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Author: liubo-intel

src/plugins/intel_cpu/src/nodes/scaled_attn.cpp

@@ -415,10 +415,8 @@ struct MHAKernel<ScaledDotProductAttention::KT_ONEDNN, T> {
         auto m_blocks = (q_len + m_block_size - 1) / m_block_size;
         bool is_xf16 = any_of(precision_of<T>::value, ov::element::bf16, ov::element::f16);
         // packed k, v
-        ov::element::Type attn_mask_precision = ov::element::Type(precision_of<T>::value);
-        if (attention_mask) {
-            attn_mask_precision = attention_mask.get_precision();
-        }
+        auto attn_mask_precision =
+            attention_mask ? attention_mask.get_precision() : ov::element::Type(precision_of<T>::value);
 
         parallel_for2d(B, Hk, [&](size_t b, size_t h) {
             T* k_ptr = &present_key.at<T>({b, h, 0, 0});
@@ -480,8 +478,7 @@ struct MHAKernel<ScaledDotProductAttention::KT_ONEDNN, T> {
                 if (sink_input) {
                     sink = &sink_input.at<float>({b, h, m, 0}, true);
                 }
-                uint8_t* attn_mask_row =
-                    attn_mask_ptr && attn_mask_stride ? attn_mask_ptr + m * attn_mask_stride : attn_mask_ptr;
+                uint8_t* attn_mask_row = attn_mask_ptr ? attn_mask_ptr + m * attn_mask_stride : nullptr;
 
                 attn_softmax(reinterpret_cast<void*>(score),
                              reinterpret_cast<T*>(score),
@@ -646,10 +643,7 @@ struct MHAKernel<ScaledDotProductAttention::KT_ACL, T> {
         auto k_stride_s = present_key.stride(3);
 
         auto m_blocks = (q_len + m_block_size - 1) / m_block_size;
-        ov::element::Type attn_mask_precision = precision;
-        if (attention_mask) {
-            attn_mask_precision = attention_mask.get_precision();
-        }
+        auto attn_mask_precision = attention_mask ? attention_mask.get_precision() : precision;
 
         parallel_for3d(B, H, m_blocks, [&](size_t b, size_t h, size_t m_blk) {
             auto m_start = m_blk * m_block_size;
@@ -709,8 +703,7 @@ struct MHAKernel<ScaledDotProductAttention::KT_ACL, T> {
             for (size_t m = m_start; m < m_end; m++) {
                 // apply attention mask & sofmax
                 auto ncausal = auto_causal ? (kv_len - q_len + m + 1) : kv_len;
-                uint8_t* attn_mask_row =
-                    attn_mask_ptr && attn_mask_stride ? attn_mask_ptr + m * attn_mask_stride : attn_mask_ptr;
+                uint8_t* attn_mask_row = attn_mask_ptr ? attn_mask_ptr + m * attn_mask_stride : nullptr;
                 attn_softmax(reinterpret_cast<void*>(qk + (m - m_start) * kv_len),
                              qk + (m - m_start) * kv_len,
                              d_scale,