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Graph hopper kernel unable to transfom the data #106

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SantaAnkit opened this issue Feb 6, 2024 · 0 comments
Open

Graph hopper kernel unable to transfom the data #106

SantaAnkit opened this issue Feb 6, 2024 · 0 comments

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@SantaAnkit
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iam getting a following error while transforming the data in case of graph hopper kernel only.

dataset_name = "MUTAG" # Replace with the desired dataset name
dataset = fetch_dataset(dataset_name, verbose=True)
G = dataset['data'] # Graphs
y = dataset['target'] # Labels
G_train, G_test, y_train, y_test = train_test_split(G, y, test_size=0.2, random_state=42)
gk = GraphHopper(normalize=True,kernel_type='bridge')
'''graph hopper kernel instance'''
K_train = gk.fit_transform(G_train)

Extracting dataset MUTAG..
Parsing dataset MUTAG..
Parse was succesful..
Deleting unzipped dataset files..
Going back to the original directory..


ValueError Traceback (most recent call last)
Cell In[98], line 8
6 gk = GraphHopper(normalize=True,kernel_type='bridge')
7 '''graph hopper kernel instance'''
----> 8 K_train = gk.fit_transform(G_train)

File ~/anaconda3/lib/python3.9/site-packages/grakel/kernels/kernel.py:198, in Kernel.fit_transform(self, X, y)
195 self.fit(X)
197 # Transform - calculate kernel matrix
--> 198 km = self._calculate_kernel_matrix()
200 self._X_diag = np.diagonal(km)
201 if self.normalize:

File ~/anaconda3/lib/python3.9/site-packages/grakel/kernels/kernel.py:232, in Kernel._calculate_kernel_matrix(self, Y)
230 cache = list()
231 for (i, x) in enumerate(self.X):
--> 232 K[i, i] = self.pairwise_operation(x, x)
233 for (j, y) in enumerate(cache):
234 K[j, i] = self.pairwise_operation(y, x)

File ~/anaconda3/lib/python3.9/site-packages/grakel/kernels/graph_hopper.py:261, in GraphHopper.pairwise_operation(self, x, y)
258 elif y[0].shape[1] > m:
259 yp = yp[:, :m, :][:, :, :m]
--> 261 return self.metric_((xp.reshape(xp.shape[0], m_sq),) + x[1:],
262 (yp.reshape(yp.shape[0], m_sq),) + y[1:])

File ~/anaconda3/lib/python3.9/site-packages/grakel/kernels/graph_hopper.py:335, in bridge_kernel(x, y)
333 nodepair = (4-NA_i_NA_j_distances)/4
334 nodepair[nodepair < 0] = 0
--> 335 return np.dot(weight_matrix.flat, nodepair.flat)

File <array_function internals>:200, in dot(*args, **kwargs)

ValueError: shapes (196,) and (0,) not aligned: 196 (dim 0) != 0 (dim 0)

I have tried this with other kernel like random walk, shortest path and WL but there it is working.

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