怎么样:

from numpy.core.umath_tests import inner1d
Z = inner1d(X,Y)

例如:

X = np.random.normal(size=(10,5))
Y = np.random.normal(size=(10,5))
Z1 = inner1d(X,Y)
Z2 = [np.dot(X[k],Y[k]) for k in range(10)]
print np.allclose(Z1,Z2)

返回True

修改，因为我没有看到问题的3D部分

Edit Correction since I didn't see the 3D part of the question

from numpy.core.umath_tests import matrix_multiply
X = np.random.normal(size=(10,5,3))
Y = np.random.normal(size=(10,3,5))
Z1 = matrix_multiply(X,Y)
Z2 = np.array([np.dot(X[k],Y[k]) for k in range(10)])
np.allclose(Z1,Z2)  # <== returns True

之所以可行，是因为(作为文档字符串状态)matrix_multiply提供了

This works because (as the docstring states), matrix_multiplyprovides

matrix_multiply(x1，x2 [，out])矩阵

matrix_multiply(x1, x2[, out]) matrix

最后两个维度上的乘法