clang format

src/include/migraphx/op/quant_dot.hpp

@@ -34,7 +34,7 @@ struct quant_dot
         const shape& a = inputs.at(0);
         const shape& b = inputs.at(1);
         auto t         = a.type();
-        if (t != shape::int8_type)
+        if(t != shape::int8_type)
         {
             MIGRAPHX_THROW("QUANT_DOT: only support data type int8_t");
         }
@@ -48,16 +48,16 @@ struct quant_dot
         if(!std::equal(
                a.lens().rbegin() + 2, a.lens().rend(), b.lens().rbegin() + 2, b.lens().rend()))
         {
-            MIGRAPHX_THROW("QUANT_DOT: batch size of A and B mismatch: {" + to_string_range(a.lens()) +
-                           "} x {" + to_string_range(b.lens()) + "}");
+            MIGRAPHX_THROW("QUANT_DOT: batch size of A and B mismatch: {" +
+                           to_string_range(a.lens()) + "} x {" + to_string_range(b.lens()) + "}");
         }
 
         std::size_t dim_0 = a.lens().size() - 2;
         std::size_t dim_1 = a.lens().size() - 1;
         if(a.lens()[dim_1] != b.lens()[dim_0])
         {
-            MIGRAPHX_THROW("QUANT_DOT: inner dimensions do not match: {" + to_string_range(a.lens()) +
-                           "} x {" + to_string_range(b.lens()) + "}");
+            MIGRAPHX_THROW("QUANT_DOT: inner dimensions do not match: {" +
+                           to_string_range(a.lens()) + "} x {" + to_string_range(b.lens()) + "}");
         }
 
         auto out_lens   = a.lens();
@@ -69,7 +69,7 @@ struct quant_dot
                            "}, cannot add to operand A * B: {" + to_string_range(out_lens) + "}");
         }
 
-        if (inputs.size() == 3 && inputs.at(2).type() != shape::int32_type)
+        if(inputs.size() == 3 && inputs.at(2).type() != shape::int32_type)
         {
             MIGRAPHX_THROW("QUANT_DOT: operand C type must be int32");
         }

src/targets/cpu/gemm.cpp

@@ -45,12 +45,8 @@ struct is_fast_gemm_type<float> : std::true_type
 };
 
 template <class T, class F>
-void migemm_impl(tensor_view<T> cmat,
-                 tensor_view<T> amat,
-                 tensor_view<T> bmat,
-                 F alpha,
-                 F beta,
-                 std::true_type)
+void migemm_impl(
+    tensor_view<T> cmat, tensor_view<T> amat, tensor_view<T> bmat, F alpha, F beta, std::true_type)
 {
     visit_mat(amat, [&](const auto& a) {
         visit_mat(bmat, [&](const auto& b) {
@@ -67,12 +63,8 @@ void migemm_impl(tensor_view<T> cmat,
 }
 
 template <class T, class F>
-void migemm_impl(tensor_view<T> cmat,
-                 tensor_view<T> amat,
-                 tensor_view<T> bmat,
-                 F alpha,
-                 F beta,
-                 std::false_type)
+void migemm_impl(
+    tensor_view<T> cmat, tensor_view<T> amat, tensor_view<T> bmat, F alpha, F beta, std::false_type)
 {
     std::size_t n_dims = cmat.get_shape().lens().size();
     std::size_t dim_0  = n_dims - 2;
@@ -96,8 +88,7 @@ void migemm_impl(tensor_view<T> cmat,
 }
 
 template <class T, class F>
-void migemm_impl(
-    tensor_view<T> cmat, tensor_view<T> amat, tensor_view<T> bmat, F alpha, F beta)
+void migemm_impl(tensor_view<T> cmat, tensor_view<T> amat, tensor_view<T> bmat, F alpha, F beta)
 {
     auto lens = amat.get_shape().lens();
     bool batch_mul =
@@ -113,9 +104,8 @@ void migemm_impl(
     }
 }
 
-template<class F>
-void migemm(
-    const argument& c_arg, const argument& a_arg, const argument& b_arg, F alpha, F beta)
+template <class F>
+void migemm(const argument& c_arg, const argument& a_arg, const argument& b_arg, F alpha, F beta)
 {
     visit_all(c_arg, a_arg, b_arg)(
         [&](auto cmat, auto amat, auto bmat) { migemm_impl(cmat, amat, bmat, alpha, beta); });

src/targets/cpu/include/migraphx/cpu/gemm.hpp

@@ -8,9 +8,8 @@ namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace cpu {
 
-template<class T>
-void migemm(
-    const argument& c_arg, const argument& a_arg, const argument& b_arg, T alpha, T beta);
+template <class T>
+void migemm(const argument& c_arg, const argument& a_arg, const argument& b_arg, T alpha, T beta);
 
 } // namespace cpu
 } // namespace MIGRAPHX_INLINE_NS

src/targets/cpu/lowering.cpp

@@ -435,15 +435,13 @@ struct cpu_quant_gemm
         argument arg_0{{shape::int32_type, {args.at(0).get_shape().lens()}}};
         argument arg_1{{shape::int32_type, {args.at(1).get_shape().lens()}}};
         arg_0.visit([&](auto output) {
-            args.at(0).visit([&](auto input) {
-                std::copy(input.begin(), input.end(), output.begin());
-            });
+            args.at(0).visit(
+                [&](auto input) { std::copy(input.begin(), input.end(), output.begin()); });
         });
 
         arg_1.visit([&](auto output) {
-            args.at(1).visit([&](auto input) {
-                std::copy(input.begin(), input.end(), output.begin());
-            });
+            args.at(1).visit(
+                [&](auto input) { std::copy(input.begin(), input.end(), output.begin()); });
         });
 
         if(args.size() == 3)
@@ -879,7 +877,7 @@ struct cpu_apply
         apply_map["im2col"]      = extend_op<cpu_im2col, op::im2col>();
         apply_map["convolution"] = extend_op<cpu_convolution, op::convolution>();
         apply_map["dot"]         = extend_op<cpu_gemm, op::dot>();
-        apply_map["quant_dot"]         = extend_op<cpu_quant_gemm, op::quant_dot>();
+        apply_map["quant_dot"]   = extend_op<cpu_quant_gemm, op::quant_dot>();
         apply_map["batch_norm_inference"] =
             extend_op<cpu_batch_norm_inference, op::batch_norm_inference>();
         apply_map["lrn"]        = extend_op<cpu_lrn, op::lrn>();