Datasets:

---

ShreyashDhoot

/

tandam-training-notebooks

like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
run_id: string
experiment: string
use_patch: bool
use_contrast: bool
best_val_acc: double
test_f1: double
test_pr_auc: double
threshold: double
cross_domain_f1: null
cross_domain_pr_auc: null
weight_path: string
history_path: string
to
{'epoch': Value('int64'), 'train_loss': Value('float64'), 'train_acc': Value('float64'), 'train_precision': Value('float64'), 'train_recall': Value('float64'), 'val_loss': Value('float64'), 'val_acc': Value('float64'), 'val_precision': Value('float64'), 'val_recall': Value('float64'), 'lr': Value('float64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 764, in write_table
                  self.write_rows_on_file()  # in case there are buffered rows to write first
                  ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
                  self._write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              run_id: string
              experiment: string
              use_patch: bool
              use_contrast: bool
              best_val_acc: double
              test_f1: double
              test_pr_auc: double
              threshold: double
              cross_domain_f1: null
              cross_domain_pr_auc: null
              weight_path: string
              history_path: string
              to
              {'epoch': Value('int64'), 'train_loss': Value('float64'), 'train_acc': Value('float64'), 'train_precision': Value('float64'), 'train_recall': Value('float64'), 'val_loss': Value('float64'), 'val_acc': Value('float64'), 'val_precision': Value('float64'), 'val_recall': Value('float64'), 'lr': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, 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 12 new columns ({'best_val_acc', 'use_contrast', 'test_f1', 'cross_domain_pr_auc', 'history_path', 'use_patch', 'weight_path', 'test_pr_auc', 'experiment', 'cross_domain_f1', 'threshold', 'run_id'}) and 10 missing columns ({'epoch', 'val_acc', 'val_loss', 'val_recall', 'lr', 'train_loss', 'val_precision', 'train_precision', 'train_acc', 'train_recall'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/ShreyashDhoot/tandam-training-notebooks/model_2_patch_history.json (at revision 9162c7c01e2f62d88dc4241f548a8cc34a7a59c5), [/tmp/hf-datasets-cache/medium/datasets/65947999568896-config-parquet-and-info-ShreyashDhoot-tandam-trai-836912b8/hub/datasets--ShreyashDhoot--tandam-training-notebooks/snapshots/9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_1_baseline_history.json (origin=hf://datasets/ShreyashDhoot/tandam-training-notebooks@9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_1_baseline_history.json), /tmp/hf-datasets-cache/medium/datasets/65947999568896-config-parquet-and-info-ShreyashDhoot-tandam-trai-836912b8/hub/datasets--ShreyashDhoot--tandam-training-notebooks/snapshots/9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_1_baseline_summary.json (origin=hf://datasets/ShreyashDhoot/tandam-training-notebooks@9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_1_baseline_summary.json), /tmp/hf-datasets-cache/medium/datasets/65947999568896-config-parquet-and-info-ShreyashDhoot-tandam-trai-836912b8/hub/datasets--ShreyashDhoot--tandam-training-notebooks/snapshots/9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_2_patch_history.json (origin=hf://datasets/ShreyashDhoot/tandam-training-notebooks@9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_2_patch_history.json), /tmp/hf-datasets-cache/medium/datasets/65947999568896-config-parquet-and-info-ShreyashDhoot-tandam-trai-836912b8/hub/datasets--ShreyashDhoot--tandam-training-notebooks/snapshots/9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_2_patch_summary.json (origin=hf://datasets/ShreyashDhoot/tandam-training-notebooks@9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_2_patch_summary.json)], ['hf://datasets/ShreyashDhoot/tandam-training-notebooks@9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_1_baseline_history.json', 'hf://datasets/ShreyashDhoot/tandam-training-notebooks@9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_1_baseline_summary.json', 'hf://datasets/ShreyashDhoot/tandam-training-notebooks@9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_2_patch_history.json', 'hf://datasets/ShreyashDhoot/tandam-training-notebooks@9162c7c01e2f62d88dc4241f548a8cc34a7a59c5/model_2_patch_summary.json']
              
              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)
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1821, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
                  self._write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              run_id: string
              experiment: string
              use_patch: bool
              use_contrast: bool
              best_val_acc: double
              test_f1: double
              test_pr_auc: double
              threshold: double
              cross_domain_f1: null
              cross_domain_pr_auc: null
              weight_path: string
              history_path: string
              to
              {'epoch': Value('int64'), 'train_loss': Value('float64'), 'train_acc': Value('float64'), 'train_precision': Value('float64'), 'train_recall': Value('float64'), 'val_loss': Value('float64'), 'val_acc': Value('float64'), 'val_precision': Value('float64'), 'val_recall': Value('float64'), 'lr': Value('float64')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, 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 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset