Erro

gistfile1.txt

INFO: [pid 14484] Worker Worker(salt=140992192, workers=1, host=ufgdeepfood.RadSquare.cloud, username=fernando, pid=14484) running   EvaluateIfoodModel(model_module=recommendation.task.model.m
atrix_factorization, model_cls=MatrixFactorizationTraining, model_task_id=MatrixFactorizationTraining____500_False_4bb5a61c77, limit_list_size=50, nofilter_iteractions_test=False, task_hash=no
ne, num_processes=16, bandit_policy=none, bandit_policy_params={}, bandit_weights=none, batch_size=100000, plot_histogram=False, no_offpolicy_eval=False)
2020-01-23 13:36:38,335 : INFO : [pid 14484] Worker Worker(salt=140992192, workers=1, host=ufgdeepfood.RadSquare.cloud, username=fernando, pid=14484) running   EvaluateIfoodModel(model_module=
recommendation.task.model.matrix_factorization, model_cls=MatrixFactorizationTraining, model_task_id=MatrixFactorizationTraining____500_False_4bb5a61c77, limit_list_size=50, nofilter_iteractio
ns_test=False, task_hash=none, num_processes=16, bandit_policy=none, bandit_policy_params={}, bandit_weights=none, batch_size=100000, plot_histogram=False, no_offpolicy_eval=False)
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ERROR: [pid 14484] Worker Worker(salt=140992192, workers=1, host=ufgdeepfood.RadSquare.cloud, username=fernando, pid=14484) failed    EvaluateIfoodModel(model_module=recommendation.task.model.
matrix_factorization, model_cls=MatrixFactorizationTraining, model_task_id=MatrixFactorizationTraining____500_False_4bb5a61c77, limit_list_size=50, nofilter_iteractions_test=False, task_hash=n
one, num_processes=16, bandit_policy=none, bandit_policy_params={}, bandit_weights=none, batch_size=100000, plot_histogram=False, no_offpolicy_eval=False)
Traceback (most recent call last):
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 384, in __init__
    codes, categories = factorize(values, sort=True)
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/util/_decorators.py", line 208, in wrapper
    return func(*args, **kwargs)
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/algorithms.py", line 672, in factorize
    values, na_sentinel=na_sentinel, size_hint=size_hint, na_value=na_value
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/algorithms.py", line 508, in _factorize_array
    values, na_sentinel=na_sentinel, na_value=na_value
  File "pandas/_libs/hashtable_class_helper.pxi", line 1798, in pandas._libs.hashtable.PyObjectHashTable.factorize
  File "pandas/_libs/hashtable_class_helper.pxi", line 1718, in pandas._libs.hashtable.PyObjectHashTable._unique
TypeError: unhashable type: 'list'

During handling of the above exception, another exception occurred:   

Traceback (most recent call last):
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/luigi/worker.py", line 203, in run
      new_deps = self._run_get_new_deps()
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/luigi/worker.py", line 140, in _run_get_new_deps
    task_gen = self.task.run()
  File "/home/fernando/recommendation-system/recommendation/task/ifood.py", line 605, in run
    "personalization_at_15": self._mean_personalization(df, 15),
  File "/home/fernando/recommendation-system/recommendation/task/ifood.py", line 540, in _mean_personalization
    personalization_per_shift.append(personalization_at_k(group_df["sorted_merchant_idx_list"], k))
  File "/home/fernando/recommendation-system/recommendation/rank_metrics.py", line 288, in personalization_at_k
    return personalization(_get_predicted_at_k(predicted, k))
  File "/home/fernando/recommendation-system/recommendation/rank_metrics.py", line 264, in personalization
    rec_matrix_sparse = make_rec_matrix(predicted)
  File "/home/fernando/recommendation-system/recommendation/rank_metrics.py", line 256, in make_rec_matrix
    df = df[['index', 'item']].pivot(index='index', columns='item', values='item')
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/frame.py", line 5919, in pivot
    return pivot(self, index=index, columns=columns, values=values)   
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/reshape/pivot.py", line 421, in pivot
    index = MultiIndex.from_arrays([index, data[columns]])
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/indexes/multi.py", line 420, in from_arrays
    codes, levels = _factorize_from_iterables(arrays)
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 2816, in _factorize_from_iterables
    return map(list, zip(*(_factorize_from_iterable(it) for it in iterables)))
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 2816, in <genexpr>
    return map(list, zip(*(_factorize_from_iterable(it) for it in iterables)))
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 2788, in _factorize_from_iterable
    cat = Categorical(values, ordered=False)
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 386, in __init__
    codes, categories = factorize(values, sort=False)
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/util/_decorators.py", line 208, in wrapper
    return func(*args, **kwargs)
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/algorithms.py", line 672, in factorize
    values, na_sentinel=na_sentinel, size_hint=size_hint, na_value=na_value
  File "/opt/anaconda3/envs/recommendation-system/lib/python3.6/site-packages/pandas/core/algorithms.py", line 508, in _factorize_array
    values, na_sentinel=na_sentinel, na_value=na_value
  File "pandas/_libs/hashtable_class_helper.pxi", line 1798, in pandas._libs.hashtable.PyObjectHashTable.factorize
  File "pandas/_libs/hashtable_class_helper.pxi", line 1718, in pandas._libs.hashtable.PyObjectHashTable._unique
TypeError: unhashable type: 'list'