def test_transpose(): combo_check(np.transpose, [0],
[npr.randn(2, 3, 4)],
axes = [None, [0, 1, 2], [0, 2, 1],
[2, 0, 1], [2, 1, 0],
[1, 0, 2], [1, 2, 0]])
R = npr.randn
def test_convolve_ignore(): combo_check(autograd.scipy.signal.convolve, [0, 1],
[R(4, 3)], [R(3, 2)],
axes=[([0],[0]), ([1],[1]), ([0],[1]), ([1],[0]),
([0, 1], [0, 1]), ([1, 0], [1, 0])],
mode=['full', 'valid'])
def test_convolve_ignore_dot(): combo_check(autograd.scipy.signal.convolve, [0, 1],
def test_tensordot_4(): combo_check(np.tensordot, [0, 1],
[R(2, 2), R(4, 2, 2)],
[R(2, 2), R(2, 2, 4)],
axes=[1, 2])
# Need custom tests because gradient is undefined when arguments are identical.
def test_maximum(): combo_check(np.maximum, [0, 1],
def test_tensordot_3():
combo_check(
np.tensordot,
[0, 1],
[R(2, 3), R(2, 3, 4)],
[R(1, 2, 3), R(2, 2, 3, 4)],
axes=[[(0, 1), (1, 2)], [(1, 0), (2, 1)]],
)
def test_select():
combo_check(
np.select,
[1],
[[R(3, 4, 5) > 0, R(3, 4, 5) > 0, R(3, 4, 5) > 0]],
[[R(3, 4, 5), R(3, 4, 5), R(3, 4, 5)]],
default=[0.0, 1.1],
)
def test_convolve_2d():
combo_check(
autograd.scipy.signal.convolve,
[0, 1],
[R(4, 3), R(5, 4), R(6, 7)],
[R(2, 2), R(3, 2), R(4, 2), R(4, 1)],
mode=["full", "valid"],
)
def test_convolve_ignore_dot(): combo_check(autograd.scipy.signal.convolve, [0, 1],
[R(3, 3, 2)], [R(3, 2, 3)],
axes=[([1],[1])],
dot_axes=[([0],[2]), ([0],[0])],
mode=['full', 'valid'])
### Special ###
def test_polygamma():
def test_logsumexp5():
combo_check(
autograd.scipy.misc.logsumexp,
[0],
[R(2, 3, 4)],
b=[np.exp(R(2, 3, 4))],
axis=[None, 0, 1],
keepdims=[True, False],
)
def test_convolve_ignore():
combo_check(
autograd.scipy.signal.convolve,
[0, 1],
[R(4, 3)],
[R(3, 2)],
axes=[([0], [0]), ([1], [1]), ([0], [1]), ([1], [0]), ([0, 1], [0, 1]), ([1, 0], [1, 0])],
mode=["full", "valid"],
)
def test_convolve2d(): combo_check(autograd.scipy.signal.convolve2d, [0, 1],
[R(4, 3), R(5, 4), R(6, 7)],
[R(2, 2), R(3, 2), R(4, 3)],
mode=['full', 'valid', 'same'])
### Special ###
def test_polygamma():
def test_concatenate_3d(): combo_check(np.concatenate, [0], [(R(2, 2, 2), R(2, 2, 2))], axis=[0, 1, 2]) # def test_vstack_1d(): combo_check(np.vstack, [0], [R(2), (R(2), R(2))]) # def test_vstack_2d(): combo_check(np.vstack, [0], [R(2, 3), (R(2, 4), R(1, 4))]) # def test_vstack_3d(): combo_check(np.vstack, [0], [R(2, 3, 4), (R(2, 3, 4), R(5, 3, 4))]) # def test_hstack_2d(): combo_check(np.hstack, [0], [R(2, 3), (R(2, 4), R(1, 4))]) # def test_hstack_3d(): combo_check(np.hstack, [0], [R(2, 3, 4), (R(2, 1, 4), R(2, 5, 4))]) # def test_dstack_3d(): combo_check(np.dstack, [0], [R(2, 3, 4), (R(2, 3, 1), R(2, 3, 5))]) def test_select(): combo_check(np.select, [1], [[R(3,4,5) > 0, R(3,4,5) > 0, R(3,4,5) > 0]],
def test_cross():
combo_check(
np.cross,
[0, 1],
[R(3, 3)],
[R(3, 3)],
axisa=[-1, 0, 1],
axisb=[-1, 0, 1],
axisc=[-1, 0, 1],
axis=[None, -1, 0, 1],
)
def test_concatenate_3d(): combo_check(np.concatenate, [0], [(R(2, 2, 2), R(2, 2, 2))], axis=[0, 1, 2]) # def test_vstack_1d(): combo_check(np.vstack, [0], [R(2), (R(2), R(2))]) # def test_vstack_2d(): combo_check(np.vstack, [0], [R(2, 3), (R(2, 4), R(1, 4))]) # def test_vstack_3d(): combo_check(np.vstack, [0], [R(2, 3, 4), (R(2, 3, 4), R(5, 3, 4))]) # def test_hstack_2d(): combo_check(np.hstack, [0], [R(2, 3), (R(2, 4), R(1, 4))]) # def test_hstack_3d(): combo_check(np.hstack, [0], [R(2, 3, 4), (R(2, 1, 4), R(2, 5, 4))]) # def test_dstack_3d(): combo_check(np.dstack, [0], [R(2, 3, 4), (R(2, 3, 1), R(2, 3, 5))]) #def test_select(): combo_check(np.select, [0, 1], [[R(3,4,5) > 0, R(3,4,5) > 0, R(3,4,5) > 0]], # [[R(3,4,5), R(3,4,5), R(3,4,5)]], default=[0.0, 1.1]) def make_psd(mat): return np.dot(mat.T, mat) + np.eye(mat.shape[0])
def test_squeeze_method():
combo_check(lambda x: x.squeeze(), [0], [R(5, 1, 4)])
def test_roll():
combo_check(np.roll, [0], [R(5, 4)], [2], axis=[1, None])
def test_expand_dims():
combo_check(np.expand_dims, [0], [R(5, 1, 3)], [2])
def test_ravel_call():
combo_check(np.ravel, [0], [R(5, 6, 4)])
def test_tensordot_3():
combo_check(np.tensordot, [0, 1], [R(2, 3), R(2, 3, 4)],
[R(1, 2, 3), R(2, 2, 3, 4)],
axes=[[(0, 1), (1, 2)], [(1, 0), (2, 1)]])
def test_repeat(): combo_check(np.repeat, [0], [R(2, 3, 4), R(3, 1)],
repeats=[0,1,2], axis = [None, 0, 1])
def test_diff():
def test_matmul_broadcast():
combo_check(np.matmul, [0, 1], [R(1, 2, 2)], [R(3, 2, 1)])
def test_tensordot_2():
combo_check(np.tensordot, [0, 1],
[R(3), R(3, 1), R(3, 4, 2)], [R(1, 3), R(2, 3, 2)],
axes=[[(0, ), (1, )]])
def test_matmul():
combo_check(np.matmul, [0, 1], [R(3), R(2, 3), R(2, 2, 3)],
[R(3), R(3, 4), R(2, 3, 4)])
def test_dot():
combo_check(np.dot, [0, 1],
[1.5, R(3), R(2, 3), R(2, 2, 3)],
[0.3, R(3), R(3, 4), R(2, 3, 4)])
def test_inner():
combo_check(np.inner, [0, 1], [1.5, R(3), R(2, 3)], [0.3, R(3), R(4, 3)])
def test_tile():
combo_check(np.tile, [0], [R(2, 1, 3, 1)], reps=[(1, 4, 1, 2)])
combo_check(np.tile, [0], [R(1, 2)], reps=[(1, 2), (2, 3), (3, 2, 1)])
combo_check(np.tile, [0], [R(1)], reps=[(2, ), 2])
def test_tensordot_4():
combo_check(np.tensordot, [0, 1], [R(2, 2), R(4, 2, 2)],
[R(2, 2), R(2, 2, 4)],
axes=[1, 2])
def test_vstack_3d(): combo_check(np.vstack, [0], [R(2, 3, 4), (R(2, 3, 4), R(5, 3, 4))]) # def test_hstack_2d(): combo_check(np.hstack, [0], [R(2, 3), (R(2, 4), R(1, 4))]) # def test_hstack_3d(): combo_check(np.hstack, [0], [R(2, 3, 4), (R(2, 1, 4), R(2, 5, 4))]) # def test_dstack_3d(): combo_check(np.dstack, [0], [R(2, 3, 4), (R(2, 3, 1), R(2, 3, 5))]) def test_select(): combo_check(np.select, [1], [[R(3,4,5) > 0, R(3,4,5) > 0, R(3,4,5) > 0]],
def test_tensordot_5():
combo_check(np.tensordot, [0, 1], [R(4)], [R()], axes=[0])
def test_tile():
combo_check(np.tile, [0], [R(2,1,3,1)], reps=[(1, 4, 1, 2)])
combo_check(np.tile, [0], [R(1,2)], reps=[(1,2), (2,3), (3,2,1)])
combo_check(np.tile, [0], [R(1)], reps=[(2,), 2])
def test_repeat():
combo_check(np.repeat, [0], [R(2, 3, 4), R(3, 1)],
repeats=[0, 1, 2],
axis=[None, 0, 1])
def test_moveaxis():
combo_check(np.moveaxis, [0], [R(2, 3, 4)],
source=[0, 1, 2],
destination=[0, 1, 2])
def test_split_2d(): combo_check(np.split, [0], [R(4, 8)], [4, [1, 2]], axis=[0, 1]) def test_split_3d(): combo_check(np.split, [0], [R(4, 4, 4)], [2, [1, 2]], axis=[0, 1, 2])
def test_transpose():
combo_check(np.transpose, [0], [R(2, 3, 4)],
axes=[
None, [0, 1, 2], [0, 2, 1], [2, 0, 1], [2, 1, 0],
[1, 0, 2], [1, 2, 0]
])
def test_array_split_1d(): combo_check(np.array_split, [0], [R(1), R(7)], [1, 3], axis=[0]) def test_array_split_2d(): combo_check(np.array_split, [0], [R(7, 7)], [4, [3, 5]], axis=[0, 1])
def test_nan_to_num():
y = np.array([0., np.nan, np.inf, -np.inf])
fun = lambda x: np.sum(np.sin(np.nan_to_num(x + y)))
x = np.random.randn(4)
combo_check(fun, [0], [x])
def test_array_split_3d(): combo_check(np.array_split, [0], [R(7, 7, 7)], [4, [3, 5]], axis=[0, 1, 2]) def test_concatenate_1ist(): combo_check(np.concatenate, [0], [(R(1), R(3))], axis=[0])
def test_clip():
combo_check(np.clip, [0], [R(5, 5)], a_min=[0.1], a_max=[1.1])
def test_concatenate_tuple(): combo_check(np.concatenate, [0], [[R(1), R(3)]], axis=[0]) def test_concatenate_2d(): combo_check(np.concatenate, [0], [(R(2, 2), R(2, 2))], axis=[0, 1])
def test_squeeze_call():
combo_check(np.squeeze, [0], [R(5, 1, 4)])
def test_concatenate_3d(): combo_check(np.concatenate, [0], [(R(2, 2, 2), R(2, 2, 2))], axis=[0, 1, 2]) def test_vstack_1d(): combo_check(np.vstack, [0], [R(2), (R(2), R(2))])
def test_tensordot_7():
combo_check(np.tensordot, [0, 1], [R(2, 6)], [R(6, 3)], axes=[[-1, 0]])
def test_diff():
combo_check(np.diff, [0], [R(5, 5), R(5, 5, 5)], n=[1, 2], axis=[0, 1])
combo_check(np.diff, [0], [R(1), R(1, 1)], axis=[0])
combo_check(np.diff, [0], [R(1, 1), R(3, 1)], axis=[1])
def test_split_1d(): combo_check(np.split, [0], [R(1), R(7)], [1], axis=[0]) def test_split_2d(): combo_check(np.split, [0], [R(4, 8)], [4, [1, 2]], axis=[0, 1])
def test_minimum():
combo_check(np.minimum, [0, 1], [R(1), R(1, 4), R(3, 4)],
[R(1), R(1, 4), R(3, 4)])
def test_split_3d(): combo_check(np.split, [0], [R(4, 4, 4)], [2, [1, 2]], axis=[0, 1, 2]) def test_array_split_1d(): combo_check(np.array_split, [0], [R(1), R(7)], [1, 3], axis=[0])
def test_fmin():
combo_check(np.fmin, [0, 1], [R(1), R(1, 4), R(3, 4)],
[R(1), R(1, 4), R(3, 4)])
def test_array_split_2d(): combo_check(np.array_split, [0], [R(7, 7)], [4, [3, 5]], axis=[0, 1]) def test_array_split_3d(): combo_check(np.array_split, [0], [R(7, 7, 7)], [4, [3, 5]], axis=[0, 1, 2])
def test_msort():
combo_check(np.msort, [0], [R(1), R(7)])
def test_concatenate_1ist(): combo_check(np.concatenate, [0], [(R(1), R(3))], axis=[0]) def test_concatenate_tuple(): combo_check(np.concatenate, [0], [[R(1), R(3)]], axis=[0])
def test_partition():
combo_check(np.partition, [0], [R(7), R(14)], kth=[0, 3, 6])
def test_concatenate_2d(): combo_check(np.concatenate, [0], [(R(2, 2), R(2, 2))], axis=[0, 1]) def test_concatenate_3d(): combo_check(np.concatenate, [0], [(R(2, 2, 2), R(2, 2, 2))], axis=[0, 1, 2])
def test_atleast_2d():
combo_check(
np.atleast_2d, [0],
[1.2, R(1), R(7), R(1, 4),
R(2, 4), R(2, 4, 5)])
def test_vstack_2d(): combo_check(np.vstack, [0], [R(2, 3), (R(2, 4), R(1, 4))]) def test_vstack_3d(): combo_check(np.vstack, [0], [R(2, 3, 4), (R(2, 3, 4), R(5, 3, 4))])
def test_einsum_transpose():
combo_check(np.einsum, [1], ['ij->ji'], [R(1, 1), R(4, 4), R(3, 4)])
def test_transpose(): combo_check(np.transpose, [0],
[R(2, 3, 4)], axes = [None, [0, 1, 2], [0, 2, 1],
[2, 0, 1], [2, 1, 0],
[1, 0, 2], [1, 2, 0]])
def test_repeat(): combo_check(np.repeat, [0], [R(2, 3, 4), R(3, 1)],
def test_einsum_matmult():
combo_check(np.einsum, [1, 2], ['ij,jk->ik'], [R(2, 3)], [R(3, 4)])
def test_diff():
combo_check(np.diff, [0], [R(5,5), R(5,5,5)], n=[1,2], axis=[0,1])
combo_check(np.diff, [0], [R(1), R(1,1)], axis=[0])
combo_check(np.diff, [0], [R(1,1), R(3,1)], axis=[1])
def test_einsum_matmult_broadcast():
combo_check(np.einsum, [1, 2], ['...ij,...jk->...ik'],
[R(2, 3), R(2, 2, 3)], [R(3, 4), R(2, 3, 4)])
def test_dot(): combo_check(np.dot, [0, 1],
[1.5, R(3), R(2, 3)],
[0.3, R(3), R(3, 4)])
def test_tensordot_1(): combo_check(np.tensordot, [0, 1],
def test_ravel_method():
combo_check(lambda x: x.ravel(), [0], [R(5, 6, 4)])
