抛出cp.full TypeError的CUML拟合函数

Question

我一直试图在谷歌Colab pro上运行RAPIDS，并成功地安装了cuml和cudf包，但我甚至无法运行示例脚本。

TLDR；

每当我尝试在Google Colab上运行cuml的fit函数时，我都会得到以下错误。我在使用演示示例进行安装和使用cuml时都得到了这一点。这种情况发生在一系列的cuml示例中(我第一次尝试运行UMAP时遇到了这个问题)。

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-3-c06fc2c31ca3> in <module>()
     13 knn.fit(X_train, y_train)
     14 
---> 15 knn.predict(X_test)

5 frames
cuml/neighbors/kneighbors_regressor.pyx in cuml.neighbors.kneighbors_regressor.KNeighborsRegressor.predict()

cuml/neighbors/nearest_neighbors.pyx in cuml.neighbors.nearest_neighbors.NearestNeighbors.kneighbors()

cuml/neighbors/nearest_neighbors.pyx in cuml.neighbors.nearest_neighbors.NearestNeighbors._kneighbors()

cuml/neighbors/nearest_neighbors.pyx in cuml.neighbors.nearest_neighbors.NearestNeighbors._kneighbors_dense()

/usr/local/lib/python3.7/site-packages/cuml/common/array.py in full(cls, shape, value, dtype, order)
    326         """
    327 
--> 328         return CumlArray(cp.full(shape, value, dtype, order))
    329 
    330     @classmethod

TypeError: full() takes from 2 to 3 positional arguments but 4 were given

在Google Colab Pro上采取的步骤(以重现错误)

下面是一个示例，我使用Rapids (https://colab.research.google.com/drive/1rY7Ln6rEE1pOlfSHCYOVaqt8OvDO35J0#forceEdit=true&offline=true&sandboxMode=true)中的这个示例安装了相关的包：

# Install RAPIDS
!git clone https://github.com/rapidsai/rapidsai-csp-utils.git
!bash rapidsai-csp-utils/colab/rapids-colab.sh stable

import sys, os, shutil

sys.path.append('/usr/local/lib/python3.7/site-packages/')
os.environ['NUMBAPRO_NVVM'] = '/usr/local/cuda/nvvm/lib64/libnvvm.so'
os.environ['NUMBAPRO_LIBDEVICE'] = '/usr/local/cuda/nvvm/libdevice/'
os.environ["CONDA_PREFIX"] = "/usr/local"
for so in ['cudf', 'rmm', 'nccl', 'cuml', 'cugraph', 'xgboost', 'cuspatial']:
  fn = 'lib'+so+'.so'
  source_fn = '/usr/local/lib/'+fn
  dest_fn = '/usr/lib/'+fn
  if os.path.exists(source_fn):
    print(f'Copying {source_fn} to {dest_fn}')
    shutil.copyfile(source_fn, dest_fn)
# fix for BlazingSQL import issue
# ImportError: /usr/lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.26' not found (required by /usr/local/lib/python3.7/site-packages/../../libblazingsql-engine.so)
if not os.path.exists('/usr/lib64'):
    os.makedirs('/usr/lib64')
for so_file in os.listdir('/usr/local/lib'):
  if 'libstdc' in so_file:
    shutil.copyfile('/usr/local/lib/'+so_file, '/usr/lib64/'+so_file)
    shutil.copyfile('/usr/local/lib/'+so_file, '/usr/lib/x86_64-linux-gnu/'+so_file)

然后，我尝试从cuML (https://docs.rapids.ai/api/cuml/stable/api.html#k-means-clustering)运行下面的示例

from cuml.neighbors import KNeighborsRegressor

from sklearn.datasets import make_blobs
from sklearn.model_selection import train_test_split

X, y = make_blobs(n_samples=100, centers=5,
                  n_features=10)

knn = KNeighborsRegressor(n_neighbors=10)

X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.80)

knn.fit(X_train, y_train)

knn.predict(X_test)

这将导致问题开头出现错误。

Answer 1

尽管conda在快速安装过程中安装了cupy==8.6.0，但Colab仍保留cupy==7.4.0。这是一个自定义安装。在安装RAPIDS之前，我刚刚成功地安装了cupy-cuda110==8.6.0，

!pip install cupy-cuda110==8.6.0

我很快就会更新脚本，这样你就不需要手动完成了，而是想测试更多的东西。再次感谢您让我们知道！

编辑:脚本已更新。