loading generation config if it is part of model

Author: eaidova

optimum/intel/openvino/modeling_base.py

@@ -89,7 +89,10 @@ def __init__(
 
         self.model = model
         self.request = None
-        self.generation_config = GenerationConfig.from_model_config(config) if self.can_generate() else None
+        if self.can_generate():
+            self.generation_config = kwargs.get("generation_config", GenerationConfig.from_model_config(config))
+        else:
+            self.generation_config = None
 
         self._openvino_config = None
         if quantization_config:
@@ -240,6 +243,20 @@ def _from_pretrained(
         quantization_config = cls._prepare_weight_quantization_config(quantization_config, load_in_8bit)
 
         model = cls.load_model(model_cache_path, quantization_config=quantization_config)
+
+        try:
+            generation_config = GenerationConfig.from_pretrained(
+                model_id, 
+                token=token, 
+                revision=revision, 
+                subfolder=subfolder, 
+                force_download=force_download, 
+                cache_dir=cache_dir
+            )
+            kwargs["generation_config"] = generation_config
+        except Exception:
+            pass
+
         return cls(
             model,
             config=config,

optimum/intel/openvino/modeling_base_seq2seq.py

@@ -78,7 +78,10 @@ def __init__(
         self.encoder_model = encoder
         self.decoder_model = decoder
         self.decoder_with_past_model = decoder_with_past
-        self.generation_config = GenerationConfig.from_model_config(config) if self.can_generate() else None
+        if self.can_generate():
+            self.generation_config = kwargs.get("generation_config", GenerationConfig.from_model_config(config))
+        else:
+            self.generation_config =  None
         self._openvino_config = None
         if quantization_config:
             self._openvino_config = OVConfig(quantization_config=quantization_config)
@@ -218,6 +221,19 @@ def _from_pretrained(
             if use_cache:
                 decoder_with_past = cls.load_model(file_names["decoder_with_past"], quantization_config)
 
+        try:
+            generation_config = GenerationConfig.from_pretrained(
+                model_id,
+                token=token,
+                revision=revision,
+                cache_dir=cache_dir,
+                force_download=force_download,
+                local_files_only=local_files_only
+            )
+            kwargs["generation_config"] = generation_config
+        except Exception:
+            pass
+
         return cls(
             encoder=encoder,
             decoder=decoder,

optimum/intel/openvino/modeling_decoder.py

@@ -763,6 +763,18 @@ def _from_pretrained(
             init_cls = cls
 
         enable_compilation = kwargs.pop("compile", True) and not load_in_4bit
+        try:
+            generation_config = GenerationConfig.from_pretrained(
+                model_id,
+                token=token,
+                revision=revision,
+                cache_dir=cache_dir,
+                force_download=force_download,
+                local_files_only=local_files_only
+            )
+            kwargs["generation_config"] = generation_config
+        except Exception:
+            pass
         causal_model = init_cls(
             model=model,
             config=config,