Merge pull request #2146 from siyerp/patch-3

Updated function signatures to comply with new tensorflow requirements

recommenders/models/sasrec/model.py

@@ -240,7 +240,7 @@ def call(self, x, training, mask):
 
         Args:
             x (tf.Tensor): Input tensor.
-            training (tf.Tensor): Training tensor.
+            training (Boolean): True if in training mode.
             mask (tf.Tensor): Mask tensor.
 
         Returns:
@@ -305,15 +305,15 @@ def call(self, x, training, mask):
 
         Args:
             x (tf.Tensor): Input tensor.
-            training (tf.Tensor): Training tensor.
+            training (Boolean): True if in training mode.
             mask (tf.Tensor): Mask tensor.
 
         Returns:
             tf.Tensor: Output tensor.
         """
 
         for i in range(self.num_layers):
-            x = self.enc_layers[i](x, training, mask)
+            x = self.enc_layers[i](x, training=training, mask=mask)
 
         return x  # (batch_size, input_seq_len, d_model)
 

recommenders/models/sasrec/ssept.py

@@ -122,7 +122,7 @@ def call(self, x, training):
         # --- ATTENTION BLOCKS ---
         seq_attention = seq_embeddings  # (b, s, h1 + h2)
 
-        seq_attention = self.encoder(seq_attention, training, mask)
+        seq_attention = self.encoder(seq_attention, training=training, mask=mask)
         seq_attention = self.layer_normalization(seq_attention)  # (b, s, h1+h2)
 
         # --- PREDICTION LAYER ---
@@ -197,7 +197,7 @@ def predict(self, inputs):
 
         seq_embeddings *= mask
         seq_attention = seq_embeddings
-        seq_attention = self.encoder(seq_attention, training, mask)
+        seq_attention = self.encoder(seq_attention, training=training, mask=mask)
         seq_attention = self.layer_normalization(seq_attention)  # (b, s, h1+h2)
         seq_emb = tf.reshape(
             seq_attention,