clang format

src/include/migraphx/operators.hpp

@@ -844,19 +844,15 @@ struct dot
         auto t         = a.type();
 
         // change to support cases like {1, 1, 3, 5} X {1, 1, 5, 6},
-        // which can be handled by numpy. as long as all previous 
+        // which can be handled by numpy. as long as all previous
         // dims are 1 except the last two dims, the two matrices
         // are multipliable
-        if (std::any_of(a.lens().rbegin() + 2, a.lens().rend(), [](auto i) {
-            return (i != 1);
-        }))
+        if(std::any_of(a.lens().rbegin() + 2, a.lens().rend(), [](auto i) { return (i != 1); }))
         {
             MIGRAPHX_THROW("DOT: first matrix, dimensions before matrix dims must be 1");
         }
 
-        if (std::any_of(b.lens().rbegin() + 2, b.lens().rend(), [](auto i) {
-            return (i != 1);
-        }))
+        if(std::any_of(b.lens().rbegin() + 2, b.lens().rend(), [](auto i) { return (i != 1); }))
         {
             MIGRAPHX_THROW("DOT: second matrix, dimensions before matrix dims must be 1");
         }
@@ -865,7 +861,7 @@ struct dot
         if(a.lens()[n_dims - 1] != b.lens()[n_dims - 2])
             MIGRAPHX_THROW("Inner dimensions do not match: {" + to_string_range(a.lens()) +
                            "} x {" + to_string_range(b.lens()) + "}");
-        auto out_lens = a.lens();
+        auto out_lens        = a.lens();
         out_lens[n_dims - 1] = b.lens()[n_dims - 1];
         return {t, out_lens};
     }

src/targets/cpu/gemm.cpp

@@ -14,10 +14,10 @@ template <class T>
 static auto make_mat(tensor_view<T> x)
 {
     const auto& s = x.get_shape();
-    //assert(s.lens().size() == 2);
+    // assert(s.lens().size() == 2);
     std::size_t n_dims = s.lens().size();
-    std::size_t dim_0 = n_dims - 2;
-    std::size_t dim_1 = n_dims - 1;
+    std::size_t dim_0  = n_dims - 2;
+    std::size_t dim_1  = n_dims - 1;
     if(s.transposed())
         return matrix<T>{x.data(), s.lens()[dim_1], s.lens()[dim_0], s.strides()[dim_1]};
     return matrix<T>{x.data(), s.lens()[dim_0], s.lens()[dim_1], s.strides()[dim_0]};
@@ -68,11 +68,11 @@ void migemm_impl(tensor_view<T> cmat,
                  std::false_type)
 {
     std::size_t n_dims = cmat.get_shape().lens().size();
-    std::size_t dim_0 = n_dims - 2;
-    std::size_t dim_1 = n_dims - 1;
-    auto m = cmat.get_shape().lens()[dim_0];
-    auto n = cmat.get_shape().lens()[dim_1];
-    auto k = amat.get_shape().lens()[dim_1];
+    std::size_t dim_0  = n_dims - 2;
+    std::size_t dim_1  = n_dims - 1;
+    auto m             = cmat.get_shape().lens()[dim_0];
+    auto n             = cmat.get_shape().lens()[dim_1];
+    auto k             = amat.get_shape().lens()[dim_1];
 
     assert(amat.get_shape().lens()[dim_1] == bmat.get_shape().lens()[dim_0]);
     assert(m == amat.get_shape().lens()[dim_0]);

src/targets/gpu/gemm.cpp

@@ -76,19 +76,19 @@ argument miopen_gemm::compute(context& ctx,
                               const shape& output_shape,
                               const std::vector<argument>& args) const
 {
-    float alpha     = 1.0f;
-    float beta      = 0.0f;
-    bool transa     = args[0].get_shape().transposed();
-    bool transb     = args[1].get_shape().transposed();
+    float alpha        = 1.0f;
+    float beta         = 0.0f;
+    bool transa        = args[0].get_shape().transposed();
+    bool transb        = args[1].get_shape().transposed();
     std::size_t n_dims = args[0].get_shape().lens().size();
-    std::size_t dim_0 = n_dims - 2;
-    std::size_t dim_1 = n_dims - 1;
-    rocblas_int lda = args[0].get_shape().strides()[transa ? dim_1 : dim_0];
-    rocblas_int ldb = args[1].get_shape().strides()[transb ? dim_1 : dim_0];
-    rocblas_int ldc = args[2].get_shape().strides()[dim_0];
-    rocblas_int m   = output_shape.lens()[dim_0];
-    rocblas_int n   = output_shape.lens()[dim_1];
-    rocblas_int k   = args[0].get_shape().lens()[dim_1];
+    std::size_t dim_0  = n_dims - 2;
+    std::size_t dim_1  = n_dims - 1;
+    rocblas_int lda    = args[0].get_shape().strides()[transa ? dim_1 : dim_0];
+    rocblas_int ldb    = args[1].get_shape().strides()[transb ? dim_1 : dim_0];
+    rocblas_int ldc    = args[2].get_shape().strides()[dim_0];
+    rocblas_int m      = output_shape.lens()[dim_0];
+    rocblas_int n      = output_shape.lens()[dim_1];
+    rocblas_int k      = args[0].get_shape().lens()[dim_1];
     output_shape.visit_type([&](auto as) {
         auto alpha_r    = to_rocblas_type(as(alpha));
         auto beta_r     = to_rocblas_type(as(beta));