[Core] Align whisper closer to other multimodal models (#27292)

Signed-off-by: Russell Bryant <rbryant@redhat.com>

vllm/model_executor/models/whisper.py

@@ -599,15 +599,16 @@ class WhisperModel(nn.Module):
 
     def forward(
         self,
-        input_features: torch.Tensor | list[torch.Tensor] | None,
         input_ids: torch.Tensor | None,
         positions: torch.Tensor,
+        encoder_outputs: list[torch.Tensor],
     ) -> torch.Tensor:
-        encoder_outputs = self.get_encoder_outputs(input_features)
+        assert len(encoder_outputs) in (0, 1)
+        enc_states = encoder_outputs[0] if len(encoder_outputs) == 1 else None
         decoder_outputs = self.decoder(
             input_ids=input_ids,
             positions=positions,
-            encoder_hidden_states=encoder_outputs,
+            encoder_hidden_states=enc_states,
         )
         return decoder_outputs
 
@@ -894,13 +895,15 @@ class WhisperForConditionalGeneration(
         self,
         input_ids: torch.Tensor,
         positions: torch.Tensor,
+        encoder_outputs: list[torch.Tensor] | None = None,
         **kwargs,
     ) -> torch.Tensor:
-        audio_input = self._parse_and_validate_audio_input(**kwargs)
+        if encoder_outputs is None:
+            encoder_outputs = []
         decoder_outputs = self.model(
-            input_features=audio_input["input_features"],
             input_ids=input_ids,
             positions=positions,
+            encoder_outputs=encoder_outputs,
         )
         return decoder_outputs