Removing instances of ScalarType, still need to change macros

csrc/fused_adam_cuda_kernel.cu

@@ -187,7 +187,7 @@ void fused_adam_cuda(
             AT_ASSERTM(p.scalar_type() == at::ScalarType::Float, "expected parameter to be of float type");
 //dispatch is done on the gradient type
             using namespace at; // prevents "toString is undefined" errors
-            DISPATCH_FLOAT_AND_HALF(g.scalar_type(), 0, "adam_cuda_kernel", 
+            DISPATCH_FLOAT_AND_HALF(g.scalar_type(), 0, "adam_cuda_kernel",
                 using accscalar_t = at::acc_type<scalar_t_0, true>;
                 adam_cuda_kernel<accscalar_t, scalar_t_0><<<blocks,threadsPerBlock, 0, stream>>>(
                         p.data<accscalar_t>(),
@@ -256,9 +256,9 @@ void fused_adam_cuda_mt(
     size_t tl_sz = tensor_lists.size();
     AT_ASSERTM(tl_sz == 4 || tl_sz == 5, "expected tensor lists of size 4 or 5");
 
-    if (tensor_lists[3][0].type().scalarType() == at::ScalarType::Half) {
+    if (tensor_lists[3][0].scalar_type() == at::ScalarType::Half) {
 //alher values should be fp32 for half gradients
-        AT_ASSERTM(tensor_lists[0][0].type().scalarType() == at::ScalarType::Float, "expected parameter to be of float type");
+        AT_ASSERTM(tensor_lists[0][0].scalar_type() == at::ScalarType::Float, "expected parameter to be of float type");
 //dich is done on the gradient type
         if (tl_sz == 5) {
             AT_DISPATCH_FLOATING_TYPES_AND_HALF(tensor_lists[3][0].type(), "adam_cuda_mt_kernel", ([&] {