Fix linting

Signed-off-by: Dheeraj Peri <[email protected]>

Author: peri044

core/conversion/converters/impl/pooling.cpp

@@ -80,17 +80,17 @@ bool AdaptivePoolingConverter(
     std::copy_n(out_size.d, out_size.nbDims, out_shape.begin() + (in_shape.size() - out_size.nbDims));
 
     std::vector<int32_t> in_shape_casted(in_shape.begin(), in_shape.end());
-    f.emplace_back(
-        nvinfer1::PluginField("in_shape", in_shape_casted.data(), nvinfer1::PluginFieldType::kINT32, in_shape.size()));
+    f.emplace_back(nvinfer1::PluginField(
+        "in_shape", in_shape_casted.data(), nvinfer1::PluginFieldType::kINT32, in_shape.size()));
 
     std::vector<int32_t> out_shape_casted(out_shape.begin(), out_shape.end());
-    f.emplace_back(
-        nvinfer1::PluginField("out_shape", out_shape_casted.data(), nvinfer1::PluginFieldType::kINT32, out_shape.size()));
+    f.emplace_back(nvinfer1::PluginField(
+        "out_shape", out_shape_casted.data(), nvinfer1::PluginFieldType::kINT32, out_shape.size()));
 
     auto out_size_vec = util::toVec(out_size);
     std::vector<int32_t> out_size_casted(out_size_vec.begin(), out_size_vec.end());
-    f.emplace_back(
-        nvinfer1::PluginField("out_size", out_size_casted.data(), nvinfer1::PluginFieldType::kINT32, out_size_vec.size()));
+    f.emplace_back(nvinfer1::PluginField(
+        "out_size", out_size_casted.data(), nvinfer1::PluginFieldType::kINT32, out_size_vec.size()));
 
     f.emplace_back(nvinfer1::PluginField("scales", nullptr, nvinfer1::PluginFieldType::kFLOAT64, 0));
 

core/plugins/impl/normalize_plugin.cpp

@@ -72,8 +72,8 @@ nvinfer1::DimsExprs NormalizePlugin::getOutputDimensions(
   // For order-0 norm, when the norm dimension is None, it should normalize across all dimensions.
   // TODO: For dim=None, the axes_ passed would have [0, 0, 0] which is obtained through loop counter in TRTorch.
   // Resolve this. For dim=None case, change the axes_ inplace to range(0, axes_.size())
-  bool isAxisNone =
-      std::all_of(axes_.begin(), axes_.end(), [](int32_t i) { return i == 0; }) && ((int32_t) axes_.size() == inputs[0].nbDims);
+  bool isAxisNone = std::all_of(axes_.begin(), axes_.end(), [](int32_t i) { return i == 0; }) &&
+      ((int32_t) axes_.size() == inputs[0].nbDims);
   if (isAxisNone) {
     std::iota(axes_.data(), axes_.data() + axes_.size(), 0);
   }