[codex] Remove vLLM layerwise reload alias patch

src/prime_rl/inference/patches.py

@@ -18,7 +18,6 @@ def transformers_v5_compat():
     _patch_qwen35_lora()
     _patch_lora_key_prefix()
     monkey_patch_deep_gemm_silu_mul_quant_int64()
-    monkey_patch_vllm_layerwise_reload_alias_buffers()
     monkey_patch_vllm_padded_input_scrub()
     monkey_patch_return_routed_experts_with_nixl_connector()
 
@@ -67,38 +66,6 @@ def _post_init(config: VllmConfig):
     logger.warning("Enabled vLLM routed-experts capture with NIXL connector patch.")
 
 
-def monkey_patch_vllm_layerwise_reload_alias_buffers():
-    # vLLM's layerwise reload materializes each buffer as an independent tensor
-    # and then copies it back into the original kernel storage. When a buffer
-    # aliases a parameter (e.g. NemotronH Mamba's mixer.conv_weights, a view of
-    # mixer.conv1d.weight), the buffer copy stamps garbage into the parameter's
-    # storage *after* the parameter has been correctly reloaded. Skip the copy
-    # for any buffer that shares storage with a parameter; _place_kernel_tensors
-    # re-registers the original view, which trivially reflects the parameter.
-    # Remove this patch once https://github.com/vllm-project/vllm/pull/42481 is
-    # included in the vLLM release we pin/use.
-    from vllm.logger import init_logger
-    from vllm.model_executor.model_loader.reload import layerwise as reload_layerwise
-
-    logger = init_logger(__name__)
-
-    def _copy_and_restore_kernel_tensors(layer: torch.nn.Module, info: reload_layerwise.LayerReloadingInfo):
-        assert info.kernel_tensors is not None
-        parameters, buffers = info.kernel_tensors
-        param_storage_ptrs = {p.untyped_storage().data_ptr() for p in layer.parameters(recurse=True)}
-        for name, param in parameters.items():
-            param.data.copy_(getattr(layer, name))
-        for name, buffer in buffers.items():
-            if buffer.untyped_storage().data_ptr() in param_storage_ptrs:
-                continue
-            buffer.data.copy_(getattr(layer, name))
-
-        reload_layerwise._place_kernel_tensors(layer, info)
-
-    reload_layerwise._copy_and_restore_kernel_tensors = _copy_and_restore_kernel_tensors
-    logger.warning("Enabled vLLM layerwise reload alias-buffer patch.")
-
-
 @triton.jit
 def _silu_mul_per_token_group_quant_fp8_colmajor_int64_kernel(
     y_ptr,