fix format. test=develop

lite/kernels/arm/group_norm_compute.cc

@@ -75,10 +75,10 @@ void GroupNormCompute::Run() {
       in_p += 16;
     }
     for (int i = 0; i < remain - 3; i += 4) {
-        float32x4_t in0 = vld1q_f32(in_p);
-        sum1 = vaddq_f32(sum1, in0);
-        summ1 = vmlaq_f32(summ1, in0, in0);
-        in_p += 4;
+      float32x4_t in0 = vld1q_f32(in_p);
+      sum1 = vaddq_f32(sum1, in0);
+      summ1 = vmlaq_f32(summ1, in0, in0);
+      in_p += 4;
     }
     float sum = 0.0;
     float summ = 0.0;
@@ -87,9 +87,9 @@ void GroupNormCompute::Run() {
     summ0 = vaddq_f32(summ0, summ1);
     summ2 = vaddq_f32(summ2, summ3);
     for (int i = 0; i < remain % 4; i++) {
-        sum += *in_p;
-        summ += (*in_p) * (*in_p);
-        in_p++;
+      sum += *in_p;
+      summ += (*in_p) * (*in_p);
+      in_p++;
     }
     sum0 = vaddq_f32(sum0, sum2);
     summ0 = vaddq_f32(summ0, summ2);
@@ -125,37 +125,37 @@ void GroupNormCompute::Run() {
       const float32x4_t vbias = vdupq_n_f32(bias_val);
       const float32x4_t vmean = vdupq_n_f32(mean_val);
       for (int k = 0; k < cnt; k++) {
-          float32x4_t in0 = vld1q_f32(in_p);
-          float32x4_t in1 = vld1q_f32(in_p + 4);
-          float32x4_t in2 = vld1q_f32(in_p + 8);
-          float32x4_t in3 = vld1q_f32(in_p + 12);
-          float32x4_t submean0 = vsubq_f32(in0, vmean);
-          float32x4_t submean1 = vsubq_f32(in1, vmean);
-          float32x4_t submean2 = vsubq_f32(in2, vmean);
-          float32x4_t submean3 = vsubq_f32(in3, vmean);
-          float32x4_t out0 = vmlaq_f32(vbias, submean0, vsstd);
-          float32x4_t out1 = vmlaq_f32(vbias, submean1, vsstd);
-          float32x4_t out2 = vmlaq_f32(vbias, submean2, vsstd);
-          float32x4_t out3 = vmlaq_f32(vbias, submean3, vsstd);
-          vst1q_f32(out_p, out0);
-          vst1q_f32(out_p + 4, out0);
-          vst1q_f32(out_p + 8, out0);
-          vst1q_f32(out_p + 12, out0);
-          in_p += 16;
-          out_p += 16;
+        float32x4_t in0 = vld1q_f32(in_p);
+        float32x4_t in1 = vld1q_f32(in_p + 4);
+        float32x4_t in2 = vld1q_f32(in_p + 8);
+        float32x4_t in3 = vld1q_f32(in_p + 12);
+        float32x4_t submean0 = vsubq_f32(in0, vmean);
+        float32x4_t submean1 = vsubq_f32(in1, vmean);
+        float32x4_t submean2 = vsubq_f32(in2, vmean);
+        float32x4_t submean3 = vsubq_f32(in3, vmean);
+        float32x4_t out0 = vmlaq_f32(vbias, submean0, vsstd);
+        float32x4_t out1 = vmlaq_f32(vbias, submean1, vsstd);
+        float32x4_t out2 = vmlaq_f32(vbias, submean2, vsstd);
+        float32x4_t out3 = vmlaq_f32(vbias, submean3, vsstd);
+        vst1q_f32(out_p, out0);
+        vst1q_f32(out_p + 4, out0);
+        vst1q_f32(out_p + 8, out0);
+        vst1q_f32(out_p + 12, out0);
+        in_p += 16;
+        out_p += 16;
       }
       for (int k = 0; k < remain - 3; k += 4) {
-          float32x4_t in0 = vld1q_f32(in_p);
-          in_p += 4;
-          float32x4_t submean0 = vsubq_f32(in0, vmean);
-          float32x4_t out0 = vmlaq_f32(vbias, submean0, vsstd);
-          vst1q_f32(out_p, out0);
-          out_p += 4;
+        float32x4_t in0 = vld1q_f32(in_p);
+        in_p += 4;
+        float32x4_t submean0 = vsubq_f32(in0, vmean);
+        float32x4_t out0 = vmlaq_f32(vbias, submean0, vsstd);
+        vst1q_f32(out_p, out0);
+        out_p += 4;
       }
       for (int k = 0; k < remain % 4; k++) {
-          *out_p = (*in_p - mean_val) * sstd_val + bias_val;
-          in_p++;
-          out_p++;
+        *out_p = (*in_p - mean_val) * sstd_val + bias_val;
+        in_p++;
+        out_p++;
       }
     } 
   }

lite/operators/deformable_conv_op.cc

@@ -84,5 +84,4 @@ bool DeformableConvOpLite::InferShapeImpl() const {
 }  // namespace lite
 }  // namespace paddle
 
-REGISTER_LITE_OP(deformconv2d,
-                 paddle::lite::operators::DeformableConvOpLite);
+REGISTER_LITE_OP(deformconv2d, paddle::lite::operators::DeformableConvOpLite);

lite/operators/group_norm_op.cc

@@ -39,8 +39,10 @@ bool GroupNormOp::CheckShape() const {
   CHECK_EQ(bias_dims.size(), 1UL) << "Input Bias must have 1 dimensions.";
   CHECK_GT(param_.epsilon, 0.f) << "epsilon should be greater than 0.f";
   CHECK_LT(param_.epsilon, 0.01f) << "epsilon should be less than 0.01f";
-  CHECK_EQ(param_.channels, x_dims[1]) << "Input channels must be equal input_shape[1]";
-  CHECK_EQ(param_.channels % param_.groups, 0) << "channels must be divide groups";
+  CHECK_EQ(param_.channels, x_dims[1])
+      << "Input channels must be equal input_shape[1]";
+  CHECK_EQ(param_.channels % param_.groups, 0)
+      << "channels must be divide groups";
   return true;
 }
 
@@ -54,8 +56,7 @@ bool GroupNormOp::InferShapeImpl() const {
   return true;
 }
 
-bool GroupNormOp::AttachImpl(const cpp::OpDesc& op_desc,
-                                lite::Scope* scope) {
+bool GroupNormOp::AttachImpl(const cpp::OpDesc& op_desc, lite::Scope* scope) {
   param_.x = scope->FindVar(op_desc.Input("X").front())->GetMutable<Tensor>();
   param_.scale =
       scope->FindVar(op_desc.Input("Scale").front())->GetMutable<Tensor>();