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[python-package] use toarray() instead of todense() in tests and examples #4446

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Jul 6, 2021
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[python-package] use toarray() instead of todense() in tests and examples #4446

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2 changes: 1 addition & 1 deletion examples/python-guide/dask/ranking.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@

# make this array dense because we're splitting across
# a sparse boundary to partition the data
X = X.todense()
X = X.toarray()

dX = da.from_array(
x=X,
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4 changes: 2 additions & 2 deletions tests/python_package_test/test_engine.py
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Expand Up @@ -1087,7 +1087,7 @@ def test_contribs_sparse_multiclass():
# convert data to dense and get back same contribs
contribs_dense = gbm.predict(X_test.toarray(), pred_contrib=True)
# validate the values are the same
contribs_csr_array = np.swapaxes(np.array([sparse_array.todense() for sparse_array in contribs_csr]), 0, 1)
contribs_csr_array = np.swapaxes(np.array([sparse_array.toarray() for sparse_array in contribs_csr]), 0, 1)
contribs_csr_arr_re = contribs_csr_array.reshape((contribs_csr_array.shape[0],
contribs_csr_array.shape[1] * contribs_csr_array.shape[2]))
if platform.machine() == 'aarch64':
Expand All @@ -1103,7 +1103,7 @@ def test_contribs_sparse_multiclass():
for perclass_contribs_csc in contribs_csc:
assert isspmatrix_csc(perclass_contribs_csc)
# validate the values are the same
contribs_csc_array = np.swapaxes(np.array([sparse_array.todense() for sparse_array in contribs_csc]), 0, 1)
contribs_csc_array = np.swapaxes(np.array([sparse_array.toarray() for sparse_array in contribs_csc]), 0, 1)
contribs_csc_array = contribs_csc_array.reshape((contribs_csc_array.shape[0],
contribs_csc_array.shape[1] * contribs_csc_array.shape[2]))
if platform.machine() == 'aarch64':
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