Formatting

src/fwd_conv_batchnorm_rewrite.cpp

@@ -12,7 +12,9 @@ void fwd_conv_batchnorm_rewrite::apply(program& p) const
     {
         if(ins->op.name() != "batch_norm_inference")
             continue;
-        if(not std::all_of(ins->arguments.begin()+1, ins->arguments.end(), [](auto arg) { return arg->op.name() == "@literal"; }))
+        if(not std::all_of(ins->arguments.begin() + 1, ins->arguments.end(), [](auto arg) {
+               return arg->op.name() == "@literal";
+           }))
             continue;
 
         auto conv_ins = ins->arguments[0];
@@ -48,9 +50,8 @@ void fwd_conv_batchnorm_rewrite::apply(program& p) const
                 auto new_bias2) {
                 dfor(out_channels, in_channels, height, width)(
                     [&](std::size_t k, std::size_t c, std::size_t h, std::size_t w) {
-                        new_weights2(k, c, h, w) = gamma2(k) /
-                                                   std::sqrt(variance2(k) + epsilon) *
-                                                   weights2(k, c, h, w);
+                        new_weights2(k, c, h, w) =
+                            gamma2(k) / std::sqrt(variance2(k) + epsilon) * weights2(k, c, h, w);
                         new_bias2(k, c, h, w) =
                             bias2(k) - (mean2(k) / std::sqrt(variance2(k) + epsilon));
                     });
@@ -58,8 +59,7 @@ void fwd_conv_batchnorm_rewrite::apply(program& p) const
         // Replace convolution instruction with updated weights
         auto l_weights = p.add_literal({weights.get_shape(), new_weights.data()});
         auto l_bias    = p.add_literal({bias.get_shape(), new_bias.data()});
-        auto c =
-            p.replace_instruction(conv_ins, conv_op, {conv_ins->arguments[0], l_weights});
+        auto c = p.replace_instruction(conv_ins, conv_op, {conv_ins->arguments[0], l_weights});
         p.replace_instruction(ins, add{}, {c, l_bias});
     }
 }