Removing unused viterbi_decoding in model.py

taishi-i · Jul 6, 2020 · 8fdc1a7 · 8fdc1a7
1 parent 21f2413
commit 8fdc1a7
Showing 1 changed file with 32 additions and 32 deletions.
diff --git a/nagisa/model.py b/nagisa/model.py
@@ -150,38 +150,38 @@ def score_sentence(self, observations, tags):
         score = score + dy.pick(self.trans[self.sp_e], tags[-1])
         return score
 
-
-    def viterbi_decoding(self, observations):
-        backpointers = []
-        init_vvars   = [-1e10] * self.dim_output
-        init_vvars[self.sp_s] = 0
-        for_expr     = dy.inputVector(init_vvars)
-        trans_exprs  = [self.trans[idx] for idx in range(self.dim_output)]
-        for obs in observations:
-            bptrs_t = []
-            vvars_t = []
-            for next_tag in range(self.dim_output):
-                next_tag_expr = for_expr + trans_exprs[next_tag]
-                next_tag_arr = next_tag_expr.npvalue()
-                best_tag_id  = np.argmax(next_tag_arr)
-                bptrs_t.append(best_tag_id)
-                vvars_t.append(dy.pick(next_tag_expr, best_tag_id))
-            for_expr = dy.concatenate(vvars_t) + obs
-            backpointers.append(bptrs_t)
-        terminal_expr = for_expr + trans_exprs[self.sp_e]
-        terminal_arr  = terminal_expr.npvalue()
-        best_tag_id   = np.argmax(terminal_arr)
-        path_score    = dy.pick(terminal_expr, best_tag_id)
-        best_path = [best_tag_id]
-        for bptrs_t in reversed(backpointers):
-            best_tag_id = bptrs_t[best_tag_id]
-            best_path.append(best_tag_id)
-        start = best_path.pop()
-        best_path.reverse()
-        if not start == self.sp_s:
-            raise AssertionError("start != self.sp_s")
-        return best_path, path_score
-
+    # Nagisa does not use this method.
+    #
+    # def viterbi_decoding(self, observations):
+    #     backpointers = []
+    #     init_vvars   = [-1e10] * self.dim_output
+    #     init_vvars[self.sp_s] = 0
+    #     for_expr     = dy.inputVector(init_vvars)
+    #     trans_exprs  = [self.trans[idx] for idx in range(self.dim_output)]
+    #     for obs in observations:
+    #         bptrs_t = []
+    #         vvars_t = []
+    #         for next_tag in range(self.dim_output):
+    #             next_tag_expr = for_expr + trans_exprs[next_tag]
+    #             next_tag_arr = next_tag_expr.npvalue()
+    #             best_tag_id  = np.argmax(next_tag_arr)
+    #             bptrs_t.append(best_tag_id)
+    #             vvars_t.append(dy.pick(next_tag_expr, best_tag_id))
+    #         for_expr = dy.concatenate(vvars_t) + obs
+    #         backpointers.append(bptrs_t)
+    #     terminal_expr = for_expr + trans_exprs[self.sp_e]
+    #     terminal_arr  = terminal_expr.npvalue()
+    #     best_tag_id   = np.argmax(terminal_arr)
+    #     path_score    = dy.pick(terminal_expr, best_tag_id)
+    #     best_path = [best_tag_id]
+    #     for bptrs_t in reversed(backpointers):
+    #         best_tag_id = bptrs_t[best_tag_id]
+    #         best_path.append(best_tag_id)
+    #     start = best_path.pop()
+    #     best_path.reverse()
+    #     if not start == self.sp_s:
+    #         raise AssertionError("start != self.sp_s")
+    #     return best_path, path_score
 
     def encode_pt(self, X, train=False):
         dy.renew_cg()