remove dead code

vllm/worker/multi_step_model_runner.py

@@ -4,13 +4,6 @@
 from typing import (TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple,
                     Union)
 
-try:
-    from vllm.attention.backends.flash_attn import FlashAttentionMetadata
-except ModuleNotFoundError:
-    # vllm_flash_attn is not installed, use the identical ROCm FA metadata
-    from vllm.attention.backends.rocm_flash_attn import (
-        ROCmFlashAttentionMetadata as FlashAttentionMetadata)
-
 import torch
 
 from vllm.distributed import get_pp_group
@@ -486,70 +479,6 @@ def _update_sampling_metadata(self, sampling_metadata, num_seqs,
             assert seq_group.seq_len is None  # Decode
             assert seq_group.query_len is None  # Decode
 
-    def _advance_step_flashattn(self, model_input: StatefulModelInput,
-                                out: SamplerOutput) -> StatefulModelInput:
-        frozen_model_input = model_input.frozen_model_input
-        assert frozen_model_input is not None
-        assert frozen_model_input.attn_metadata is not None
-
-        num_seqs = model_input.num_seqs
-        num_queries = model_input.num_queries
-        assert num_seqs > 0
-        assert num_queries > 0
-        assert num_seqs >= num_queries
-
-        attn_metadata = frozen_model_input.attn_metadata
-        assert isinstance(attn_metadata, FlashAttentionMetadata)
-
-        attn_metadata.advance_step(
-            frozen_model_input,
-            model_input.cached_outputs[-1].sampled_token_ids, self.block_size,
-            num_seqs, num_queries)
-
-        if frozen_model_input.seq_lens is not None:
-            for i in range(num_queries):
-                frozen_model_input.seq_lens[i] = attn_metadata.seq_lens[i]
-
-        return model_input
-
-    def _advance_step_flashinfer(
-        self,
-        model_input: StatefulModelInput,
-        out: SamplerOutput,
-    ) -> StatefulModelInput:
-        """Advance the model input for the next step."""
-        # Append the output token to the sequence data.
-        frozen_model_input = model_input.frozen_model_input
-        assert frozen_model_input is not None
-        assert frozen_model_input.attn_metadata is not None
-        attn_metadata = frozen_model_input.attn_metadata
-        num_seqs = model_input.num_seqs
-        num_queries = model_input.num_queries
-
-        sampled_tokens = model_input.cached_outputs[-1].sampled_token_ids
-        assert sampled_tokens is not None
-        assert frozen_model_input.input_tokens is not None
-        frozen_model_input.input_tokens[:num_queries] = sampled_tokens.flatten(
-        )
-
-        # Update GPU tensors
-        ops.advance_step_flashinfer(
-            num_seqs=num_seqs,
-            num_queries=num_queries,
-            block_size=self.block_size,
-            input_tokens=frozen_model_input.input_tokens,
-            sampled_token_ids=frozen_model_input.input_tokens,
-            input_positions=frozen_model_input.input_positions,
-            seq_lens=attn_metadata.seq_lens_tensor,
-            slot_mapping=attn_metadata.slot_mapping,
-            block_tables=attn_metadata.block_tables,
-            paged_kv_indices=attn_metadata.paged_kv_indices,
-            paged_kv_indptr=attn_metadata.paged_kv_indptr,
-            paged_kv_last_page_len=attn_metadata.paged_kv_last_page_len,
-            block_table_bound=attn_metadata.block_table_bound)
-
-        return model_input
-
     def _advance_step(self, model_input: StatefulModelInput,
                       out: SamplerOutput) -> StatefulModelInput:
         if self.attn_backend.get_name() not in MULTI_STEP_ATTENTION_BACKENDS:
@@ -563,24 +492,18 @@ def _advance_step(self, model_input: StatefulModelInput,
         num_queries = model_input.num_queries
         frozen_model_input = model_input.frozen_model_input
         assert frozen_model_input is not None
+        attn_metadata = frozen_model_input.attn_metadata
+        assert attn_metadata is not None
 
-        self.attn_backend.advance_step(
+        attn_metadata.advance_step(
             frozen_model_input,
             sampled_token_ids,
             self.block_size,
             num_seqs,
             num_queries,
         )
 
-        return
-
-        if self.attn_backend.get_name() == "flash-attn":
-            return self._advance_step_flashattn(model_input, out)
-        elif self.attn_backend.get_name() == "flashinfer":
-            return self._advance_step_flashinfer(model_input, out)
-        else:
-            raise ValueError(
-                f"Unsupported attention backend: {self.attn_backend}")
+        return model_input
 
     def load_model(self) -> None:
         return self._base_model_runner.load_model()