[Bugfix] Fix interface for Olmo2 on V1 (#14976)

Signed-off-by: Roger Wang <ywang@roblox.com>

vllm/model_executor/models/olmo2.py

@@ -42,7 +42,7 @@ from vllm.model_executor.layers.linear import (MergedColumnParallelLinear,
                                                RowParallelLinear)
 from vllm.model_executor.layers.logits_processor import LogitsProcessor
 from vllm.model_executor.layers.rotary_embedding import get_rope
-from vllm.model_executor.layers.sampler import Sampler, SamplerOutput
+from vllm.model_executor.layers.sampler import SamplerOutput, get_sampler
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead, VocabParallelEmbedding)
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
@@ -283,17 +283,19 @@ class Olmo2Model(nn.Module):
         input_ids: torch.Tensor,
         positions: torch.Tensor,
         intermediate_tensors: Optional[IntermediateTensors],
+        inputs_embeds: Optional[torch.Tensor] = None,
     ) -> Union[torch.Tensor, IntermediateTensors]:
         """
         :param input_ids: A tensor of shape `(batch_size, seq_len)`.
         """
         if get_pp_group().is_first_rank:
+            if inputs_embeds is not None:
+                hidden_states = inputs_embeds
             # Get embeddings of input.
             # shape: (batch_size, seq_len, d_model)
-            inputs_embeds = self.embed_tokens(input_ids)
+            else:
+                hidden_states = self.embed_tokens(input_ids)
 
-            # embed positions
-            hidden_states = inputs_embeds
         else:
             assert intermediate_tensors is not None
             hidden_states = intermediate_tensors["hidden_states"]
@@ -337,7 +339,7 @@ class Olmo2ForCausalLM(nn.Module, SupportsPP):
                 prefix=maybe_prefix(prefix, "lm_head"),
             )
         self.logits_processor = LogitsProcessor(config.vocab_size)
-        self.sampler = Sampler()
+        self.sampler = get_sampler()
         self.make_empty_intermediate_tensors = (
             self.model.make_empty_intermediate_tensors)
 
@@ -346,11 +348,13 @@ class Olmo2ForCausalLM(nn.Module, SupportsPP):
         input_ids: torch.Tensor,
         positions: torch.Tensor,
         intermediate_tensors: Optional[IntermediateTensors] = None,
+        inputs_embeds: Optional[torch.Tensor] = None,
     ) -> Union[torch.Tensor, IntermediateTensors]:
         hidden_states = self.model(
             input_ids=input_ids,
             positions=positions,
             intermediate_tensors=intermediate_tensors,
+            inputs_embeds=inputs_embeds,
         )
         return hidden_states