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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
option: string
trained_at: string
elapsed_sec: double
winning_loss: string
test_ann_return: double
test_ann_vol: double
test_sharpe: double
test_max_dd: double
test_hit_rate: double
test_start: timestamp[s]
n_params: int64
n_assets: int64
tickers: list<item: string>
child 0, item: string
n_asset_feats: int64
n_macro_feats: int64
lookback: int64
config: struct<d_model: int64, d_state: int64, d_conv: int64, expand: int64, n_mamba_layers: int64, macro_hi (... 62 chars omitted)
child 0, d_model: int64
child 1, d_state: int64
child 2, d_conv: int64
child 3, expand: int64
child 4, n_mamba_layers: int64
child 5, macro_hidden_dim: int64
child 6, graph_hidden_dim: int64
child 7, n_attn_heads: int64
all_results: struct<sharpe: struct<loss_fn: string, test_ann_ret: double, test_sharpe: double, test_ann_vol: doub (... 222 chars omitted)
child 0, sharpe: struct<loss_fn: string, test_ann_ret: double, test_sharpe: double, test_ann_vol: double, test_max_dd (... 49 chars omitted)
child 0, loss_fn: string
child 1, test_ann_ret: double
child 2, test_sharpe: double
child 3, test_ann_vol: double
child 4, test_max_dd: double
child 5, test_hit_rate: double
child 6, n_params: int64
child 1, evar: struct<loss_fn: string, test_ann_ret: double, test_sharpe: double, test_ann_vol: double, test_max_dd (... 49 chars omitted)
child 0, loss_fn: string
child 1, test_ann_ret: double
child 2, test_sharpe: double
child 3, tes
...
x_dd: double
option_B: struct<option: string, mode: string, option_name: string, signal_date: timestamp[s], last_data_date: (... 589 chars omitted)
child 0, option: string
child 1, mode: string
child 2, option_name: string
child 3, signal_date: timestamp[s]
child 4, last_data_date: timestamp[s]
child 5, generated_at: string
child 6, pick: string
child 7, conviction: double
child 8, weights: struct<SPY: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XL (... 114 chars omitted)
child 0, SPY: double
child 1, QQQ: double
child 2, XLK: double
child 3, XLF: double
child 4, XLE: double
child 5, XLV: double
child 6, XLI: double
child 7, XLY: double
child 8, XLP: double
child 9, XLU: double
child 10, GDX: double
child 11, IWF: double
child 12, IWM: double
child 13, XSD: double
child 14, XBI: double
child 15, XME: double
child 9, regime_context: struct<VIX: double, T10Y2Y: double, HY_SPREAD: double, USD_INDEX: double>
child 0, VIX: double
child 1, T10Y2Y: double
child 2, HY_SPREAD: double
child 3, USD_INDEX: double
child 10, trained_at: string
child 11, winning_loss: string
child 12, test_ann_return: double
child 13, test_ann_vol: double
child 14, test_sharpe: double
child 15, test_max_dd: double
child 16, test_hit_rate: double
child 17, test_start: timestamp[s]
child 18, model_n_params: int64
to
{'generated_at': Value('string'), 'option_A': {'option': Value('string'), 'mode': Value('string'), 'option_name': Value('string'), 'signal_date': Value('timestamp[s]'), 'last_data_date': Value('timestamp[s]'), 'generated_at': Value('string'), 'pick': Value('string'), 'conviction': Value('float64'), 'weights': {'TLT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64'), 'PFF': Value('float64'), 'MBB': Value('float64')}, 'regime_context': {'VIX': Value('float64'), 'T10Y2Y': Value('float64'), 'HY_SPREAD': Value('float64'), 'USD_INDEX': Value('float64')}, 'trained_at': Value('string'), 'winning_loss': Value('string'), 'test_ann_return': Value('float64'), 'test_ann_vol': Value('float64'), 'test_sharpe': Value('float64'), 'test_max_dd': Value('float64'), 'test_hit_rate': Value('float64'), 'test_start': Value('timestamp[s]'), 'model_n_params': Value('int64')}, 'option_B': {'option': Value('string'), 'mode': Value('string'), 'option_name': Value('string'), 'signal_date': Value('timestamp[s]'), 'last_data_date': Value('timestamp[s]'), 'generated_at': Value('string'), 'pick': Value('string'), 'conviction': Value('float64'), 'weights': {'SPY': Value('float64'), 'QQQ': Value('float64'), 'XLK': Value('float64'), 'XLF': Value('float64'), 'XLE': Value('float64'), 'XLV': Value('float64'), 'XLI': Value('float64'), 'XLY': Value('float64'), 'XLP': Value('float64'), 'XLU': Value('float64'), 'GDX': Value('fl
...
, 'GLD': Value('float64'), 'SLV': Value('float64'), 'PFF': Value('float64'), 'MBB': Value('float64')}, 'trained_at': Value('string'), 'winning_window': Value('int64'), 'winning_train_start': Value('timestamp[s]'), 'winning_train_end': Value('timestamp[s]'), 'winning_loss': Value('string'), 'oos_ann_return': Value('float64'), 'oos_ann_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'oos_hit_rate': Value('float64'), 'oos_max_dd': Value('float64')}, 'option_B_window': {'option': Value('string'), 'mode': Value('string'), 'option_name': Value('string'), 'signal_date': Value('timestamp[s]'), 'last_data_date': Value('timestamp[s]'), 'generated_at': Value('string'), 'pick': Value('string'), 'conviction': Value('float64'), 'weights': {'SPY': Value('float64'), 'QQQ': Value('float64'), 'XLK': Value('float64'), 'XLF': Value('float64'), 'XLE': Value('float64'), 'XLV': Value('float64'), 'XLI': Value('float64'), 'XLY': Value('float64'), 'XLP': Value('float64'), 'XLU': Value('float64'), 'GDX': Value('float64'), 'IWF': Value('float64'), 'IWM': Value('float64'), 'XSD': Value('float64'), 'XBI': Value('float64'), 'XME': Value('float64')}, 'trained_at': Value('string'), 'winning_window': Value('int64'), 'winning_train_start': Value('timestamp[s]'), 'winning_train_end': Value('timestamp[s]'), 'winning_loss': Value('string'), 'oos_ann_return': Value('float64'), 'oos_ann_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'oos_hit_rate': Value('float64'), 'oos_max_dd': Value('float64')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_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
option: string
trained_at: string
elapsed_sec: double
winning_loss: string
test_ann_return: double
test_ann_vol: double
test_sharpe: double
test_max_dd: double
test_hit_rate: double
test_start: timestamp[s]
n_params: int64
n_assets: int64
tickers: list<item: string>
child 0, item: string
n_asset_feats: int64
n_macro_feats: int64
lookback: int64
config: struct<d_model: int64, d_state: int64, d_conv: int64, expand: int64, n_mamba_layers: int64, macro_hi (... 62 chars omitted)
child 0, d_model: int64
child 1, d_state: int64
child 2, d_conv: int64
child 3, expand: int64
child 4, n_mamba_layers: int64
child 5, macro_hidden_dim: int64
child 6, graph_hidden_dim: int64
child 7, n_attn_heads: int64
all_results: struct<sharpe: struct<loss_fn: string, test_ann_ret: double, test_sharpe: double, test_ann_vol: doub (... 222 chars omitted)
child 0, sharpe: struct<loss_fn: string, test_ann_ret: double, test_sharpe: double, test_ann_vol: double, test_max_dd (... 49 chars omitted)
child 0, loss_fn: string
child 1, test_ann_ret: double
child 2, test_sharpe: double
child 3, test_ann_vol: double
child 4, test_max_dd: double
child 5, test_hit_rate: double
child 6, n_params: int64
child 1, evar: struct<loss_fn: string, test_ann_ret: double, test_sharpe: double, test_ann_vol: double, test_max_dd (... 49 chars omitted)
child 0, loss_fn: string
child 1, test_ann_ret: double
child 2, test_sharpe: double
child 3, tes
...
x_dd: double
option_B: struct<option: string, mode: string, option_name: string, signal_date: timestamp[s], last_data_date: (... 589 chars omitted)
child 0, option: string
child 1, mode: string
child 2, option_name: string
child 3, signal_date: timestamp[s]
child 4, last_data_date: timestamp[s]
child 5, generated_at: string
child 6, pick: string
child 7, conviction: double
child 8, weights: struct<SPY: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XL (... 114 chars omitted)
child 0, SPY: double
child 1, QQQ: double
child 2, XLK: double
child 3, XLF: double
child 4, XLE: double
child 5, XLV: double
child 6, XLI: double
child 7, XLY: double
child 8, XLP: double
child 9, XLU: double
child 10, GDX: double
child 11, IWF: double
child 12, IWM: double
child 13, XSD: double
child 14, XBI: double
child 15, XME: double
child 9, regime_context: struct<VIX: double, T10Y2Y: double, HY_SPREAD: double, USD_INDEX: double>
child 0, VIX: double
child 1, T10Y2Y: double
child 2, HY_SPREAD: double
child 3, USD_INDEX: double
child 10, trained_at: string
child 11, winning_loss: string
child 12, test_ann_return: double
child 13, test_ann_vol: double
child 14, test_sharpe: double
child 15, test_max_dd: double
child 16, test_hit_rate: double
child 17, test_start: timestamp[s]
child 18, model_n_params: int64
to
{'generated_at': Value('string'), 'option_A': {'option': Value('string'), 'mode': Value('string'), 'option_name': Value('string'), 'signal_date': Value('timestamp[s]'), 'last_data_date': Value('timestamp[s]'), 'generated_at': Value('string'), 'pick': Value('string'), 'conviction': Value('float64'), 'weights': {'TLT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64'), 'PFF': Value('float64'), 'MBB': Value('float64')}, 'regime_context': {'VIX': Value('float64'), 'T10Y2Y': Value('float64'), 'HY_SPREAD': Value('float64'), 'USD_INDEX': Value('float64')}, 'trained_at': Value('string'), 'winning_loss': Value('string'), 'test_ann_return': Value('float64'), 'test_ann_vol': Value('float64'), 'test_sharpe': Value('float64'), 'test_max_dd': Value('float64'), 'test_hit_rate': Value('float64'), 'test_start': Value('timestamp[s]'), 'model_n_params': Value('int64')}, 'option_B': {'option': Value('string'), 'mode': Value('string'), 'option_name': Value('string'), 'signal_date': Value('timestamp[s]'), 'last_data_date': Value('timestamp[s]'), 'generated_at': Value('string'), 'pick': Value('string'), 'conviction': Value('float64'), 'weights': {'SPY': Value('float64'), 'QQQ': Value('float64'), 'XLK': Value('float64'), 'XLF': Value('float64'), 'XLE': Value('float64'), 'XLV': Value('float64'), 'XLI': Value('float64'), 'XLY': Value('float64'), 'XLP': Value('float64'), 'XLU': Value('float64'), 'GDX': Value('fl
...
, 'GLD': Value('float64'), 'SLV': Value('float64'), 'PFF': Value('float64'), 'MBB': Value('float64')}, 'trained_at': Value('string'), 'winning_window': Value('int64'), 'winning_train_start': Value('timestamp[s]'), 'winning_train_end': Value('timestamp[s]'), 'winning_loss': Value('string'), 'oos_ann_return': Value('float64'), 'oos_ann_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'oos_hit_rate': Value('float64'), 'oos_max_dd': Value('float64')}, 'option_B_window': {'option': Value('string'), 'mode': Value('string'), 'option_name': Value('string'), 'signal_date': Value('timestamp[s]'), 'last_data_date': Value('timestamp[s]'), 'generated_at': Value('string'), 'pick': Value('string'), 'conviction': Value('float64'), 'weights': {'SPY': Value('float64'), 'QQQ': Value('float64'), 'XLK': Value('float64'), 'XLF': Value('float64'), 'XLE': Value('float64'), 'XLV': Value('float64'), 'XLI': Value('float64'), 'XLY': Value('float64'), 'XLP': Value('float64'), 'XLU': Value('float64'), 'GDX': Value('float64'), 'IWF': Value('float64'), 'IWM': Value('float64'), 'XSD': Value('float64'), 'XBI': Value('float64'), 'XME': Value('float64')}, 'trained_at': Value('string'), 'winning_window': Value('int64'), 'winning_train_start': Value('timestamp[s]'), 'winning_train_end': Value('timestamp[s]'), 'winning_loss': Value('string'), 'oos_ann_return': Value('float64'), 'oos_ann_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'oos_hit_rate': Value('float64'), 'oos_max_dd': Value('float64')}}
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