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Origin: https://github.com/dask/dask/issues/4361
Summary: Here's a temporary work-around that resolve the issue with NumPy 1.16.
See also: https://github.com/numpy/numpy/issues/12712 for discussion
about the bug.
diff --git a/dask/array/core.py b/dask/array/core.py
index 5cf0f082a..bdb31a833 100644
--- a/dask/array/core.py
+++ b/dask/array/core.py
@@ -952,6 +952,10 @@ def __array_ufunc__(self, numpy_ufunc, method, *inputs, **kwargs):
return NotImplemented
if method == '__call__':
+ if numpy_ufunc is np.matmul:
+ from .routines import matmul
+ # special case until apply_gufunc handles optional dimensions
+ return matmul(*inputs, **kwargs)
if numpy_ufunc.signature is not None:
from .gufunc import apply_gufunc
return apply_gufunc(numpy_ufunc,
diff --git a/dask/array/tests/test_array_core.py b/dask/array/tests/test_array_core.py
index 97e6b0b72..2f73688e7 100644
--- a/dask/array/tests/test_array_core.py
+++ b/dask/array/tests/test_array_core.py
@@ -857,6 +857,16 @@ def test_matmul():
assert_eq(operator.matmul(z, a), operator.matmul(c, x))
+def test_matmul_array_ufunc():
+ # regression test for https://github.com/dask/dask/issues/4353
+ x = np.random.random((5, 5))
+ y = np.random.random((5, 2))
+ a = from_array(x, chunks=(1, 5))
+ b = from_array(y, chunks=(5, 1))
+ result = b.__array_ufunc__(np.matmul, '__call__', a, b)
+ assert_eq(result, x.dot(y))
+
+
def test_T():
x = np.arange(400).reshape((20, 20))
a = from_array(x, chunks=(5, 5))
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