WARNING:d3m.utils:Using global/shared random source using 'numpy.random.normal' can make execution not reproducible.
Stack (most recent call last):
File "submission/pipelines/generate_pipelines.py", line 880, in <module>
main()
File "submission/pipelines/generate_pipelines.py", line 863, in main
pipeline_run_name
File "./submission/pipelines/run_pipeline.py", line 185, in run_and_save_pipeline_for_submission
should_output_scores
File "./submission/pipelines/run_pipeline.py", line 67, in run_pipeline
cli.main(run_args)
File "/src/d3m/d3m/cli.py", line 1172, in main
handler(arguments, parser)
File "/src/d3m/d3m/cli.py", line 1057, in handler
problem_resolver=problem_resolver,
File "/src/d3m/d3m/cli.py", line 539, in runtime_handler
problem_resolver=problem_resolver,
File "/src/d3m/d3m/runtime.py", line 2534, in fit_score_handler
runtime_environment=runtime_environment,
File "/src/d3m/d3m/runtime.py", line 1323, in fit
result = runtime.fit(inputs, return_values=return_values)
File "/src/d3m/d3m/runtime.py", line 1132, in fit
return self._run(inputs, metadata_base.PipelineRunPhase.FIT, return_values)
File "/src/d3m/d3m/runtime.py", line 1039, in _run
self._do_run()
File "/src/d3m/d3m/runtime.py", line 1025, in _do_run
self._do_run_step(step)
File "/src/d3m/d3m/runtime.py", line 1008, in _do_run_step
self._run_step(step)
File "/src/d3m/d3m/runtime.py", line 998, in _run_step
self._run_primitive(step)
File "/src/d3m/d3m/runtime.py", line 873, in _run_primitive
multi_call_result = self._call_primitive_method(primitive.fit_multi_produce, fit_multi_produce_arguments)
File "/src/d3m/d3m/runtime.py", line 970, in _call_primitive_method
result = method(**arguments)
File "/src/d3m/d3m/primitive_interfaces/transformer.py", line 71, in fit_multi_produce
return self._fit_multi_produce(produce_methods=produce_methods, timeout=timeout, iterations=iterations, inputs=inputs)
File "/src/d3m/d3m/primitive_interfaces/base.py", line 568, in _fit_multi_produce
produce_results = self._multi_produce(produce_methods=produce_methods, timeout=timeout, iterations=iterations, **kwargs)
File "/src/d3m/d3m/primitive_interfaces/base.py", line 465, in _multi_produce
results.append(getattr(self, method_name)(timeout=timeout, iterations=iterations, **arguments))
File "/usr/local/lib/python3.6/dist-packages/byudml/metafeature_extraction/metafeature_extraction.py", line 217, in produce
metadata = self._produce(inputs.metadata, copy.copy(inputs))
File "/usr/local/lib/python3.6/dist-packages/byudml/metafeature_extraction/metafeature_extraction.py", line 262, in _produce
metafeatures = Metafeatures().compute(data, target_series, column_types=column_types, metafeature_ids=metalearn_metafeatures_to_compute, seed=self.random_seed)
File "/usr/local/lib/python3.6/dist-packages/metalearn/metafeatures/metafeatures.py", line 198, in compute
value, compute_time = self._get_resource(mf_id)
File "/usr/local/lib/python3.6/dist-packages/metalearn/metafeatures/metafeatures.py", line 444, in _get_resource
computed_resources = resource_computer(**args)
File "/usr/local/lib/python3.6/dist-packages/metalearn/metafeatures/base.py", line 48, in __call__
return self.computer(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/metalearn/metafeatures/statistical_metafeatures.py", line 118, in get_pca
pca_data.fit_transform(X_preprocessed.values)
File "/usr/local/lib/python3.6/dist-packages/sklearn/decomposition/_pca.py", line 369, in fit_transform
U, S, V = self._fit(X)
File "/usr/local/lib/python3.6/dist-packages/sklearn/decomposition/_pca.py", line 418, in _fit
return self._fit_truncated(X, n_components, self._fit_svd_solver)
File "/usr/local/lib/python3.6/dist-packages/sklearn/decomposition/_pca.py", line 535, in _fit_truncated
random_state=random_state)
File "/usr/local/lib/python3.6/dist-packages/sklearn/utils/extmath.py", line 348, in randomized_svd
power_iteration_normalizer, random_state)
File "/usr/local/lib/python3.6/dist-packages/sklearn/utils/extmath.py", line 213, in randomized_range_finder
Q = random_state.normal(size=(A.shape[1], size))
File "/src/d3m/d3m/utils.py", line 1137, in wrapper
stack_info=True,
File "/src/d3m/d3m/utils.py", line 1593, in log_once
logger.log(level, msg, *args, **kwargs)
