Add error message when parameter is set to 0 (#33859)

Author: FrostML

python/paddle/nn/layer/transformer.py

@@ -161,6 +161,12 @@ def __init__(self,
                  weight_attr=None,
                  bias_attr=None):
         super(MultiHeadAttention, self).__init__()
+
+        assert embed_dim > 0, ("Expected embed_dim to be greater than 0, "
+                               "but recieved {}".format(embed_dim))
+        assert num_heads > 0, ("Expected num_heads to be greater than 0, "
+                               "but recieved {}".format(num_heads))
+
         self.embed_dim = embed_dim
         self.kdim = kdim if kdim is not None else embed_dim
         self.vdim = vdim if vdim is not None else embed_dim
@@ -501,6 +507,15 @@ def __init__(self,
         self._config.pop("__class__", None)  # py3
 
         super(TransformerEncoderLayer, self).__init__()
+
+        assert d_model > 0, ("Expected d_model to be greater than 0, "
+                             "but recieved {}".format(d_model))
+        assert nhead > 0, ("Expected nhead to be greater than 0, "
+                           "but recieved {}".format(nhead))
+        assert dim_feedforward > 0, (
+            "Expected dim_feedforward to be greater than 0, "
+            "but recieved {}".format(dim_feedforward))
+
         attn_dropout = dropout if attn_dropout is None else attn_dropout
         act_dropout = dropout if act_dropout is None else act_dropout
         self.normalize_before = normalize_before
@@ -797,6 +812,15 @@ def __init__(self,
         self._config.pop("__class__", None)  # py3
 
         super(TransformerDecoderLayer, self).__init__()
+
+        assert d_model > 0, ("Expected d_model to be greater than 0, "
+                             "but recieved {}".format(d_model))
+        assert nhead > 0, ("Expected nhead to be greater than 0, "
+                           "but recieved {}".format(nhead))
+        assert dim_feedforward > 0, (
+            "Expected dim_feedforward to be greater than 0, "
+            "but recieved {}".format(dim_feedforward))
+
         attn_dropout = dropout if attn_dropout is None else attn_dropout
         act_dropout = dropout if act_dropout is None else act_dropout
         self.normalize_before = normalize_before
@@ -1196,6 +1220,14 @@ def __init__(self,
                  custom_decoder=None):
         super(Transformer, self).__init__()
 
+        assert d_model > 0, ("Expected d_model to be greater than 0, "
+                             "but recieved {}".format(d_model))
+        assert nhead > 0, ("Expected nhead to be greater than 0, "
+                           "but recieved {}".format(nhead))
+        assert dim_feedforward > 0, (
+            "Expected dim_feedforward to be greater than 0, "
+            "but recieved {}".format(dim_feedforward))
+
         if isinstance(bias_attr, (list, tuple)):
             if len(bias_attr) == 1:
                 encoder_bias_attr = [bias_attr[0]] * 2