def test_roi_pooling():
A = np.ones((1, 1, 5, INT_OVERFLOW))
A[0][0][0][2] = 100
roi = np.array([[0, 0, 0, 3, 3]])
A.attach_grad()
with mx.autograd.record():
B = npx.roi_pooling(A, roi, pooled_size=(2, 2), spatial_scale=1)
assert B.shape == (1, 1, 2, 2)
assert B[0][0][0][1] == 100
B.backward()
assert A.grad.shape == (1, 1, 5, INT_OVERFLOW)
assert A.grad[0][0][0][0] == 1
def test_roi_pooling():
def test_roi_pooling_large_dim():
A = np.ones((1, 1, INT_OVERFLOW, 5))
roi = np.array([[0, 0, 0, 5, 5]])
assertRaises(MXNetError, npx.roi_pooling, A, roi, pooled_size=(3, 3), \
spatial_scale=1)
test_roi_pooling_large_dim()
H, W = 2**16, 2**16
A = np.ones((1, 1, H, W))
A[0, 0, 0, 2] = 100
roi = np.array([[0, 0, 0, 5, 5]])
A.attach_grad()
with mx.autograd.record():
B = npx.roi_pooling(A, roi, pooled_size=(3, 3), spatial_scale=1)
assert B.shape == (1, 1, 3, 3)
assert B[0][0][0][1] == 100
B.backward()
assert A.grad.shape == (1, 1, H, W)
assert A.grad[0][0][0][0] == 1