TF: correct TFBart embeddings weights name when load_weight_prefix is…

… passed (huggingface#18993)

src/transformers/models/bart/modeling_tf_bart.py

@@ -16,6 +16,7 @@
 
 
 import random
+from contextlib import nullcontext
 from typing import Optional, Tuple, Union
 
 import numpy as np
@@ -748,7 +749,15 @@ def call(
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
         if inputs_embeds is None:
-            with tf.name_scope(self.embed_tokens.name + "/"):
+            # if `self.embed_tokens.load_weight_prefix` is set, runs the embedding operation with the correct name
+            # scope, so that its weights are registered with the desired name for loading/storing. When `tf.name_scope`
+            # is used with a name ending in `/`, that name replaces the current name scope.
+            # (embeddings with tf.name_scope: self.embed_tokens.load_weight_prefix/self.embed_tokens.name/embeddings:0)
+            if hasattr(self.embed_tokens, "load_weight_prefix"):
+                context_manager = tf.name_scope(self.embed_tokens.load_weight_prefix + "/")
+            else:
+                context_manager = nullcontext()
+            with context_manager:
                 inputs_embeds = self.embed_tokens(input_ids) * self.embed_scale
 
         embed_pos = self.embed_positions(input_shape)
@@ -936,7 +945,15 @@ def call(
             positions = self.embed_positions(input_shape, position_ids=position_ids)
 
         if inputs_embeds is None:
-            with tf.name_scope(self.embed_tokens.name + "/"):
+            # if `self.embed_tokens.load_weight_prefix` is set, runs the embedding operation with the correct name
+            # scope, so that its weights are registered with the desired name for loading/storing. When `tf.name_scope`
+            # is used with a name ending in `/`, that name replaces the current name scope.
+            # (embeddings with tf.name_scope: self.embed_tokens.load_weight_prefix/self.embed_tokens.name/embeddings:0)
+            if hasattr(self.embed_tokens, "load_weight_prefix"):
+                context_manager = tf.name_scope(self.embed_tokens.load_weight_prefix + "/")
+            else:
+                context_manager = nullcontext()
+            with context_manager:
                 inputs_embeds = self.embed_tokens(input_ids) * self.embed_scale
 
         hidden_states = inputs_embeds
@@ -1032,8 +1049,9 @@ class TFBartMainLayer(tf.keras.layers.Layer):
     def __init__(self, config: BartConfig, load_weight_prefix=None, **kwargs):
         super().__init__(**kwargs)
         self.config = config
-        load_weight_prefix = "model.shared" if load_weight_prefix is None else load_weight_prefix
-        self.shared = tf.keras.layers.Embedding(config.vocab_size, config.d_model, name=load_weight_prefix)
+        self.shared = tf.keras.layers.Embedding(config.vocab_size, config.d_model, name="model.shared")
+        # Additional attribute to specify the expected name scope of the layer (for loading/storing weights)
+        self.shared.load_weight_prefix = "model.shared" if load_weight_prefix is None else load_weight_prefix
 
         self.encoder = TFBartEncoder(config, self.shared, name="encoder")
         self.decoder = TFBartDecoder(config, self.shared, name="decoder")