[Chore] Remove Sampler from Model Code (#17084)

Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>

vllm/model_executor/models/qwen2_audio.py

@@ -22,7 +22,6 @@
 # limitations under the License.
 """Inference-only Qwen2-Audio model compatible with HuggingFace weights."""
 from collections.abc import Iterable, Mapping, Sequence
-from functools import cached_property
 from typing import Any, Optional, Set, Tuple, TypedDict, Union
 
 import torch
@@ -34,7 +33,6 @@ from transformers.models.qwen2_audio import (Qwen2AudioConfig,
 from transformers.models.whisper import WhisperFeatureExtractor
 
 from vllm.config import VllmConfig
-from vllm.model_executor.layers.sampler import SamplerOutput, get_sampler
 from vllm.model_executor.sampling_metadata import SamplingMetadata
 from vllm.multimodal import MULTIMODAL_REGISTRY
 from vllm.multimodal.inputs import (MultiModalDataDict, MultiModalFieldConfig,
@@ -267,13 +265,6 @@ class Qwen2AudioForConditionalGeneration(nn.Module, SupportsMultiModal,
         self.make_empty_intermediate_tensors = (
             self.language_model.make_empty_intermediate_tensors)
 
-    @cached_property
-    def sampler(self):
-        if hasattr(self.language_model, "sampler"):
-            return self.language_model.sampler
-
-        return get_sampler()
-
     def _validate_and_reshape_mm_tensor(self, mm_input: object,
                                         name: str) -> torch.Tensor:
         if not isinstance(mm_input, (torch.Tensor, list)):
@@ -405,13 +396,6 @@ class Qwen2AudioForConditionalGeneration(nn.Module, SupportsMultiModal,
         return self.language_model.compute_logits(hidden_states,
                                                   sampling_metadata)
 
-    def sample(
-        self,
-        logits: torch.Tensor,
-        sampling_metadata: SamplingMetadata,
-    ) -> Optional[SamplerOutput]:
-        return self.language_model.sample(logits, sampling_metadata)
-
     def load_weights(self, weights: Iterable[Tuple[str,
                                                    torch.Tensor]]) -> Set[str]:
         loader = AutoWeightsLoader(self)