | 1 | 0.507469 | 0.544352 | 0.040493 | 0.001069 | 1.31 | 461.372 | 0.000154 |
26 | 3 | 0 | 7 | 7 | 2 | 6 | 5 | 0 | 4 | 0.755487 | 0.602522 | 1 | 0.438928 | 0.3767 | 0.122049 | 0.001922 | 1.31 | 457.8858 | 0.000148 |
27 | 6 | 2 | 0 | 4 | 1 | 7 | 7 | 5 | 0 | 0.132085 | 0.210598 | 1 | 0.507155 | 0.424009 | 0.021941 | 0.000733 | 1.31 | 461.356 | 0.00015 |
28 | 3 | 1 | 2 | 3 | 1 | 6 | 1 | 7 | 5 | 0.550314 | 0.639298 | 1 | 0.428089 | 0.650798 | 0.089101 | 0.002033 | 1.31 | 457.3345 | 0.000158 |
29 | 7 | 0 | 4 | 6 | 7 | 2 | 2 | 6 | 2 | 0.11971 | 0.28985 | 1 | 0.496418 | 0.299823 | 0.019954 | 0.000973 | 1.31 | 460.8099 | 0.000146 |
30 | 1 | 4 | 3 | 7 | 3 | 0 | 1 | 6 | 4 | 0.694863 | 0.526273 | 1 | 0.47485 | 0.684506 | 0.112313 | 0.00169 | 1.31 | 459.7129 | 0.000159 |
31 | 2 | 0 | 7 | 7 | 1 | 5 | 0 | 1 | 3 | 0.340818 | 0.435326 | 1 | 0.510768 | 0.540804 | 0.05546 | 0.001414 | 1.31 | 461.5398 | 0.000154 |
32 | 4 | 7 | 0 | 1 | 3 | 4 | 0 | 1 | 7 | 0.475831 | 0.408419 | 1 | 0.521505 | 0.573329 | 0.077141 | 0.001333 | 1.31 | 462.0859 | 0.000155 |
33 | 7 | 6 | 7 | 4 | 3 | 5 | 2 | 7 | 3 | 0.532535 | 0.497191 | 1 | 0.197943 | 0.451804 | 0.086246 | 0.001602 | 1.31 | 445.6287 | 0.000151 |
34 | 7 | 4 | 7 | 1 | 2 | 3 | 1 | 1 | 7 | 0.423379 | 0.443827 | 1 | 0.377545 | 0.649911 | 0.068718 | 0.00144 | 1.31 | 454.7637 | 0.000158 |
35 | 0 | 1 | 4 | 1 | 1 | 1 | 0 | 5 | 4 | 0.064909 | 0.224503 | 1 | 0.722887 | 0.761975 | 0.011154 | 0.000775 | 1.31 | 472.3287 | 0.000161 |
36 | 0 | 2 | 0 | 2 | 0 | 6 | 3 | 3 | 5 | 0.242549 | 0.44596 | 1 | 0.63694 | 0.334122 | 0.03968 | 0.001447 | 1.31 | 467.9572 | 0.000147 |
37 | 3 | 3 | 5 | 6 | 1 | 1 | 0 | 2 | 0 | 0.299151 | 0.465476 | 1 | 0.600846 | 0.731815 | 0.048769 | 0.001506 | 1.31 | 466.1214 | 0.00016 |
38 | 1 | 6 | 3 | 0 | 5 | 0 | 5 | 7 | 0 | 0.510224 | 0.430275 | 1 | 0.536058 | 0.561502 | 0.082664 | 0.001399 | 1.31 | 462.8261 | 0.000155 |
39 | 3 | 6 | 2 | 6 | 4 | 5 | 1 | 4 | 6 | 0.11613 | 0.271422 | 1 | 0.453343 | 0.39178 | 0.019379 | 0.000917 | 1.31 | 458.619 | 0.000149 |
40 | 0 | 7 | 5 | 2 | 4 | 7 | 5 | 7 | 6 | 0.320387 | 0.56688 | 1 | 0.302159 | 0.391189 | 0.052179 | 0.001814 | 1.31 | 450.9294 | 0.000149 |
41 | 4 | 0 | 5 | 3 | 3 | 0 | 7 | 1 | 2 | 0.472454 | 0.534492 | 1 | 0.514521 | 0.619456 | 0.076598 | 0.001715 | 1.31 | 461.7307 | 0.000157 |
42 | 4 | 2 | 5 | 3 | 5 | 2 | 6 | 7 | 1 | 0.538166 | 0.571798 | 1 | 0.399394 | 0.477232 | 0.087151 | 0.001828 | 1.31 | 455.875 | 0.000152 |
43 | 3 | 3 | 7 | 5 | 0 | 0 | 6 | 4 | 6 | 0.613564 | 0.685433 | 1 | 0.428228 | 0.561206 | 0.099258 | 0.002173 | 1.31 | 457.3416 | 0.000155 |
44 | 5 | 3 | 2 | 1 | 5 | 0 | 0 | 3 | 4 | 0.187648 | 0.217897 | 1 | 0.546968 | 0.588409 | 0.030863 | 0.000755 | 1.31 | 463.381 | 0.000156 |
45 | 3 | 7 | 1 | 4 | 7 | 2 | 6 | 2 | 5 | 0.284908 | 0.524088 | 1 | 0.366947 | 0.47191 | 0.046482 | 0.001684 | 1.31 | 454.2247 | 0.000152 |
46 | 2 | 4 | 3 | 6 | 1 | 3 | 5 | 5 | 1 | 0.421197 | 0.456595 | 1 | 0.431806 | 0.544352 | 0.068367 | 0.001479 | 1.31 | 457.5236 | 0.000154 |
47 | 3 | 2 | 1 | 0 | 6 | 1 | 7 | 1 | 7 | 0.403619 | 0.395517 | 1 | 0.499894 | 0.712892 | 0.065545 | 0.001294 | 1.31 | 460.9867 | 0.00016 |
48 | 3 | 1 | 5 | 1 | 3 | 6 | 5 | 3 | 2 | 0.285674 | 0.452128 | 1 | 0.392308 | 0.707865 | 0.046605 | 0.001465 | 1.31 | 455.5146 | 0.00016 |
49 | 7 | 6 | 5 | 0 | 5 | 0 | 6 | 7 | 7 | 0.548869 | 0.591139 | 1 | 0.323731 | 0.346836 | 0.088869 | 0.001887 | 1.31 | 452.0266 | 0.000147 |
50 | 2 | 0 | 2 | 2 | 6 | 2 | 7 | 6 | 5 | 0.134423 | 0.452395 | 1 | 0.557661 | 0.197221 | 0.022316 | 0.001466 | 1.31 | 463.9249 | 0.000142 |
51 | 5 | 2 | 6 | 3 | 3 | 2 | 3 | 2 | 6 | 0.430391 | 0.4078 | 1 | 0.417596 | 0.493199 | 0.069844 | 0.001331 | 1.31 | 456.8008 | 0.000152 |
52 | 3 | 3 | 1 | 3 | 0 | 2 | 4 | 5 | 6 | 0.560031 | 0.480069 | 1 | 0.467866 | 0.672975 | 0.090662 | 0.00155 | 1.31 | 459.3577 | 0.000158 |
53 | 6 | 3 | 6 | 6 | 0 | 5 | 7 | 6 | 6 | 0.242732 | 0.408835 | 1 | 0.359822 | 0.284151 | 0.039709 | 0.001334 | 1.31 | 453.8623 | 0.000145 |
54 | 0 | 7 | 1 | 6 | 7 | 3 | 3 | 2 | 3 | 0.551504 | 0.478632 | 1 | 0.36344 | 0.570077 | 0.089292 | 0.001546 | 1.31 | 454.0463 | 0.000155 |
55 | 3 | 4 | 7 | 5 | 7 | 7 | 3 | 3 | 3 | 0.578299 | 0.597709 | 1 | 0.104533 | 0.620343 | 0.093595 | 0.001907 | 1.31 | 440.8776 | 0.000157 |
56 | 0 | 2 | 0 | 5 | 6 | 3 | 3 | 7 | 4 | 0.277372 | 0.452161 | 1 | 0.471409 | 0.444707 | 0.045272 | 0.001466 | 1.31 | 459.5379 | 0.000151 |
57 | 4 | 7 | 4 | 0 | 5 | 2 | 3 | 7 | 0 | 0.275232 | 0.324038 | 1 | 0.453311 | 0.451804 | 0.044928 | 0.001077 | 1.31 | 458.6174 | 0.000151 |
58 | 7 | 2 | 1 | 7 | 7 | 3 | 1 | 0 | 7 | 0.427597 | 0.439545 | 1 | 0.341589 | 0.560319 | 0.069395 | 0.001427 | 1.31 | 452.9349 | 0.000155 |
59 | 3 | 1 | 4 | 2 | 7 | 0 | 6 | 6 | 4 | 0.094595 | 0.178919 | 1 | 0.500033 | 0.482555 | 0.015921 | 0.000637 | 1.31 | 460.9938 | 0.000152 |
60 | 3 | 0 | 1 | 5 | 3 | 7 | 2 | 2 | 7 | 0.461002 | 0.537221 | 1 | 0.406586 | 0.561798 | 0.074759 | 0.001724 | 1.31 | 456.2408 | 0.000155 |
61 | 1 | 3 | 6 | 3 | 2 | 2 | 0 | 4 | 4 | 0.494293 | 0.382014 | 1 | 0.575696 | 0.641041 | 0.080105 | 0.001253 | 1.31 | 464.8422 | 0.000157 |
62 | 3 | 7 | 3 | 4 | 6 | 7 | 7 | 2 | 3 | 0.575096 | 0.494679 | 1 | 0.197978 | 0.533116 | 0.093081 | 0.001595 | 1.31 | 445.6305 | 0.000154 |
63 | 6 | 7 | 2 | 5 | 1 | 2 | 6 | 6 | 3 | 0.47932 | 0.546471 | 1 | 0.41016 | 0.400946 | 0.077701 | 0.001752 | 1.31 | 456.4226 | 0.000149 |
64 | 3 | 5 | 0 | 7 | 1 | 1 | 5 | 3 | 6 | 0.550448 | 0.485482 | 1 | 0.395782 | 0.735659 | 0.089123 | 0.001567 | 1.31 | 455.6913 | 0.00016 |
65 | 6 | 3 | 5 | 2 | 3 | 3 | 5 | 0 | 5 | 0.307622 | 0.658289 | 1 | 0.36007 | 0.453873 | 0.050129 | 0.002091 | 1.31 | 453.8749 | 0.000151 |
66 | 6 | 0 | 3 | 2 | 6 | 2 | 3 | 2 | 1 | 0.403209 | 0.294518 | 1 | 0.590109 | 0.51508 | 0.065479 | 0.000987 | 1.31 | 465.5753 | 0.000153 |
67 | 7 | 2 | 4 | 2 | 0 | 3 | 7 | 4 | 6 | 0.142804 | 0.248769 | 1 | 0.442506 | 0.392667 | 0.023662 | 0.000849 | 1.31 | 458.0678 | 0.000149 |
68 | 1 | 6 | 6 | 6 | 1 | 5 | 5 | 3 | 0 | 0.190283 | 0.330206 | 1 | 0.478493 | 0.503548 | 0.031287 | 0.001096 | 1.31 | 459.8982 | 0.000153 |
69 | 3 | 5 | 2 | 4 | 5 | 2 | 4 | 2 | 4 | 0.122977 | 0.231877 | 1 | 0.485827 | 0.425488 | 0.020478 | 0.000797 | 1.31 | 460.2712 | 0.00015 |
70 | 6 | 7 | 7 | 7 | 5 | 0 | 3 | 2 | 0 | 0.904235 | 0.703666 | 1 | 0.366947 | 0.479302 | 0.145935 | 0.002229 | 1.31 | 454.2247 | 0.000152 |
71 | 1 | 4 | 6 | 7 | 2 | 1 | 4 | 6 | 7 | 0.338105 | 0.503494 | 1 | 0.431527 | 0.500887 | 0.055024 | 0.001621 | 1.31 | 457.5094 | 0.000153 |
72 | 6 | 2 | 2 | 7 | 0 | 7 | 3 | 1 | 1 | 0.440544 | 0.398428 | 1 | 0.499963 | 0.582496 | 0.071474 | 0.001303 | 1.31 | 460.9902 | 0.000155 |
73 | 6 | 4 | 2 | 1 | 2 | 4 | 6 | 0 | 2 | 0.023334 | 0.118602 | 1 | 0.669107 | 0.383205 | 0.004477 | 0.000454 | 1.31 | 469.5933 | 0.000149 |
74 | 2 | 7 | 3 | 5 | 0 | 5 | 0 | 6 | 6 | 0.537169 | 0.610318 | 1 | 0.45699 | 0.439681 | 0.086991 | 0.001945 | 1.31 | 458.8045 | 0.00015 |
75 | 4 | 3 | 7 | 5 | 3 | 4 | 4 | 3 | 1 | 0.569722 | 0.649718 | 1 | 0.31672 | 0.636606 | 0.092218 | 0.002065 | 1.31 | 451.67 | 0.000157 |
76 | 6 | 4 | 7 | 1 | 6 | 3 | 0 | 3 | 0 | 0.50661 | 0.42206 | 1 | 0.496491 | 0.598167 | 0.082083 | 0.001374 | 1.31 | 460.8136 | 0.000156 |
77 | 1 | 0 | 1 | 2 | 1 | 7 | 0 | 2 | 2 | 0.041376 | 0.092042 | 1 | 0.748104 | 0.678001 | 0.007375 | 0.000373 | 1.31 | 473.6113 | 0.000159 |
78 | 2 | 0 | 4 | 6 | 5 | 2 | 0 | 7 | 0 | 0.164847 | 0.25014 | 1 | 0.643956 | 0.265523 | 0.027202 | 0.000853 | 1.31 | 468.3141 | 0.000145 |
79 | 6 | 3 | 6 | 1 | 5 | 5 | 2 | 3 | 3 | 0.480119 | 0.454953 | 1 | 0.349196 | 0.559728 | 0.077829 | 0.001474 | 1.31 | 453.3218 | 0.000155 |
80 | 3 | 3 | 0 | 3 | 1 | 3 | 7 | 6 | 4 | 0.579898 | 0.42444 | 1 | 0.367124 | 0.747191 | 0.093852 | 0.001381 | 1.31 | 454.2337 | 0.000161 |
81 | 6 | 4 | 3 | 3 | 1 | 5 | 6 | 7 | 7 | 0.465137 | 0.480013 | 1 | 0.255471 | 0.445594 | 0.075423 | 0.00155 | 1.31 | 448.5547 | 0.000151 |
82 | 3 | 6 | 1 | 1 | 0 | 3 | 4 | 7 | 2 | 0.247122 | 0.271963 | 1 | 0.503647 | 0.704021 | 0.040414 | 0.000919 | 1.31 | 461.1776 | 0.000159 |
83 | 1 | 3 | 0 | 6 | 1 | 7 | 5 | 3 | 4 | 0.217825 | 0.265261 | 1 | 0.435316 | 0.666765 | 0.035709 | 0.000899 | 1.31 | 457.7021 | 0.000158 |
84 | 5 | 3 | 2 | 1 | 1 | 5 | 5 | 6 | 4 | 0.19824 | 0.26569 | 1 | 0.431771 | 0.561502 | 0.032564 | 0.0009 | 1.31 | 457.5218 | 0.000155 |
85 | 4 | 4 | 1 | 3 | 1 | 3 | 0 | 6 | 1 | 0.379392 | 0.3188 | 1 | 0.575558 | 0.679184 | 0.061654 | 0.001061 | 1.31 | 464.8352 | 0.000159 |
86 | 5 | 6 | 2 | 1 | 5 | 1 | 6 | 7 | 1 | 0.159262 | 0.200435 | 1 | 0.453168 | 0.581313 | 0.026305 | 0.000702 | 1.31 | 458.6101 | 0.000155 |
87 | 3 | 7 | 6 | 5 | 7 | 0 | 6 | 5 | 5 | 0.36116 | 0.856509 | 1 | 0.251926 | 0.244234 | 0.058727 | 0.002692 | 1.31 | 448.3744 | 0.000144 |
88 | 0 | 6 | 7 | 0 | 1 | 7 | 4 | 6 | 2 | 0.390273 | 0.406191 | 1 | 0.532305 | 0.446481 | 0.063401 | 0.001326 | 1.31 | 462.6352 | 0.000151 |
89 | 3 | 7 | 7 | 7 | 6 | 5 | 7 | 7 | 1 | 0.978264 | 0.839107 | 1 | 0.093412 | 0.434358 | 0.157823 | 0.002639 | 1.31 | 440.312 | 0.00015 |
90 | 7 | 3 | 2 | 6 | 1 | 0 | 1 | 0 | 7 | 0.530957 | 0.478283 | 1 | 0.535918 | 0.557067 | 0.085993 | 0.001545 | 1.31 | 462.819 | 0.000154 |
91 | 0 | 1 | 7 | 1 | 7 | 6 | 0 | 6 | 1 | 0.374793 | 0.377066 | 1 | 0.560964 | 0.535778 | 0.060916 | 0.001238 | 1.31 | 464.0929 | 0.000154 |
92 | 6 | 2 | 7 | 2 | 1 | 4 | 1 | 4 | 0 | 0.359549 | 0.341154 | 1 | 0.611441 | 0.558545 | 0.058468 | 0.001129 | 1.31 | 466.6603 | 0.000155 |
93 | 6 | 4 | 7 | 4 | 1 | 5 | 3 | 7 | 6 | 0.560916 | 0.522354 | 1 | 0.294969 | 0.535482 | 0.090804 | 0.001678 | 1.31 | 450.5637 | 0.000154 |
94 | 7 | 5 | 6 | 0 | 5 | 0 | 2 | 0 | 7 | 0.411529 | 0.491096 | 1 | 0.503645 | 0.374926 | 0.066815 | 0.001584 | 1.31 | 461.1775 | 0.000148 |
95 | 0 | 5 | 4 | 4 | 2 | 4 | 0 | 5 | 3 | 0.350671 | 0.450295 | 1 | 0.557738 | 0.311354 | 0.057042 | 0.00146 | 1.31 | 463.9288 | 0.000146 |
96 | 2 | 2 | 6 | 7 | 7 | 4 | 2 | 3 | 1 | 0.488383 | 0.423471 | 1 | 0.435279 | 0.453873 | 0.079156 | 0.001379 | 1.31 | 457.7002 | 0.000151 |
97 | 2 | 7 | 6 | 6 | 6 | 2 | 4 | 5 | 7 | 0.490549 | 0.669365 | 1 | 0.34895 | 0.161739 | 0.079504 | 0.002124 | 1.31 | 453.3093 | 0.000141 |
98 | 5 | 3 | 2 | 2 | 7 | 6 | 3 | 1 | 3 | 0.531609 | 0.396077 | 1 | 0.35993 | 0.631283 | 0.086098 | 0.001295 | 1.31 | 453.8678 | 0.000157 |
99 | 1 | 7 | 5 | 2 | 7 | 1 | 5 | 3 | 3 | 0.538176 | 0.598929 | 1 | 0.30223 | 0.722649 | 0.087152 | 0.001911 | 1.31 | 450.933 | 0.00016 |
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8-bit GNN Multiplier Configuration PPA Dataset
This repository contains the 8-bit approximate multiplier configuration dataset used by the OpenACM PEA-GNN surrogate, together with the final model weights and helper code needed for reproduction.
Hugging Face Dataset File
data/configs_ppa.csv: the main table fordatasets.load_dataset. Each row containssample_id, the multiplier configuration vector, normalized targets, and raw targets (mred,nmed,delay,area,power).
Example:
from datasets import load_dataset
dataset = load_dataset("xuzhuo0417/openacm-gnn-8bit-dataset")
print(dataset["train"][0])
Repository Layout
raw/dir_vectors.txt: original50000x9configuration vectors.raw/label.txt: normalized50000x 5 labels used for GNN training.raw/merged.log: unnormalized50000x 5 target values.raw/label_minmax.txt: two-row min/max file used to normalizeraw/merged.logintoraw/label.txt.raw/Graph.csv: fixed graph adjacency matrix for the multiplier graph.metadata/FEATURE.csv: static feature table retained for reproducibility.metadata/graph_edges.csv: edge list exported fromraw/Graph.csv; duplicate edges are preserved when the adjacency entry is greater than 1.metadata/dataset_summary.json: compact machine-readable metadata.code/data_pyg.pyandcode/node_feature.py: scripts for rebuilding the PyTorch Geometric dataset fromraw/.code/merge.pyandcode/minmax.py: scripts documenting target merge and min-max normalization.model/best_model_weights_8.pth: final GNN model weights.model/gnn_predictor.pyandmodel/my_io.py: inference helper files.model/FEATURE.csvandmodel/label_minmax_8.txt: model-side metadata used by the inference helpers.
Row Ranges
The main HF table keeps all rows in one file. The row ranges used by the local training scripts are:
all: 0:50000 (50000 rows)
train: 0:46000 (46000 rows)
validation: 46000:48000 (2000 rows)
test: 48000:50000 (2000 rows)
Normalization
raw/label.txt is generated from raw/merged.log using min-max normalization:
target_normalized = (target_raw - target_min) / (target_max - target_min + 1e-12)
The min and max values are stored in raw/label_minmax.txt.
Model Weights
The model/ directory contains final model parameters only, without optimizer or epoch state. For model discovery and download statistics on Hugging Face, these files can also be uploaded to a separate model repository and linked to the same paper page.
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Models trained or fine-tuned on xuzhuo0417/openacm-gnn-8bit-dataset