Merge branch 'vllm-project:main' into add-doc-linter

vllm-project · Nov 19, 2024 · defdc21 · defdc21
2 parents 0ad8b0d + fd9f124
commit defdc21
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Showing 5 changed files with 30 additions and 9 deletions.
diff --git a/cmake/cpu_extension.cmake b/cmake/cpu_extension.cmake
@@ -16,10 +16,16 @@ include_directories("${CMAKE_SOURCE_DIR}/csrc")
 #
 # Check the compile flags
 #
-list(APPEND CXX_COMPILE_FLAGS
-    "-fopenmp"
-    "-mf16c"
-    "-DVLLM_CPU_EXTENSION")
+if (CMAKE_SYSTEM_PROCESSOR STREQUAL "ppc64le")
+    list(APPEND CXX_COMPILE_FLAGS
+        "-fopenmp"
+        "-DVLLM_CPU_EXTENSION")
+else()
+    list(APPEND CXX_COMPILE_FLAGS
+        "-fopenmp"
+        "-mf16c"
+        "-DVLLM_CPU_EXTENSION")
+endif()
 
 execute_process(COMMAND cat /proc/cpuinfo
                 RESULT_VARIABLE CPUINFO_RET

diff --git a/csrc/cpu/attention.cpp b/csrc/cpu/attention.cpp
@@ -24,12 +24,20 @@ struct KernelVecType<float> {
 
 template <>
 struct KernelVecType<c10::Half> {
+#ifdef __powerpc64__
+  // Power architecture-specific vector types
+  using q_load_vec_type = vec_op::FP32Vec8;
+  using k_load_vec_type = vec_op::FP32Vec16;
+  using v_load_vec_type = vec_op::FP32Vec16;
+#else
+  // Fallback for other architectures, including x86
   using q_load_vec_type = vec_op::FP16Vec8;
-  using q_vec_type = vec_op::FP32Vec16;
   using k_load_vec_type = vec_op::FP16Vec16;
+  using v_load_vec_type = vec_op::FP16Vec16;
+#endif
+  using q_vec_type = vec_op::FP32Vec16;
   using k_vec_type = vec_op::FP32Vec16;
   using qk_acc_vec_type = vec_op::FP32Vec16;
-  using v_load_vec_type = vec_op::FP16Vec16;
 };
 
 #ifdef __AVX512BF16__

diff --git a/csrc/cpu/quant.cpp b/csrc/cpu/quant.cpp
@@ -25,7 +25,13 @@ struct KernelVecType<c10::BFloat16> {
 
 template <>
 struct KernelVecType<c10::Half> {
+#ifdef __powerpc64__
+  // Power architecture-specific vector type
+  using load_vec_type = vec_op::FP32Vec16;
+#else
+  // Fallback for other architectures
   using load_vec_type = vec_op::FP16Vec16;
+#endif
   using azp_adj_load_vec_type = vec_op::INT32Vec16;
   using cvt_vec_type = vec_op::FP32Vec16;
 };

diff --git a/vllm/model_executor/model_loader/loader.py b/vllm/model_executor/model_loader/loader.py
@@ -105,7 +105,7 @@ def _initialize_model(vllm_config: VllmConfig, prefix: str = "") -> nn.Module:
     msg = ("vLLM model class should accept `vllm_config` and `prefix` as "
            "input arguments. Possibly you have an old-style model class"
            " registered from out of tree and it is used for new vLLM version. "
-           "Check https://docs.vllm.ai/en/latest/design/class_hierarchy.html "
+           "Check https://docs.vllm.ai/en/latest/design/arch_overview.html "
            "for the design and update the model class accordingly.")
     logger.warning(msg)
     logger.warning(

diff --git a/vllm/model_executor/models/pixtral.py b/vllm/model_executor/models/pixtral.py
@@ -331,6 +331,7 @@ class VisionEncoderArgs:
     num_attention_heads: int
     rope_theta: float  # for rope-2D
     image_token_id: int
+    adapter_bias: bool = True
 
 
 def _reshape_for_broadcast(freqs_cis: torch.Tensor,
@@ -595,10 +596,10 @@ def __init__(self, args: VisionEncoderArgs, dim: int):
         self.w_in = nn.Linear(
             args.hidden_size,
             dim,
-            bias=True,
+            bias=args.adapter_bias,
         )
         self.gelu = nn.GELU()
-        self.w_out = nn.Linear(dim, dim, bias=True)
+        self.w_out = nn.Linear(dim, dim, bias=args.adapter_bias)
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         return self.w_out(self.gelu(self.w_in(x)))