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python 3 compatibility, running for cora initial example #17

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python 3 compatibility, running for cora initial example #17

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14 changes: 7 additions & 7 deletions graphsage/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,7 @@ def load_cora():
with open("cora/cora.content") as fp:
for i,line in enumerate(fp):
info = line.strip().split()
feat_data[i,:] = map(float, info[1:-1])
feat_data[i,:] = list(map(float, info[1:-1]))
node_map[info[0]] = i
if not info[-1] in label_map:
label_map[info[-1]] = len(label_map)
Expand Down Expand Up @@ -99,11 +99,11 @@ def run_cora():
optimizer.step()
end_time = time.time()
times.append(end_time-start_time)
print batch, loss.data[0]
print(batch, loss.data.item())

val_output = graphsage.forward(val)
print "Validation F1:", f1_score(labels[val], val_output.data.numpy().argmax(axis=1), average="micro")
print "Average batch time:", np.mean(times)
print("Validation F1:", f1_score(labels[val], val_output.data.numpy().argmax(axis=1), average="micro"))
print("Average batch time:", np.mean(times))

def load_pubmed():
#hardcoded for simplicity...
Expand Down Expand Up @@ -171,11 +171,11 @@ def run_pubmed():
optimizer.step()
end_time = time.time()
times.append(end_time-start_time)
print batch, loss.data[0]
print(batch, loss.data.item())

val_output = graphsage.forward(val)
print "Validation F1:", f1_score(labels[val], val_output.data.numpy().argmax(axis=1), average="micro")
print "Average batch time:", np.mean(times)
print("Validation F1:", f1_score(labels[val], val_output.data.numpy().argmax(axis=1), average="micro"))
print("Average batch time:", np.mean(times))

if __name__ == "__main__":
run_cora()