TWLab/femtosecond-laser-hydrogel-etching-model
Reinforcement Learning • Updated • 167
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
power_mW: double
repetition_rate_kHz: int64
scan_speed_mm_s: double
pulse_duration_fs: double
wavelength_nm: int64
num_passes: int64
spot_diameter_um: double
focal_offset_um: double
material_name: large_string
material_type: large_string
water_content: double
threshold_fluence_J_cm2: double
absorption_depth_nm: int64
incubation_coefficient: double
refractive_index: double
youngs_modulus_kPa: double
degree_of_methacrylation: double
crosslink_density_mol_m3: int64
two_photon_cross_section_GM: double
pulse_energy_uJ: double
peak_fluence_J_cm2: double
effective_pulses: double
overlap_percent: double
etch_depth_um: double
etch_width_um: double
surface_roughness_Sa_um: double
aspect_ratio: double
side_wall_angle_deg: double
-- schema metadata --
huggingface: '{"info": {"features": {"power_mW": {"dtype": "float64", "_t' + 1666
to
{'power_mW': Value('float64'), 'repetition_rate_kHz': Value('float64'), 'scan_speed_mm_s': Value('float64'), 'pulse_duration_fs': Value('float64'), 'wavelength_nm': Value('float64'), 'num_passes': Value('int64'), 'spot_diameter_um': Value('float64'), 'focal_offset_um': Value('float64'), 'material': Value('large_string'), 'water_content': Value('float64'), 'threshold_fluence_J_cm2': Value('float64'), 'absorption_depth_nm': Value('float64'), 'incubation_coefficient': Value('float64'), 'refractive_index': Value('float64'), 'pulse_energy_uJ': Value('float64'), 'peak_fluence_J_cm2': Value('float64'), 'effective_pulses': Value('float64'), 'overlap_percent': Value('float64'), 'etch_depth_um': Value('float64'), 'etch_width_um': Value('float64'), 'surface_roughness_Sa_um': Value('float64'), 'aspect_ratio': Value('float64'), 'side_wall_angle_deg': 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/parquet/parquet.py", line 209, in _generate_tables
yield Key(file_idx, batch_idx), self._cast_table(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 147, 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
power_mW: double
repetition_rate_kHz: int64
scan_speed_mm_s: double
pulse_duration_fs: double
wavelength_nm: int64
num_passes: int64
spot_diameter_um: double
focal_offset_um: double
material_name: large_string
material_type: large_string
water_content: double
threshold_fluence_J_cm2: double
absorption_depth_nm: int64
incubation_coefficient: double
refractive_index: double
youngs_modulus_kPa: double
degree_of_methacrylation: double
crosslink_density_mol_m3: int64
two_photon_cross_section_GM: double
pulse_energy_uJ: double
peak_fluence_J_cm2: double
effective_pulses: double
overlap_percent: double
etch_depth_um: double
etch_width_um: double
surface_roughness_Sa_um: double
aspect_ratio: double
side_wall_angle_deg: double
-- schema metadata --
huggingface: '{"info": {"features": {"power_mW": {"dtype": "float64", "_t' + 1666
to
{'power_mW': Value('float64'), 'repetition_rate_kHz': Value('float64'), 'scan_speed_mm_s': Value('float64'), 'pulse_duration_fs': Value('float64'), 'wavelength_nm': Value('float64'), 'num_passes': Value('int64'), 'spot_diameter_um': Value('float64'), 'focal_offset_um': Value('float64'), 'material': Value('large_string'), 'water_content': Value('float64'), 'threshold_fluence_J_cm2': Value('float64'), 'absorption_depth_nm': Value('float64'), 'incubation_coefficient': Value('float64'), 'refractive_index': Value('float64'), 'pulse_energy_uJ': Value('float64'), 'peak_fluence_J_cm2': Value('float64'), 'effective_pulses': Value('float64'), 'overlap_percent': Value('float64'), 'etch_depth_um': Value('float64'), 'etch_width_um': Value('float64'), 'surface_roughness_Sa_um': Value('float64'), 'aspect_ratio': Value('float64'), 'side_wall_angle_deg': Value('float64')}
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This dataset repository was generated by ML Intern, an agent for machine learning research and development on the Hugging Face Hub.
from datasets import load_dataset
dataset = load_dataset('TWLAb/femtosecond-laser-hydrogel-etching-data')