Add meaning map print.

wit/meaning_dataset.py

@@ -237,10 +237,28 @@ class BatchGroupMeaningDataloader(Dataset):
     def mapping(self, idx):
         return self.dataset.get_mapping_batch(self.indexBatch[idx])
 
+    def print_mapping(self, idx):
+        map = self.mapping(idx)
+        s = ""
+        for m in map:
+            s += BatchGroupMeaningDataloader.get_mapping_str(m, "")
+            s += "--------\n"
+        return s
+
+    def get_mapping_str(map, prefix):
+        if isinstance(map, dict):
+            base = ""
+            for key, value in map.items():
+                base += prefix + str(key) + "\n"
+                base += BatchGroupMeaningDataloader.get_mapping_str(value, prefix + "    ")
+            return base
+        else:
+            return ""
+
 
 if __name__ == "__main__":
 
-    md = MeaningDataset(1024, 115200, vocab_size=1024, size=1024)
+    md = MeaningDataset(100000, 115200, vocab_size=1024, size=1024)
     train, val = md.split(0.95)
 
     dl = BatchGroupMeaningDataloader(train, 2)
@@ -250,7 +268,9 @@ if __name__ == "__main__":
     ne2 = next(it)
     ne3 = next(it)
 
-    map = dl.mapping(0)
+    map1 = dl.mapping(0)
+    map2 = dl.mapping(1)
+    print(dl.print_mapping(0))
 
     dl = DataLoader(
         train,

wit/train.py

@@ -65,7 +65,6 @@ if __name__ == "__main__":
     torch.set_float32_matmul_precision("medium")
     lit_trainer = pl.Trainer(
         accelerator="cuda",
-        devices=[0, 1],
         precision=precision,
         logger=TBLogger("./log/", name=name, version=ver, default_hp_metric=False),
         strategy=strategy,