fix flip meaning of symmetric and asymmetric
@@ -211,7 +211,7 @@ def matrix_to_array(m, indices):
# - input_tensor: tensor for which the predictions are computed
# - symmetric: are connections between needs symmentric? then only the half of the predictions have to be computed
# - keepConnections: if true keep the predictions between the needs where a connection existed before
-def predict_rescal_hints_by_threshold(A, R, threshold, input_tensor, symmetric=False, keepConnections=False):
+def predict_rescal_hints_by_threshold(A, R, threshold, input_tensor, symmetric=True, keepConnections=False):
rows = []
cols = []
@@ -225,7 +225,7 @@ def predict_rescal_hints_by_threshold(A, R, threshold, input_tensor, symmetric=F
rounds = rounds + 1
colPred = np.dot(R[SparseTensor.CONNECTION_SLICE], A_T[:,j])
for i in input_tensor.getNeedIndices():
- if (symmetric or j < i):
+ if ((not symmetric) or j < i):
x = np.dot(A[i], colPred)
if (x > threshold):
if (keepConnections or (not input_tensor.hasConnection(i,j))):
