update

Author: bob7783

nlp_class2/pmi.py

@@ -152,9 +152,13 @@ def remove_punctuation_3(s):
 
 
 # PMI(w, c) = #(w, c) / #(w) / p(c)
-pmi = wc_counts / wc_counts.sum(axis=1) / c_probs
+# pmi = wc_counts / wc_counts.sum(axis=1) / c_probs # works only if numpy arrays
+pmi = wc_counts.multiply(1.0 / wc_counts.sum(axis=1) / c_probs).tocsr()
+# this operation changes it to a coo_matrix
+# which doesn't have functions we need, e.g log1p()
+# so convert it back to a csr
 print("type(pmi):", type(pmi))
-logX = np.log(pmi.A + 1)
+logX = pmi.log1p() # would be logX = np.log(pmi.A + 1) in numpy
 print("type(logX):", type(logX))
 logX[logX < 0] = 0
 
@@ -180,7 +184,9 @@ def remove_punctuation_3(s):
 for epoch in range(10):
   print("epoch:", epoch)
   delta = W.dot(U.T) + b.reshape(V, 1) + c.reshape(1, V) + mu - logX
-  cost = ( delta * delta ).sum()
+  # cost = ( delta * delta ).sum()
+  cost = np.multiply(delta, delta).sum()
+  # * behaves differently if delta is a "matrix" object vs "array" object
   costs.append(cost)
 
   ### partially vectorized updates ###