ValueError: buffer source array is read-only when running bench_mnist.py #15851
Description
scikit-learn version : 0.22
Tried both python: 3.7.3 and python 3.7.5, the error is the same as below:
when running python bench_mnist.py --classifiers ExtraTrees, it will report below error:
MNIST dataset benchmark
Benchmark on the MNIST dataset. The dataset comprises 70,000 samples
and 784 features. Here, we consider the task of predicting
10 classes - digits from 0 to 9 from their raw images. By contrast to the
covertype dataset, the feature space is homogenous.
Example of output :
[..]
Classification performance:
===========================
Classifier train-time test-time error-rate
------------------------------------------------------------
MLP_adam 53.46s 0.11s 0.0224
Nystroem-SVM 112.97s 0.92s 0.0228
MultilayerPerceptron 24.33s 0.14s 0.0287
ExtraTrees 42.99s 0.57s 0.0294
RandomForest 42.70s 0.49s 0.0318
SampledRBF-SVM 135.81s 0.56s 0.0486
LinearRegression-SAG 16.67s 0.06s 0.0824
CART 20.69s 0.02s 0.1219
dummy 0.00s 0.01s 0.8973
Dataset statistics:
number of features: 784
number of classes: 10
data type: float32
number of train samples: 60000 (size=188MB)
number of test samples: 10000 (size=31MB)
Training Classifiers
Training ExtraTrees ... Traceback (most recent call last):
File "bench_mnist.py", line 161, in <module>
y_pred = estimator.predict(X_test)
File "/usr/local/lib/python3.7/dist-packages/sklearn/ensemble/_forest.py", line 612, in predict
proba = self.predict_proba(X)
File "/usr/local/lib/python3.7/dist-packages/sklearn/ensemble/_forest.py", line 669, in predict_proba
for e in self.estimators_)
File "/usr/local/lib/python3.7/dist-packages/joblib/parallel.py", line 1003, in __call__
if self.dispatch_one_batch(iterator):
File "/usr/local/lib/python3.7/dist-packages/joblib/parallel.py", line 834, in dispatch_one_batch
self._dispatch(tasks)
File "/usr/local/lib/python3.7/dist-packages/joblib/parallel.py", line 753, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "/usr/local/lib/python3.7/dist-packages/joblib/_parallel_backends.py", line 201, in apply_async
result = ImmediateResult(func)
File "/usr/local/lib/python3.7/dist-packages/joblib/_parallel_backends.py", line 582, in __init__
self.results = batch()
File "/usr/local/lib/python3.7/dist-packages/joblib/parallel.py", line 256, in __call__
for func, args, kwargs in self.items]
File "/usr/local/lib/python3.7/dist-packages/joblib/parallel.py", line 256, in <listcomp>
for func, args, kwargs in self.items]
File "/usr/local/lib/python3.7/dist-packages/sklearn/ensemble/_forest.py", line 449, in _accumulate_prediction
prediction = predict(X, check_input=False)
File "/usr/local/lib/python3.7/dist-packages/sklearn/tree/_classes.py", line 908, in predict_proba
proba = self.tree_.predict(X)
File "sklearn/tree/_tree.pyx", line 768, in sklearn.tree._tree.Tree.predict
File "sklearn/tree/_tree.pyx", line 770, in sklearn.tree._tree.Tree.predict
File "sklearn/tree/_tree.pyx", line 781, in sklearn.tree._tree.Tree.apply
File "sklearn/tree/_tree.pyx", line 795, in sklearn.tree._tree.Tree._apply_dense
File "stringsource", line 658, in View.MemoryView.memoryview_cwrapper
File "stringsource", line 349, in View.MemoryView.memoryview.__cinit__
ValueError: buffer source array is read-only