Do not use deprecated at::Tensor::type()

Summary:
X-link: facebookexternal/vizard#5

X-link: fairinternal/egohowto#72


Replace `tensor.type().scalarType()` with `tensor.scalar_type()` (this be able to get rid of the cast function in pytorch/pytorch#139358 )

Remove extraneous braces around lambdas

Reviewed By: huydhn, r-barnes

Differential Revision: D65308547

projects_oss/detr/detr/src/gpu/ms_deform_attn_cuda.cu

@@ -61,7 +61,7 @@ at::Tensor ms_deform_attn_cuda_forward(
     for (int n = 0; n < batch/im2col_step_; ++n)
     {
         auto columns = output_n.select(0, n);
-        AT_DISPATCH_FLOATING_TYPES(value.type(), "ms_deform_attn_forward_cuda", ([&] {
+        AT_DISPATCH_FLOATING_TYPES(value.scalar_type(), "ms_deform_attn_forward_cuda", [&] {
             ms_deformable_im2col_cuda(at::cuda::getCurrentCUDAStream(),
                 value.data<scalar_t>() + n * im2col_step_ * per_value_size,
                 spatial_shapes.data<int64_t>(),
@@ -71,7 +71,7 @@ at::Tensor ms_deform_attn_cuda_forward(
                 batch_n, spatial_size, num_heads, channels, num_levels, num_query, num_point,
                 columns.data<scalar_t>());
 
-        }));
+        });
     }
 
     output = output.view({batch, num_query, num_heads*channels});
@@ -131,7 +131,7 @@ std::vector<at::Tensor> ms_deform_attn_cuda_backward(
     for (int n = 0; n < batch/im2col_step_; ++n)
     {
         auto grad_output_g = grad_output_n.select(0, n);
-        AT_DISPATCH_FLOATING_TYPES(value.type(), "ms_deform_attn_backward_cuda", ([&] {
+        AT_DISPATCH_FLOATING_TYPES(value.scalar_type(), "ms_deform_attn_backward_cuda", [&] {
             ms_deformable_col2im_cuda(at::cuda::getCurrentCUDAStream(),
                                     grad_output_g.data<scalar_t>(),
                                     value.data<scalar_t>() + n * im2col_step_ * per_value_size,
@@ -144,7 +144,7 @@ std::vector<at::Tensor> ms_deform_attn_cuda_backward(
                                     grad_sampling_loc.data<scalar_t>() + n * im2col_step_ * per_sample_loc_size,
                                     grad_attn_weight.data<scalar_t>() + n * im2col_step_ * per_attn_weight_size);
 
-        }));
+        });
     }
 
     return {