fix if use lang embeddings in tf xlm

src/transformers/modeling_tf_xlm.py

@@ -408,7 +408,7 @@ class TFXLMMainLayer(tf.keras.layers.Layer):
             inputs_embeds = self.embeddings(input_ids)
 
         tensor = inputs_embeds + self.position_embeddings(position_ids)
-        if langs is not None and self.use_lang_emb:
+        if langs is not None and self.use_lang_emb and self.n_langs > 1:
             tensor = tensor + self.lang_embeddings(langs)
         if token_type_ids is not None:
             tensor = tensor + self.embeddings(token_type_ids)

tests/test_modeling_tf_xlm.py

@@ -342,4 +342,4 @@ class TFXLMModelLanguageGenerationTest(unittest.TestCase):
         ]  # the president the president the president the president the president the president the president the president the president the president
         # TODO(PVP): this and other input_ids I tried for generation give pretty bad results. Not sure why. Model might just not be made for auto-regressive inference
         output_ids = model.generate(input_ids)
-        self.assertListEqual(output_ids[0].tolist(), expected_output_ids, do_sample=False)
+        self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids, do_sample=False)