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Improve code coverage #43

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Dec 16, 2022
Merged

Improve code coverage #43

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18 changes: 5 additions & 13 deletions tests/test_misc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,21 +75,13 @@ def test_multi_matching_result():
num_graphs = 5
pygm.BACKEND = 'numpy'
As, X = pygm.utils.generate_isomorphic_graphs(num_nodes, num_graphs)
As_1, As_2, Fs_1, Fs_2 = [], [], [], []
for i in range(num_graphs):
for j in range(num_graphs):
As_1.append(pygm.utils.to_numpy(As[i]))
As_2.append(pygm.utils.to_numpy(As[j]))
As_1 = pygm.utils.from_numpy(np.stack(As_1, axis=0))
As_2 = pygm.utils.from_numpy(np.stack(As_2, axis=0))
conn1, edge1, ne1 = pygm.utils.dense_to_sparse(As_1)
conn2, edge2, ne2 = pygm.utils.dense_to_sparse(As_2)
K = pygm.utils.build_aff_mat(None, edge1, conn1, None, edge2, conn2, None, ne1, None, ne2)
K = K.reshape((num_graphs, num_graphs, num_nodes ** 2, num_nodes ** 2))
X = pygm.cao(K) # X is multi-matching result
mmX = pygm.utils.MultiMatchingResult()
for i in range(X.shape[0]):
for j in range(X.shape[1]):
mmX[i, j] = X[i, j]

for backend in ['numpy', 'pytorch', 'paddle', 'jittor']:
newX = pygm.utils.from_numpy(X, backend=backend)
newX = pygm.utils.from_numpy(mmX, backend=backend)
newX.__repr__()
newX.__str__()

Expand Down
31 changes: 27 additions & 4 deletions tests/test_multi_graph_solvers.py
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Expand Up @@ -83,6 +83,8 @@ def _test_mgm_solver_on_isomorphic_graphs(num_graph, num_node, node_feat_dim, so
pygm.BACKEND = working_backend
if 'x0' in solver_param_dict and solver_param_dict['x0'] is not None:
solver_param_dict['x0'] = pygm.utils.from_numpy(solver_param_dict['x0'])
if 'ns' in solver_param_dict and solver_param_dict['ns'] is not None:
solver_param_dict['ns'] = pygm.utils.from_numpy(solver_param_dict['ns'])
if mode == 'lawler-qap':
_As_1, _As_2, _Fs_1, _Fs_2, _X_gt = data_from_numpy(As_1, As_2, Fs_1, Fs_2, X_gt)
_conn1, _edge1, _ne1 = pygm.utils.dense_to_sparse(_As_1)
Expand Down Expand Up @@ -133,17 +135,26 @@ def _test_mgm_solver_on_isomorphic_graphs(num_graph, num_node, node_feat_dim, so
last_X = pygm.utils.to_numpy(_X)

matched = 0
total = 0
for i, j in itertools.product(range(num_graph), repeat=2):
matched += (pygm.utils.to_numpy(_X[i, j]) * X_gt[i, j]).sum()
accuracy = matched / X_gt.sum()
if 'ns' in solver_param_dict and solver_param_dict['ns'] is not None:
nsi = pygm.utils.to_numpy(solver_param_dict['ns'][i]).item()
nsj = pygm.utils.to_numpy(solver_param_dict['ns'][j]).item()
matched += (pygm.utils.to_numpy(_X[i, j]) * X_gt[i, j, :nsi, :nsj]).sum()
total += X_gt[i, j, :nsi, :nsj].sum()
else:
matched += (pygm.utils.to_numpy(_X[i, j]) * X_gt[i, j]).sum()
total += X_gt[i, j].sum()
accuracy = matched / total
assert accuracy == 1, f"GM is inaccurate for {working_backend}, accuracy={accuracy}, " \
f"params: {';'.join([k + '=' + str(v) for k, v in aff_param_dict.items()])};" \
f"{';'.join([k + '=' + str(v) for k, v in solver_param_dict.items()])}"
else:
raise ValueError(f'Unknown mode: {mode}')
if 'x0' in solver_param_dict and solver_param_dict['x0'] is not None:
solver_param_dict['x0'] = pygm.utils.to_numpy(solver_param_dict['x0'])

if 'ns' in solver_param_dict and solver_param_dict['ns'] is not None:
solver_param_dict['ns'] = pygm.utils.to_numpy(solver_param_dict['ns'])

def test_cao():
num_nodes = 5
Expand Down Expand Up @@ -174,6 +185,7 @@ def test_mgm_floyd():
def test_gamgm():
num_nodes = 5
num_graphs = 10
# test without outliers
_test_mgm_solver_on_isomorphic_graphs(num_graphs, num_nodes, 10, pygm.gamgm, 'kb-qap', {
'sk_init_tau': [0.5, 0.1],
'sk_min_tau': [0.1, 0.05],
Expand All @@ -182,6 +194,18 @@ def test_gamgm():
'verbose': [True]
}, ['pytorch', 'numpy', 'paddle', 'jittor'])

# test with outliers
_test_mgm_solver_on_isomorphic_graphs(num_graphs, num_nodes, 10, pygm.gamgm, 'kb-qap', {
'sk_init_tau': [0.5],
'sk_gamma': [0.8],
'sk_min_tau': [0.1],
'param_lambda': [0.1],
'node_aff_fn': [functools.partial(pygm.utils.gaussian_aff_fn, sigma=.1)],
'verbose': [True],
'n_univ': [10],
'ns': [np.array([num_nodes] * (num_graphs // 2) + [num_nodes-1] * (num_graphs - num_graphs // 2))],
}, ['pytorch', 'numpy', 'paddle', 'jittor'])


def test_gamgm_backward():
# Pytorch
Expand All @@ -208,7 +232,6 @@ def test_gamgm_backward():
acc.backward()
assert torch.sum(W.grad != 0) > 0


# Jittor
pygm.BACKEND = 'jittor'
jt.set_global_seed(2)
Expand Down