Consistent verbose behavior

shenweichen · Mar 24, 2024 · 7299315 · 7299315
1 parent f685425
commit 7299315
Showing 1 changed file with 3 additions and 7 deletions.
diff --git a/deepctr_torch/models/basemodel.py b/deepctr_torch/models/basemodel.py
@@ -47,11 +47,6 @@ def __init__(self, feature_columns, feature_index, init_std=0.0001, device='cpu'
         self.embedding_dict = create_embedding_matrix(feature_columns, init_std, linear=True, sparse=False,
                                                       device=device)
 
-        #         nn.ModuleDict(
-        #             {feat.embedding_name: nn.Embedding(feat.dimension, 1, sparse=True) for feat in
-        #              self.sparse_feature_columns}
-        #         )
-        # .to("cuda:1")
         for tensor in self.embedding_dict.values():
             nn.init.normal_(tensor.weight, mean=0, std=init_std)
 
@@ -227,8 +222,9 @@ def fit(self, x=None, y=None, batch_size=None, epochs=1, verbose=1, initial_epoc
         callbacks.model.stop_training = False
 
         # Train
-        print("Train on {0} samples, validate on {1} samples, {2} steps per epoch".format(
-            len(train_tensor_data), len(val_y), steps_per_epoch))
+        if verbose > 0:
+            print("Train on {0} samples, validate on {1} samples, {2} steps per epoch".format(
+                len(train_tensor_data), len(val_y), steps_per_epoch))
         for epoch in range(initial_epoch, epochs):
             callbacks.on_epoch_begin(epoch)
             epoch_logs = {}