add prelu neon impl

paddle/math/Matrix.cpp

@@ -28,6 +28,7 @@ limitations under the License. */
 #include "hl_top_k.h"
 #include "paddle/utils/Logging.h"
 
+#include "NEONFunctions.h"
 #include "paddle/function/GemmFunctor.h"
 #include "paddle/utils/ThreadLocal.h"
 
@@ -4157,16 +4158,36 @@ void CpuMatrix::print(std::ostream& os) const {
 void CpuMatrix::paramReluForward(Matrix& data, Matrix& W) {
   real* input = data.getData();
   real* w = W.getData();
+  real* output = data_;
   size_t numElements = data.getWidth();
   size_t numSamples = data.getHeight();
   size_t paraSize = W.getHeight() * W.getWidth();
   CHECK(!(numElements % paraSize));  // this check from ParameterReluLayer::init
+
   size_t partial_sum = numElements / paraSize;
+  if (paraSize == numElements) {
+    for (size_t n = 0; n < numSamples * numElements; ++n) {
+      output[n] = input[n] > 0 ? input[n] : input[n] * w[n % numElements];
+    }
+    return;
+  }
+
+#if defined(__ARM_NEON__) || defined(__ARM_NEON)
+  for (size_t n = 0; n < numSamples; ++n) {
+    for (size_t i = 0; i < paraSize; i++) {
+      neon::prelu(
+          input + i * partial_sum, w[i], output + i * partial_sum, partial_sum);
+    }
+    input = input + numElements;
+    output = output + numElements;
+  }
+#else
   for (size_t n = 0, k = 0; n < numSamples; ++n) {
     for (size_t i = 0; i < numElements; ++i, ++k) {
-      data_[k] = input[k] > 0 ? input[k] : input[k] * w[i / partial_sum];
+      output[k] = input[k] > 0 ? input[k] : input[k] * w[i / partial_sum];
     }
   }
+#endif
 }
 
 void CpuMatrix::paramReluBackwardW(Matrix& oGrad, Matrix& data) {

paddle/math/NEONFunctions.cpp

@@ -49,6 +49,46 @@ void relu(const float* a, float* b, int len) {
   }
 }
 
+// b[i] = a[i] > 0.0f ? a[i] : a[i] * w
+void prelu(const float* a, float w, float* b, int len) {
+  int offset = len % 16;
+  float32x4_t ma0, ma1, ma2, ma3;
+
+  float32x4_t zero = vdupq_n_f32(0.f);
+  float32x4_t vw = vdupq_n_f32(w);
+
+  for (int k = 0; k < len / 16; k++, a += 16, b += 16) {
+    ma0 = vld1q_f32(a);
+    ma1 = vld1q_f32(a + 4);
+    ma2 = vld1q_f32(a + 8);
+    ma3 = vld1q_f32(a + 12);
+
+    uint32x4_t flag0 = vcgtq_f32(ma0, zero);
+    uint32x4_t flag1 = vcgtq_f32(ma1, zero);
+    uint32x4_t flag2 = vcgtq_f32(ma2, zero);
+    uint32x4_t flag3 = vcgtq_f32(ma3, zero);
+
+    float32x4_t mul0 = vmulq_f32(ma0, vw);
+    float32x4_t mul1 = vmulq_f32(ma1, vw);
+    float32x4_t mul2 = vmulq_f32(ma2, vw);
+    float32x4_t mul3 = vmulq_f32(ma3, vw);
+
+    ma0 = vbslq_f32(flag0, ma0, mul0);
+    ma1 = vbslq_f32(flag1, ma1, mul1);
+    ma2 = vbslq_f32(flag2, ma2, mul2);
+    ma3 = vbslq_f32(flag3, ma3, mul3);
+
+    vst1q_f32(b, ma0);
+    vst1q_f32(b + 4, ma1);
+    vst1q_f32(b + 8, ma2);
+    vst1q_f32(b + 12, ma3);
+  }
+
+  for (int i = 0; i < offset; i++) {
+    b[i] = a[i] > 0.0f ? a[i] : a[i] * w;
+  }
+}
+
 }  // namespace neon
 }  // namespace paddle
 

paddle/math/NEONFunctions.h

@@ -18,6 +18,7 @@ namespace paddle {
 namespace neon {
 
 void relu(const float* a, float* b, int len);
+void prelu(const float* a, float w, float* b, int len);
 
 }  // namespace neon
 }  // namespace paddle