set eos_token_id to None to generate until max length (#16989)

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

tests/encoder_decoder/test_modeling_encoder_decoder.py

@@ -413,6 +413,9 @@ class EncoderDecoderMixin:
         enc_dec_model = EncoderDecoderModel(encoder=encoder_model, decoder=decoder_model)
 
         # Generate until max length
+        if hasattr(enc_dec_model.config, "eos_token_id"):
+            enc_dec_model.config.eos_token_id = None
+        if hasattr(enc_dec_model.config, "decoder") and hasattr(enc_dec_model.config.decoder, "eos_token_id"):
             enc_dec_model.config.decoder.eos_token_id = None
         enc_dec_model.to(torch_device)
 

tests/encoder_decoder/test_modeling_tf_encoder_decoder.py

@@ -314,6 +314,12 @@ class TFEncoderDecoderMixin:
         encoder_model, decoder_model = self.get_encoder_decoder_model(config, decoder_config)
         enc_dec_model = TFEncoderDecoderModel(encoder=encoder_model, decoder=decoder_model)
 
+        # Generate until max length
+        if hasattr(enc_dec_model.config, "eos_token_id"):
+            enc_dec_model.config.eos_token_id = None
+        if hasattr(enc_dec_model.config, "decoder") and hasattr(enc_dec_model.config.decoder, "eos_token_id"):
+            enc_dec_model.config.decoder.eos_token_id = None
+
         # Bert does not have a bos token id, so use pad_token_id instead
         generated_output = enc_dec_model.generate(
             input_ids, decoder_start_token_id=enc_dec_model.config.decoder.pad_token_id

tests/speech_encoder_decoder/test_modeling_speech_encoder_decoder.py

@@ -347,6 +347,7 @@ class EncoderDecoderMixin:
         enc_dec_model.to(torch_device)
 
         # make sure EOS token is set to None to prevent early stopping of generation
+        if hasattr(enc_dec_model.config, "eos_token_id"):
             enc_dec_model.config.eos_token_id = None
         if hasattr(enc_dec_model.config, "decoder") and hasattr(enc_dec_model.config.decoder, "eos_token_id"):
             enc_dec_model.config.decoder.eos_token_id = None

tests/vision_encoder_decoder/test_modeling_tf_vision_encoder_decoder.py

@@ -300,6 +300,12 @@ class TFVisionEncoderDecoderMixin:
         encoder_model, decoder_model = self.get_encoder_decoder_model(config, decoder_config)
         enc_dec_model = TFVisionEncoderDecoderModel(encoder=encoder_model, decoder=decoder_model)
 
+        # Generate until max length
+        if hasattr(enc_dec_model.config, "eos_token_id"):
+            enc_dec_model.config.eos_token_id = None
+        if hasattr(enc_dec_model.config, "decoder") and hasattr(enc_dec_model.config.decoder, "eos_token_id"):
+            enc_dec_model.config.decoder.eos_token_id = None
+
         # Bert does not have a bos token id, so use pad_token_id instead
         generated_output = enc_dec_model.generate(
             pixel_values, decoder_start_token_id=enc_dec_model.config.decoder.pad_token_id

tests/vision_encoder_decoder/test_modeling_vision_encoder_decoder.py

@@ -269,6 +269,12 @@ class EncoderDecoderMixin:
     def check_encoder_decoder_model_generate(self, config, decoder_config, pixel_values=None, **kwargs):
         encoder_model, decoder_model = self.get_encoder_decoder_model(config, decoder_config)
         enc_dec_model = VisionEncoderDecoderModel(encoder=encoder_model, decoder=decoder_model)
+
+        # Generate until max length
+        if hasattr(enc_dec_model.config, "eos_token_id"):
+            enc_dec_model.config.eos_token_id = None
+        if hasattr(enc_dec_model.config, "decoder") and hasattr(enc_dec_model.config.decoder, "eos_token_id"):
+            enc_dec_model.config.decoder.eos_token_id = None
         enc_dec_model.to(torch_device)
 
         inputs = pixel_values