test failures in test_unsupervised_grid_search

[mrocklin]

from tests.model_selection.dask_searchcv.test_model_selection_sklearn import test_unsupervised_grid_search
for i in range(1000): print(i); test_unsupervised_grid_search()

```python-traceback --------------------------------------------------------------------------- IndexError Traceback (most recent call last) in () ----> 1 for i in range(1000): print(i); test_unsupervised_grid_search() /home/mrocklin/workspace/dask-ml/tests/model_selection/dask_searchcv/test_model_selection_sklearn.pyc in test_unsupervised_grid_search() 603 km, param_grid=dict(n_clusters=[2, 3, 4]), scoring="adjusted_rand_score" 604 ) --> 605 grid_search.fit(X, y) 606 # ARI can find the right number :) 607 assert grid_search.best_params_["n_clusters"] == 3 /home/mrocklin/workspace/dask-ml/dask_ml/model_selection/_search.pyc in fit(self, X, y, groups, **fit_params) 1198 scheduler = dask.local.get_sync 1199 -> 1200 out = scheduler(dsk, keys, num_workers=n_jobs) 1201 1202 results = handle_deprecated_train_score(out[0], self.return_train_score) /home/mrocklin/workspace/dask/dask/threaded.pyc in get(dsk, result, cache, num_workers, **kwargs) 73 results = get_async(pool.apply_async, len(pool._pool), dsk, result, 74 cache=cache, get_id=_thread_get_id, ---> 75 pack_exception=pack_exception, **kwargs) 76 77 # Cleanup pools associated to dead threads /home/mrocklin/workspace/dask/dask/local.pyc in get_async(apply_async, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, **kwargs) 499 _execute_task(task, data) # Re-execute locally 500 else: --> 501 raise_exception(exc, tb) 502 res, worker_id = loads(res_info) 503 state['cache'][key] = res /home/mrocklin/workspace/dask/dask/local.pyc in execute_task(key, task_info, dumps, loads, get_id, pack_exception) 270 try: 271 task, data = loads(task_info) --> 272 result = _execute_task(task, data) 273 id = get_id() 274 result = dumps((result, id)) /home/mrocklin/workspace/dask/dask/local.pyc in _execute_task(arg, cache, dsk) 251 func, args = arg[0], arg[1:] 252 args2 = [_execute_task(a, cache) for a in args] --> 253 return func(*args2) 254 elif not ishashable(arg): 255 return arg /home/mrocklin/workspace/dask-ml/dask_ml/model_selection/methods.pyc in fit_and_score(est, cv, X, y, n, scorer, error_score, fields, params, fit_params, return_train_score) 319 X_test = cv.extract(X, y, n, True, False) 320 y_test = cv.extract(X, y, n, False, False) --> 321 est_and_time = fit(est, X_train, y_train, error_score, fields, params, fit_params) 322 if not return_train_score: 323 X_train = y_train = None /home/mrocklin/workspace/dask-ml/dask_ml/model_selection/methods.pyc in fit(est, X, y, error_score, fields, params, fit_params) 239 try: 240 est = set_params(est, fields, params) --> 241 est.fit(X, y, **fit_params) 242 except Exception as e: 243 if error_score == "raise": /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/sklearn/cluster/k_means_.pyc in fit(self, X, y, sample_weight) 966 tol=self.tol, random_state=random_state, copy_x=self.copy_x, 967 n_jobs=self.n_jobs, algorithm=self.algorithm, --> 968 return_n_iter=True) 969 return self 970 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/sklearn/cluster/k_means_.pyc in k_means(X, n_clusters, sample_weight, init, precompute_distances, n_init, max_iter, verbose, tol, random_state, copy_x, n_jobs, algorithm, return_n_iter) 378 verbose=verbose, precompute_distances=precompute_distances, 379 tol=tol, x_squared_norms=x_squared_norms, --> 380 random_state=random_state) 381 # determine if these results are the best so far 382 if best_inertia is None or inertia < best_inertia: /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/sklearn/cluster/k_means_.pyc in _kmeans_single_elkan(X, sample_weight, n_clusters, max_iter, init, verbose, x_squared_norms, random_state, tol, precompute_distances) 434 # init 435 centers = _init_centroids(X, n_clusters, init, random_state=random_state, --> 436 x_squared_norms=x_squared_norms) 437 centers = np.ascontiguousarray(centers) 438 if verbose: /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/sklearn/cluster/k_means_.pyc in _init_centroids(X, k, init, random_state, x_squared_norms, init_size) 746 if isinstance(init, string_types) and init == 'k-means++': 747 centers = _k_init(X, k, random_state=random_state, --> 748 x_squared_norms=x_squared_norms) 749 elif isinstance(init, string_types) and init == 'random': 750 seeds = random_state.permutation(n_samples)[:k] /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/sklearn/cluster/k_means_.pyc in _k_init(X, n_clusters, x_squared_norms, random_state, n_local_trials) 137 centers[c] = X[best_candidate].toarray() 138 else: --> 139 centers[c] = X[best_candidate] 140 current_pot = best_pot 141 closest_dist_sq = best_dist_sq IndexError: index 4634920304854618928 is out of bounds for axis 0 with size 67 ```

``` /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x79e5)[0x7fee6dfda645] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x6852)[0x7fee6dfd94b2] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x6852)[0x7fee6dfd94b2] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x6852)[0x7fee6dfd94b2] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x6852)[0x7fee6dfd94b2] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(+0x6d0f7)[0x7fee6df650f7] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7fee6df407a3] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x28a0)[0x7fee6dfd5500] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x6852)[0x7fee6dfd94b2] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(+0x6d00a)[0x7fee6df6500a] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7fee6df407a3] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x28a0)[0x7fee6dfd5500] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x6852)[0x7fee6dfd94b2] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(+0x6d0f7)[0x7fee6df650f7] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7fee6df407a3] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x28a0)[0x7fee6dfd5500] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(+0x6d0f7)[0x7fee6df650f7] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7fee6df407a3] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x28a0)[0x7fee6dfd5500] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x817c)[0x7fee6dfdaddc] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x817c)[0x7fee6dfdaddc] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x7e9)[0x7fee6dfdc519] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(+0x6d00a)[0x7fee6df6500a] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7fee6df407a3] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(+0x5753d)[0x7fee6df4f53d] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7fee6df407a3] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(PyEval_CallObjectWithKeywords+0x48)[0x7fee6dfd2708] /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0(+0x113d76)[0x7fee6e00bd76] /lib/x86_64-linux-gnu/libpthread.so.0(+0x76ba)[0x7fee6dce26ba] /lib/x86_64-linux-gnu/libc.so.6(clone+0x6d)[0x7fee6d30841d] ======= Memory map: ======== 55bb8406d000-55bb8406e000 r-xp 00000000 fd:01 32135796 /home/mrocklin/Software/anaconda/envs/27/bin/python2.7 55bb8426d000-55bb8426e000 r--p 00000000 fd:01 32135796 /home/mrocklin/Software/anaconda/envs/27/bin/python2.7 55bb8426e000-55bb8426f000 rw-p 00001000 fd:01 32135796 /home/mrocklin/Software/anaconda/envs/27/bin/python2.7 55bb8483e000-55bb86c65000 rw-p 00000000 00:00 0 [heap] 7fee1c000000-7fee1c021000 rw-p 00000000 00:00 0 7fee1c021000-7fee20000000 ---p 00000000 00:00 0 7fee204c8000-7fee23de5000 r-xp 00000000 fd:01 23158272 /home/mrocklin/Software/anaconda/envs/27/lib/libmkl_avx2.so 7fee23de5000-7fee23fe5000 ---p 0391d000 fd:01 23158272 /home/mrocklin/Software/anaconda/envs/27/lib/libmkl_avx2.so 7fee23fe5000-7fee23fec000 r--p 0391d000 fd:01 23158272 /home/mrocklin/Software/anaconda/envs/27/lib/libmkl_avx2.so 7fee23fec000-7fee23ffb000 rw-p 03924000 fd:01 23158272 /home/mrocklin/Software/anaconda/envs/27/lib/libmkl_avx2.so 7fee23ffb000-7fee24000000 rw-p 00000000 00:00 0 7fee24000000-7fee24021000 rw-p 00000000 00:00 0 7fee24021000-7fee28000000 ---p 00000000 00:00 0 7fee28000000-7fee28021000 rw-p 00000000 00:00 0 7fee28021000-7fee2c000000 ---p 00000000 00:00 0 7fee2c000000-7fee2c021000 rw-p 00000000 00:00 0 7fee2c021000-7fee30000000 ---p 00000000 00:00 0 7fee30000000-7fee30021000 rw-p 00000000 00:00 0 7fee30021000-7fee34000000 ---p 00000000 00:00 0 7fee340f7000-7fee340f8000 ---p 00000000 00:00 0 7fee340f8000-7fee35a54000 rw-p 00000000 00:00 0 7fee35a54000-7fee365e5000 r-xp 00000000 fd:01 23158260 /home/mrocklin/Software/anaconda/envs/27/lib/libmkl_vml_avx2.so 7fee365e5000-7fee367e4000 ---p 00b91000 fd:01 23158260 /home/mrocklin/Software/anaconda/envs/27/lib/libmkl_vml_avx2.so 7fee367e4000-7fee367e7000 r--p 00b90000 fd:01 23158260 /home/mrocklin/Software/anaconda/envs/27/lib/libmkl_vml_avx2.so 7fee367e7000-7fee367fc000 rw-p 00b93000 fd:01 23158260 /home/mrocklin/Software/anaconda/envs/27/lib/libmkl_vml_avx2.so 7fee367fc000-7fee367fd000 rw-p 00000000 00:00 0 7fee367fd000-7fee367fe000 ---p 00000000 00:00 0 7fee367fe000-7fee36ffe000 rw-p 00000000 00:00 0 7fee36ffe000-7fee36fff000 ---p 00000000 00:00 0 7fee36fff000-7fee377ff000 rw-p 00000000 00:00 0 7fee377ff000-7fee37800000 ---p 00000000 00:00 0 7fee37800000-7fee38000000 rw-p 00000000 00:00 0 7fee38000000-7fee38024000 rw-p 00000000 00:00 0 7fee38024000-7fee3c000000 ---p 00000000 00:00 0 7fee3c013000-7fee3c2a3000 rw-p 00000000 00:00 0 7fee3c2a3000-7fee3c2a4000 ---p 00000000 00:00 0 7fee3c2a4000-7fee3caa4000 rw-p 00000000 00:00 0 7fee3caa4000-7fee3caa5000 ---p 00000000 00:00 0 7fee3caa5000-7fee3d565000 rw-p 00000000 00:00 0 7fee3d565000-7fee3d57c000 r-xp 00000000 fd:01 32143455 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/msgpack/_unpacker.so 7fee3d57c000-7fee3d77c000 ---p 00017000 fd:01 32143455 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/msgpack/_unpacker.so 7fee3d77c000-7fee3d77f000 rw-p 00017000 fd:01 32143455 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/msgpack/_unpacker.so 7fee3d77f000-7fee3d792000 r-xp 00000000 fd:01 32143454 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/msgpack/_packer.so 7fee3d792000-7fee3d992000 ---p 00013000 fd:01 32143454 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/msgpack/_packer.so 7fee3d992000-7fee3d994000 rw-p 00013000 fd:01 32143454 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/msgpack/_packer.so 7fee3d994000-7fee3d9c8000 r-xp 00000000 fd:01 44716240 /home/mrocklin/Software/anaconda/envs/27/lib/libtinfow.so.6.0 7fee3d9c8000-7fee3dbc7000 ---p 00034000 fd:01 44716240 /home/mrocklin/Software/anaconda/envs/27/lib/libtinfow.so.6.0 7fee3dbc7000-7fee3dbcb000 r--p 00033000 fd:01 44716240 /home/mrocklin/Software/anaconda/envs/27/lib/libtinfow.so.6.0 7fee3dbcb000-7fee3dbcc000 rw-p 00037000 fd:01 44716240 /home/mrocklin/Software/anaconda/envs/27/lib/libtinfow.so.6.0 7fee3dbcc000-7fee3dbcd000 rw-p 00000000 00:00 0 7fee3dbcd000-7fee3dc02000 r-xp 00000000 fd:01 22638004 /home/mrocklin/Software/anaconda/envs/27/lib/libncursesw.so.6.0 7fee3dc02000-7fee3de01000 ---p 00035000 fd:01 22638004 /home/mrocklin/Software/anaconda/envs/27/lib/libncursesw.so.6.0 7fee3de01000-7fee3de02000 r--p 00034000 fd:01 22638004 /home/mrocklin/Software/anaconda/envs/27/lib/libncursesw.so.6.0 7fee3de02000-7fee3de03000 rw-p 00035000 fd:01 22638004 /home/mrocklin/Software/anaconda/envs/27/lib/libncursesw.so.6.0 7fee3de03000-7fee3de16000 r-xp 00000000 fd:01 32002349 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/lib-dynload/_curses.so 7fee3de16000-7fee3e015000 ---p 00013000 fd:01 32002349 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/lib-dynload/_curses.so 7fee3e015000-7fee3e016000 r--p 00012000 fd:01 32002349 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/lib-dynload/_curses.so 7fee3e016000-7fee3e018000 rw-p 00013000 fd:01 32002349 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/lib-dynload/_curses.so 7fee3e018000-7fee3e1d8000 rw-p 00000000 00:00 0 7fee3e1d8000-7fee3e1e9000 r-xp 00000000 fd:01 32000155 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/testing.so 7fee3e1e9000-7fee3e3e9000 ---p 00011000 fd:01 32000155 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/testing.so 7fee3e3e9000-7fee3e3ea000 r--p 00011000 fd:01 32000155 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/testing.so 7fee3e3ea000-7fee3e3eb000 rw-p 00012000 fd:01 32000155 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/testing.so 7fee3e3eb000-7fee3e42c000 rw-p 00000000 00:00 0 7fee3e42c000-7fee3e42e000 r-xp 00000000 fd:01 31999742 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/util/_move.so 7fee3e42e000-7fee3e62d000 ---p 00002000 fd:01 31999742 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/util/_move.so 7fee3e62d000-7fee3e62e000 r--p 00001000 fd:01 31999742 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/util/_move.so 7fee3e62e000-7fee3e62f000 rw-p 00002000 fd:01 31999742 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/util/_move.so 7fee3e62f000-7fee3e644000 r-xp 00000000 fd:01 32000224 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/io/msgpack/_unpacker.so 7fee3e644000-7fee3e843000 ---p 00015000 fd:01 32000224 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/io/msgpack/_unpacker.so 7fee3e843000-7fee3e844000 r--p 00014000 fd:01 32000224 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/io/msgpack/_unpacker.so 7fee3e844000-7fee3e846000 rw-p 00015000 fd:01 32000224 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/io/msgpack/_unpacker.so 7fee3e846000-7fee3e858000 r-xp 00000000 fd:01 32000160 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/io/msgpack/_packer.so 7fee3e858000-7fee3ea57000 ---p 00012000 fd:01 32000160 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/io/msgpack/_packer.so 7fee3ea57000-7fee3ea58000 r--p 00011000 fd:01 32000160 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/io/msgpack/_packer.so 7fee3ea58000-7fee3ea59000 rw-p 00012000 fd:01 32000160 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/io/msgpack/_packer.so 7fee3ea59000-7fee3eb5a000 rw-p 00000000 00:00 0 7fee3eb5a000-7fee3eb70000 r-xp 00000000 fd:01 32000218 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/json.so 7fee3eb70000-7fee3ed6f000 ---p 00016000 fd:01 32000218 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/json.so 7fee3ed6f000-7fee3ed70000 r--p 00015000 fd:01 32000218 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/json.so 7fee3ed70000-7fee3ed71000 rw-p 00016000 fd:01 32000218 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/json.so 7fee3ed71000-7fee3edf3000 r-xp 00000000 fd:01 32000297 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/parsers.so 7fee3edf3000-7fee3eff2000 ---p 00082000 fd:01 32000297 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/parsers.so 7fee3eff2000-7fee3eff3000 r--p 00081000 fd:01 32000297 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/parsers.so 7fee3eff3000-7fee3eff9000 rw-p 00082000 fd:01 32000297 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/parsers.so 7fee3eff9000-7fee3f07a000 rw-p 00000000 00:00 0 7fee3f07a000-7fee3f095000 r-xp 00000000 fd:01 32000252 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/reshape.so 7fee3f095000-7fee3f294000 ---p 0001b000 fd:01 32000252 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/reshape.so 7fee3f294000-7fee3f295000 r--p 0001a000 fd:01 32000252 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/reshape.so 7fee3f295000-7fee3f297000 rw-p 0001b000 fd:01 32000252 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/reshape.so 7fee3f297000-7fee3f2d8000 rw-p 00000000 00:00 0 7fee3f2d8000-7fee3f37c000 r-xp 00000000 fd:01 32000300 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/groupby.so 7fee3f37c000-7fee3f57b000 ---p 000a4000 fd:01 32000300 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/groupby.so 7fee3f57b000-7fee3f57c000 r--p 000a3000 fd:01 32000300 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/groupby.so 7fee3f57c000-7fee3f582000 rw-p 000a4000 fd:01 32000300 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/groupby.so 7fee3f582000-7fee3f5c3000 rw-p 00000000 00:00 0 7fee3f5c3000-7fee3f666000 r-xp 00000000 fd:01 32000301 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/window.so 7fee3f666000-7fee3f865000 ---p 000a3000 fd:01 32000301 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/window.so 7fee3f865000-7fee3f866000 r--p 000a2000 fd:01 32000301 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/window.so 7fee3f866000-7fee3f86d000 rw-p 000a3000 fd:01 32000301 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/window.so 7fee3f86d000-7fee3f8ee000 rw-p 00000000 00:00 0 7fee3f8ee000-7fee3f917000 r-xp 00000000 fd:01 23205235 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/matplotlib/_path.so 7fee3f917000-7fee3fb17000 ---p 00029000 fd:01 23205235 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/matplotlib/_path.so 7fee3fb17000-7fee3fb18000 r--p 00029000 fd:01 23205235 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/matplotlib/_path.so 7fee3fb18000-7fee3fb19000 rw-p 0002a000 fd:01 23205235 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/matplotlib/_path.so 7fee3fb19000-7fee3fd59000 rw-p 00000000 00:00 0 7fee3fd59000-7fee3fd5d000 r-xp 00000000 fd:01 23204227 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/_posixsubprocess32.so 7fee3fd5d000-7fee3ff5c000 ---p 00004000 fd:01 23204227 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/_posixsubprocess32.so 7fee3ff5c000-7fee3ff5d000 r--p 00003000 fd:01 23204227 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/_posixsubprocess32.so 7fee3ff5d000-7fee3ff5e000 rw-p 00004000 fd:01 23204227 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/_posixsubprocess32.so 7fee3ff5e000-7fee4005e000 rw-p 00000000 00:00 0 7fee4005e000-7fee40144000 r-xp 00000000 fd:01 32000302 /home/mrocklin/Software/anaconda/envs/27/lib/python2.7/site-packages/pandas/_libs/sparse.soAborted (core dumped) ```

[mrocklin]

This is under Python 2.7

I'm now running this under Python 3.6 to see if it fails there and also under 2.7 with gdb

[mrocklin]

With gdb:

(gdb) where
#0  0x00007ffff6d38428 in __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:54
#1  0x00007ffff6d3a02a in __GI_abort () at abort.c:89
#2  0x00007ffff6d802e8 in __malloc_assert (
    assertion=assertion@entry=0x7ffff6e94488 "!victim || chunk_is_mmapped (mem2chunk (victim)) || ar_ptr == arena_for_chunk (mem2chunk (victim))", file=file@entry=0x7ffff6e90bc5 "malloc.c", line=line@entry=2927, 
    function=function@entry=0x7ffff6e94978 <__func__.11586> "__libc_malloc") at malloc.c:301
#3  0x00007ffff6d872ce in __GI___libc_malloc (bytes=48) at malloc.c:2926
#4  0x00007ffff6d87a18 in __GI___libc_realloc (oldmem=0x0, bytes=48) at malloc.c:2994
#5  0x00007ffff7a6a758 in list_resize ()
   from /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0
#6  0x00007ffff7a6b978 in listextend ()
   from /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0
#7  0x00007ffff7a6ba89 in list_inplace_concat ()
   from /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0
#8  0x00007ffff7ad9cbd in PyEval_EvalFrameEx ()
   from /home/mrocklin/Software/anaconda/envs/27/bin/../lib/libpython2.7.so.1.0

Some sort of malloc failure when resizing a Python list

[mrocklin]

I am so far unable to reproduce this in Python 3, so I'm inclined to just ignore this

[TomAugspurger]

+1 for ignoring.

[jrbourbeau]

FWIW I was able to reproduce the error on Python 3.6

``` --------------------------------------------------------------------------- IndexError Traceback (most recent call last) in () ----> 1 for i in range(1000): print(i); test_unsupervised_grid_search() ~/github/dask/dask-ml/tests/model_selection/dask_searchcv/test_model_selection_sklearn.py in test_unsupervised_grid_search() 609 # Now without a score, and without y 610 grid_search = dcv.GridSearchCV(km, param_grid=dict(n_clusters=[2, 3, 4])) --> 611 grid_search.fit(X) 612 assert grid_search.best_params_["n_clusters"] == 4 613 ~/github/dask/dask-ml/dask_ml/model_selection/_search.py in fit(self, X, y, groups, **fit_params) 1198 scheduler = dask.local.get_sync 1199 -> 1200 out = scheduler(dsk, keys, num_workers=n_jobs) 1201 1202 results = handle_deprecated_train_score(out[0], self.return_train_score) ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/dask/threaded.py in get(dsk, result, cache, num_workers, **kwargs) 73 results = get_async(pool.apply_async, len(pool._pool), dsk, result, 74 cache=cache, get_id=_thread_get_id, ---> 75 pack_exception=pack_exception, **kwargs) 76 77 # Cleanup pools associated to dead threads ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/dask/local.py in get_async(apply_async, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, **kwargs) 499 _execute_task(task, data) # Re-execute locally 500 else: --> 501 raise_exception(exc, tb) 502 res, worker_id = loads(res_info) 503 state['cache'][key] = res ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/dask/compatibility.py in reraise(exc, tb) 110 if exc.__traceback__ is not tb: 111 raise exc.with_traceback(tb) --> 112 raise exc 113 114 else: ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/dask/local.py in execute_task(key, task_info, dumps, loads, get_id, pack_exception) 270 try: 271 task, data = loads(task_info) --> 272 result = _execute_task(task, data) 273 id = get_id() 274 result = dumps((result, id)) ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/dask/local.py in _execute_task(arg, cache, dsk) 251 func, args = arg[0], arg[1:] 252 args2 = [_execute_task(a, cache) for a in args] --> 253 return func(*args2) 254 elif not ishashable(arg): 255 return arg ~/github/dask/dask-ml/dask_ml/model_selection/methods.py in fit_and_score(est, cv, X, y, n, scorer, error_score, fields, params, fit_params, return_train_score) 319 X_test = cv.extract(X, y, n, True, False) 320 y_test = cv.extract(X, y, n, False, False) --> 321 est_and_time = fit(est, X_train, y_train, error_score, fields, params, fit_params) 322 if not return_train_score: 323 X_train = y_train = None ~/github/dask/dask-ml/dask_ml/model_selection/methods.py in fit(est, X, y, error_score, fields, params, fit_params) 239 try: 240 est = set_params(est, fields, params) --> 241 est.fit(X, y, **fit_params) 242 except Exception as e: 243 if error_score == "raise": ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/sklearn/cluster/k_means_.py in fit(self, X, y, sample_weight) 966 tol=self.tol, random_state=random_state, copy_x=self.copy_x, 967 n_jobs=self.n_jobs, algorithm=self.algorithm, --> 968 return_n_iter=True) 969 return self 970 ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/sklearn/cluster/k_means_.py in k_means(X, n_clusters, sample_weight, init, precompute_distances, n_init, max_iter, verbose, tol, random_state, copy_x, n_jobs, algorithm, return_n_iter) 378 verbose=verbose, precompute_distances=precompute_distances, 379 tol=tol, x_squared_norms=x_squared_norms, --> 380 random_state=random_state) 381 # determine if these results are the best so far 382 if best_inertia is None or inertia < best_inertia: ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/sklearn/cluster/k_means_.py in _kmeans_single_elkan(X, sample_weight, n_clusters, max_iter, init, verbose, x_squared_norms, random_state, tol, precompute_distances) 434 # init 435 centers = _init_centroids(X, n_clusters, init, random_state=random_state, --> 436 x_squared_norms=x_squared_norms) 437 centers = np.ascontiguousarray(centers) 438 if verbose: ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/sklearn/cluster/k_means_.py in _init_centroids(X, k, init, random_state, x_squared_norms, init_size) 746 if isinstance(init, string_types) and init == 'k-means++': 747 centers = _k_init(X, k, random_state=random_state, --> 748 x_squared_norms=x_squared_norms) 749 elif isinstance(init, string_types) and init == 'random': 750 seeds = random_state.permutation(n_samples)[:k] ~/miniconda/envs/dask-ml-dev/lib/python3.6/site-packages/sklearn/cluster/k_means_.py in _k_init(X, n_clusters, x_squared_norms, random_state, n_local_trials) 115 # Compute distances to center candidates 116 distance_to_candidates = euclidean_distances( --> 117 X[candidate_ids], X, Y_norm_squared=x_squared_norms, squared=True) 118 119 # Decide which candidate is the best IndexError: index 67 is out of bounds for axis 0 with size 67 ```