add output arc; fix black

egs/librispeech/ASR/tdnn_lstm_ctc/asr_datamodule.py

@@ -449,9 +449,7 @@ class LibriSpeechAsrDataModule:
     @lru_cache()
     def test_book_cuts(self) -> CutSet:
         logging.info("About to get test-books cuts")
-        return load_manifest_lazy(
-            self.args.manifest_dir / "libri_books_feats.jsonl.gz"
-        )
+        return load_manifest_lazy(self.args.manifest_dir / "libri_books_feats.jsonl.gz")
 
     @lru_cache()
     def test_book_test_cuts(self) -> CutSet:

icefall/context_graph.py

@@ -61,6 +61,7 @@ class ContextState:
         self.is_end = is_end
         self.next = {}
         self.fail = None
+        self.output = None
 
 
 class ContextGraph:
@@ -97,7 +98,7 @@ class ContextGraph:
         )
         self.root.fail = self.root
 
-    def _fill_fail(self):
+    def _fill_fail_output(self):
         """This function fills the fail arc for each trie node, it can be computed
         in linear time by performing a breadth-first search starting from the root.
         See https://en.wikipedia.org/wiki/Aho%E2%80%93Corasick_algorithm for the
@@ -122,6 +123,14 @@ class ContextGraph:
                     if token in fail.next:
                         fail = fail.next[token]
                 node.fail = fail
+                # fill the output arc
+                output = node.fail
+                while not output.is_end:
+                    output = output.fail
+                    if output.token == -1:  # root
+                        output = None
+                        break
+                node.output = output
                 queue.append(node)
 
     def build(self, token_ids: List[List[int]]):
@@ -155,7 +164,7 @@ class ContextGraph:
                         is_end=is_end,
                     )
                 node = node.next[token]
-        self._fill_fail()
+        self._fill_fail_output()
 
     def forward_one_step(
         self, state: ContextState, token: int
@@ -171,11 +180,14 @@ class ContextGraph:
         Returns:
           Return a tuple of score and next state.
         """
+        node = None
+        score = 0
         # token matched
         if token in state.next:
             node = state.next[token]
             score = node.token_score
-            return (score, node)
+            if state.is_end:
+                score += state.node_score
         else:
             # token not matched
             # We will trace along the fail arc until it matches the token or reaching
@@ -191,7 +203,13 @@ class ContextGraph:
 
             # The score of the fail path
             score = node.node_score - state.local_node_score
-            return (score, node)
+        assert node is not None
+        matched_score = 0
+        output = node.output
+        while output is not None:
+            matched_score += output.node_score
+            output = output.output
+        return (score + matched_score, node)
 
     def finalize(self, state: ContextState) -> Tuple[float, ContextState]:
         """When reaching the end of the decoded sequence, we need to finalize
@@ -208,7 +226,9 @@ class ContextGraph:
           to root. The next state is always root.
         """
         # The score of the fail arc
-        score = self.root.node_score - state.local_node_score
+        score = -state.node_score
+        if state.is_end:
+            score = 0
         return (score, self.root)
 
     def draw(
@@ -279,7 +299,7 @@ class ContextGraph:
         queue.append(self.root)
         # root id is always 0
         dot.node("0", label="0", **default_node_attr)
-        dot.edge("0", "0", label=f"*/0")
+        dot.edge("0", "0", color="red")
         seen.add(0)
 
         while len(queue):
@@ -304,6 +324,12 @@ class ContextGraph:
                     str(node.fail.id),
                     color="red",
                 )
+                if node.output is not None:
+                    dot.edge(
+                        str(node.id),
+                        str(node.output.id),
+                        color="green",
+                    )
                 queue.append(node)
 
         if filename:
@@ -331,7 +357,17 @@ class ContextGraph:
 
 
 if __name__ == "__main__":
-    contexts_str = ["HE", "SHE", "SHELL", "HIS", "HERS", "HELLO"]
+    contexts_str = [
+        "S",
+        "HE",
+        "SHE",
+        "SHELL",
+        "HIS",
+        "HERS",
+        "HELLO",
+        "THIS",
+        "THEM",
+    ]
     contexts = []
     for s in contexts_str:
         contexts.append([ord(x) for x in s])
@@ -350,9 +386,17 @@ if __name__ == "__main__":
         symbol_table=symbol_table,
     )
 
-    queries = ["HERSHE", "HISHE", "SHED", "HELL", "HELLO", "DHRHISQ"]
-    expected_scores = [7, 6, 3, 2, 5, 3]
-    for i, query in enumerate(queries):
+    queries = {
+        "HEHERSHE": 14,  # "HE", "HE", "HERS", "S", "SHE", "HE"
+        "HERSHE": 12,  # "HE", "HERS", "S", "SHE", "HE"
+        "HISHE": 9,  # "HIS", "S", "SHE", "HE"
+        "SHED": 6,  # "S", "SHE", "HE"
+        "HELL": 2,  # "HE"
+        "HELLO": 7,  # "HE", "HELLO"
+        "DHRHISQ": 4,  # "HIS", "S"
+        "THEN": 2,  # "HE"
+    }
+    for query, expected_score in queries.items():
         total_scores = 0
         state = context_graph.root
         for q in query:
@@ -361,8 +405,8 @@ if __name__ == "__main__":
         score, state = context_graph.finalize(state)
         assert state.token == -1, state.token
         total_scores += score
-        assert total_scores == expected_scores[i], (
+        assert total_scores == expected_score, (
             total_scores,
-            expected_scores[i],
+            expected_score,
             query,
         )