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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type
struct<beam_size: int64, max_depth: int64, nb_exec: int64>
to
{'beam_size': Value('int64'), 'max_depth': Value('int64')}
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<beam_size: int64, max_depth: int64, nb_exec: int64>
to
{'beam_size': Value('int64'), 'max_depth': Value('int64')}
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 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 1694, 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 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
parameters dict | program_annotation dict | initial_execution_time dict | schedules_list list | exploration_trace dict | program_name string | Tiramisu_cpp string |
|---|---|---|---|---|---|---|
{
"beam_size": 3,
"max_depth": 6
} | {"memory_size":"5.0078125","iterators":{"i0":{"lower_bound":"0","upper_bound":"512","parent_iterator(...TRUNCATED) | {
"xeon_e5_2695_v2": 2521.149902,
"xeon_e5_2680_v4": 149.605
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:","ISL_AST":"0|iterato(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":2521.149902,"children":[{"id":1,"schedule":"I(L0,L1)","(...TRUNCATED) | function552277 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 2,
"max_depth": 6
} | {"memory_size":"257.0","iterators":{"i0":{"lower_bound":"0","upper_bound":"512","parent_iterator":nu(...TRUNCATED) | {
"xeon_e5_2695_v2": 32.258099,
"xeon_e5_2680_v4": 23.2018
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:","ISL_AST":"0|iterato(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":32.258099,"children":[{"id":1,"schedule":"I(L0,L1)","de(...TRUNCATED) | function684979 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 2,
"max_depth": 0
} | {"memory_size":"18.050811767578125","iterators":{"i0":{"lower_bound":"1","upper_bound":"1537","paren(...TRUNCATED) | {
"xeon_e5_2695_v2": 10211.900391,
"xeon_e5_2680_v4": 13685.9
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:","ISL_AST":"0|iterato(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":10211.900391,"children":[{"id":1,"schedule":"M(2,1,0,-1(...TRUNCATED) | function745428 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 2,
"max_depth": 6
} | {"memory_size":"16.500244140625","iterators":{"i0":{"lower_bound":"0","upper_bound":"64","parent_ite(...TRUNCATED) | {
"xeon_e5_2695_v2": 6.15093,
"xeon_e5_2680_v4": 3.54637
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:","ISL_AST":"0|iterato(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":6.15093,"children":[{"id":1,"schedule":"I(L0,L1)","dept(...TRUNCATED) | function640793 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 2,
"max_depth": 4
} | {"memory_size":"9.261749267578125","iterators":{"i0":{"lower_bound":"1","upper_bound":"97","parent_i(...TRUNCATED) | {
"xeon_e5_2695_v2": 6.42414,
"xeon_e5_2680_v4": 5.96616
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:","ISL_AST":"0|iterato(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":6.42414,"children":[{"id":1,"schedule":"M(0,1,0,1,0,0,0(...TRUNCATED) | function730099 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 2,
"max_depth": 4
} | {"memory_size":"3.005859375","iterators":{"i0":{"lower_bound":"0","upper_bound":"512","parent_iterat(...TRUNCATED) | {
"xeon_e5_2695_v2": 164.501007,
"xeon_e5_2680_v4": 163.885
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:{comp01}:","ISL_AST":"(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":164.501007,"children":[{"id":0,"schedule":"","depth":1,(...TRUNCATED) | function781045 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 2,
"max_depth": 6
} | {"memory_size":"2.09375","iterators":{"i0":{"lower_bound":"1","upper_bound":"65","parent_iterator":n(...TRUNCATED) | {
"xeon_e5_2695_v2": 0.294401,
"xeon_e5_2680_v4": 0.214985
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:","ISL_AST":"0|iterato(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":0.294401,"children":[{"id":1,"schedule":"I(L0,L1)","dep(...TRUNCATED) | function677381 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 2,
"max_depth": 6
} | {"memory_size":"2.015655517578125","iterators":{"i0":{"lower_bound":"0","upper_bound":"256","parent_(...TRUNCATED) | {
"xeon_e5_2695_v2": 736.703003,
"xeon_e5_2680_v4": 586.965
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:","ISL_AST":"0|iterato(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":736.703003,"children":[{"id":0,"schedule":"","depth":1,(...TRUNCATED) | function640072 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 3,
"max_depth": 6
} | {"memory_size":"9.0","iterators":{"i0":{"lower_bound":"0","upper_bound":"256","parent_iterator":null(...TRUNCATED) | {
"xeon_e5_2695_v2": 774.460022,
"xeon_e5_2680_v4": 626.206
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"{comp00}:","ISL_AST":"0|iterato(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":774.460022,"children":[{"id":1,"schedule":"I(L0,L1)","d(...TRUNCATED) | function620762 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
{
"beam_size": 3,
"max_depth": 3
} | {"memory_size":"0.000675201416015625","iterators":{"i0":{"lower_bound":"0","upper_bound":"5","parent(...TRUNCATED) | {
"xeon_e5_2695_v2": 0.000591,
"xeon_e5_2680_v4": 0.000232
} | [{"transformations_list":[],"schedule_str":"","legacy_schedule_str":"","ISL_AST":"0|iterator|c1|0|c1(...TRUNCATED) | {"id":0,"schedule":"","depth":1,"evaluation":0.000591,"children":[{"id":1,"schedule":"F({C0,C1},L1)"(...TRUNCATED) | function1189350 | "#include <tiramisu/tiramisu.h> \n#include <tiramisu/auto_scheduler/evaluator.h>\n#include <tiramisu(...TRUNCATED) |
End of preview.
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