refactor(aten::leaky_relu): Apply linting

Signed-off-by: Naren Dasan <[email protected]>
Signed-off-by: Naren Dasan <[email protected]>

Author: narendasan

core/conversion/converters/impl/activation.cpp

@@ -125,22 +125,20 @@ auto acthardtanh TRTORCH_UNUSED =
                LOG_DEBUG("Output shape: " << out_tensor->getDimensions());
                return true;
              }})
-       .pattern(
-            {"aten::leaky_relu(Tensor self, Scalar negative_slope=0.01) -> (Tensor)",
-             [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
-               auto self = args[0].ITensorOrFreeze(ctx);
-               auto negative_slopeScalar = args[1].unwrapToScalar().to<float>();
+        .pattern({"aten::leaky_relu(Tensor self, Scalar negative_slope=0.01) -> (Tensor)",
+                  [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
+                    auto self = args[0].ITensorOrFreeze(ctx);
+                    auto negative_slopeScalar = args[1].unwrapToScalar().to<float>();
 
-               auto new_layer = ctx->net->addActivation(*self, nvinfer1::ActivationType::kLEAKY_RELU);
-               new_layer->setAlpha(negative_slopeScalar);
-
-               new_layer->setName(util::node_info(n).c_str());
-               auto out_tensor = new_layer->getOutput(0);
-               out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], out_tensor);
-               LOG_DEBUG("Output shape: " << out_tensor->getDimensions());
-               return true;
-             }});
+                    auto new_layer = ctx->net->addActivation(*self, nvinfer1::ActivationType::kLEAKY_RELU);
+                    new_layer->setAlpha(negative_slopeScalar);
 
+                    new_layer->setName(util::node_info(n).c_str());
+                    auto out_tensor = new_layer->getOutput(0);
+                    out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], out_tensor);
+                    LOG_DEBUG("Output shape: " << out_tensor->getDimensions());
+                    return true;
+                  }});
 
 } // namespace
 } // namespace impl