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Author: wonjoo-wj

torch_xla/csrc/ops/ops_xla_shape_fn.cpp

@@ -133,7 +133,8 @@ xla::Shape AddcmulOutputShape(const torch::lazy::Value& input,
   return InferOutputShape({GetXlaShape(input), GetXlaShape(t1), GetXlaShape(t2),
                            GetXlaShape(value)},
                           shape_fn);
-                          
+}
+
 xla::Shape AllDimOutputShape(const torch::lazy::Value& input, const int64_t dim,
                              const bool keepdim) {
   auto lower_for_shape_fn =

torch_xla/csrc/ops/ops_xla_shape_fn.h

@@ -38,7 +38,7 @@ xla::Shape AddcmulOutputShape(const torch::lazy::Value& input,
                               const torch::lazy::Value& t1,
                               const torch::lazy::Value& t2,
                               const torch::lazy::Value& value);
-                              
+
 xla::Shape AllDimOutputShape(const torch::lazy::Value& input, const int64_t dim,
                              const bool keepdim);
 

torch_xla/csrc/reduction.cpp

@@ -415,10 +415,10 @@ xla::XlaOp BuildAll(xla::XlaOp input, absl::Span<const int64_t> dimensions,
                     bool keep_reduced_dimensions) {
   const xla::Shape& shape = XlaHelpers::ShapeOfXlaOp(input);
   std::vector<int64_t> canonical_dimensions =
-    torch::lazy::GetCanonicalDimensionIndices(
-        xla::util::ToVector<int64_t>(dimensions), shape.rank());
-  ReductionInfo rinfo =
-      GetReductionInfo(input, shape, canonical_dimensions, keep_reduced_dimensions);
+      torch::lazy::GetCanonicalDimensionIndices(
+          xla::util::ToVector<int64_t>(dimensions), shape.rank());
+  ReductionInfo rinfo = GetReductionInfo(input, shape, canonical_dimensions,
+                                         keep_reduced_dimensions);
   xla::XlaOp init_value = xla::ConstantLiteral(
       input.builder(), xla::LiteralUtil::One(shape.element_type()));
   xla::PrimitiveType result_type =