fix: allocate tmp based on sgmv kernel if available (#2345)

* fix: allocate tmp based on sgmv kernel if available

* fix: re add copy build artifacts step for punica kernels

Dockerfile

@@ -226,6 +226,8 @@ COPY --from=exllamav2-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-31
 COPY --from=awq-kernels-builder /usr/src/llm-awq/awq/kernels/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
 # Copy build artifacts from eetq kernels builder
 COPY --from=eetq-kernels-builder /usr/src/eetq/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
+# Copy build artifacts from lorax punica kernels builder
+COPY --from=lorax-punica-builder /usr/src/lorax-punica/server/punica_kernels/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages
 # Copy build artifacts from fbgemm builder
 COPY --from=fbgemm-builder /usr/src/fbgemm/fbgemm_gpu/_skbuild/linux-x86_64-3.10/cmake-install /opt/conda/lib/python3.10/site-packages
 # Copy build artifacts from vllm builder

server/text_generation_server/utils/sgmv.py

@@ -151,13 +151,17 @@ def get_tmp_expand_size(size: int) -> int:
 def get_tmp_tensors(
     nsegments: int, lora_rank: int, device: torch.device
 ) -> Tuple[torch.Tensor, torch.Tensor]:
-    if use_cutlass_shrink(lora_rank) and has_sgmv():
+    use_cutlass = use_cutlass_shrink(lora_rank) and has_sgmv()
+    has_sgmv_available = has_sgmv()
+
+    if use_cutlass:
         tmp = get_tmp_tensor_for_size(nsegments, device)
         return tmp, tmp
+    elif has_sgmv_available:
+        return get_tmp_tensor(device), get_tmp_tensor_for_size(nsegments, device)
     else:
-        tmp_shrink = get_tmp_tensor(device)
-        tmp_expand = get_tmp_tensor_for_size_no_kernels(nsegments, device)
-        return tmp_shrink, tmp_expand
+        tmp = get_tmp_tensor_for_size(nsegments, device)
+        return tmp, tmp
 
 
 def lora_a_sgmv_cutlass(