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Fix deprecated torch API use #380

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Merged
merged 1 commit into from
Sep 6, 2025
Merged

Fix deprecated torch API use #380

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4 changes: 2 additions & 2 deletions detrex/layers/csrc/DCNv3/dcnv3_cuda.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ at::Tensor dcnv3_cuda_forward(const at::Tensor &input, const at::Tensor &offset,
auto columns = output_n.select(0, n);
// AT_DISPATCH_FLOATING_TYPES(
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
input.type(), "ms_deform_attn_forward_cuda", ([&] {
input.scalar_type(), "ms_deform_attn_forward_cuda", ([&] {
dcnv3_im2col_cuda(
at::cuda::getCurrentCUDAStream(),
input.data<scalar_t>() + n * im2col_step_ * per_input_size,
Expand Down Expand Up @@ -145,7 +145,7 @@ dcnv3_cuda_backward(const at::Tensor &input, const at::Tensor &offset,
auto grad_output_g = grad_output_n.select(0, n);
// AT_DISPATCH_FLOATING_TYPES(
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
input.type(), "ms_deform_attn_backward_cuda", ([&] {
input.scalar_type(), "ms_deform_attn_backward_cuda", ([&] {
dcnv3_col2im_cuda(
at::cuda::getCurrentCUDAStream(),
grad_output_g.data<scalar_t>(),
Expand Down
56 changes: 28 additions & 28 deletions detrex/layers/csrc/MsDeformAttn/ms_deform_attn_cuda.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -32,11 +32,11 @@ at::Tensor ms_deform_attn_cuda_forward(
AT_ASSERTM(sampling_loc.is_contiguous(), "sampling_loc tensor has to be contiguous");
AT_ASSERTM(attn_weight.is_contiguous(), "attn_weight tensor has to be contiguous");

AT_ASSERTM(value.type().is_cuda(), "value must be a CUDA tensor");
AT_ASSERTM(spatial_shapes.type().is_cuda(), "spatial_shapes must be a CUDA tensor");
AT_ASSERTM(level_start_index.type().is_cuda(), "level_start_index must be a CUDA tensor");
AT_ASSERTM(sampling_loc.type().is_cuda(), "sampling_loc must be a CUDA tensor");
AT_ASSERTM(attn_weight.type().is_cuda(), "attn_weight must be a CUDA tensor");
AT_ASSERTM(value.device().is_cuda(), "value must be a CUDA tensor");
AT_ASSERTM(spatial_shapes.device().is_cuda(), "spatial_shapes must be a CUDA tensor");
AT_ASSERTM(level_start_index.device().is_cuda(), "level_start_index must be a CUDA tensor");
AT_ASSERTM(sampling_loc.device().is_cuda(), "sampling_loc must be a CUDA tensor");
AT_ASSERTM(attn_weight.device().is_cuda(), "attn_weight must be a CUDA tensor");

const int batch = value.size(0);
const int spatial_size = value.size(1);
Expand All @@ -62,15 +62,15 @@ 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>(),
level_start_index.data<int64_t>(),
sampling_loc.data<scalar_t>() + n * im2col_step_ * per_sample_loc_size,
attn_weight.data<scalar_t>() + n * im2col_step_ * per_attn_weight_size,
value.data_ptr<scalar_t>() + n * im2col_step_ * per_value_size,
spatial_shapes.data_ptr<int64_t>(),
level_start_index.data_ptr<int64_t>(),
sampling_loc.data_ptr<scalar_t>() + n * im2col_step_ * per_sample_loc_size,
attn_weight.data_ptr<scalar_t>() + n * im2col_step_ * per_attn_weight_size,
batch_n, spatial_size, num_heads, channels, num_levels, num_query, num_point,
columns.data<scalar_t>());
columns.data_ptr<scalar_t>());

}));
}
Expand Down Expand Up @@ -98,12 +98,12 @@ std::vector<at::Tensor> ms_deform_attn_cuda_backward(
AT_ASSERTM(attn_weight.is_contiguous(), "attn_weight tensor has to be contiguous");
AT_ASSERTM(grad_output.is_contiguous(), "grad_output tensor has to be contiguous");

AT_ASSERTM(value.type().is_cuda(), "value must be a CUDA tensor");
AT_ASSERTM(spatial_shapes.type().is_cuda(), "spatial_shapes must be a CUDA tensor");
AT_ASSERTM(level_start_index.type().is_cuda(), "level_start_index must be a CUDA tensor");
AT_ASSERTM(sampling_loc.type().is_cuda(), "sampling_loc must be a CUDA tensor");
AT_ASSERTM(attn_weight.type().is_cuda(), "attn_weight must be a CUDA tensor");
AT_ASSERTM(grad_output.type().is_cuda(), "grad_output must be a CUDA tensor");
AT_ASSERTM(value.device().is_cuda(), "value must be a CUDA tensor");
AT_ASSERTM(spatial_shapes.device().is_cuda(), "spatial_shapes must be a CUDA tensor");
AT_ASSERTM(level_start_index.device().is_cuda(), "level_start_index must be a CUDA tensor");
AT_ASSERTM(sampling_loc.device().is_cuda(), "sampling_loc must be a CUDA tensor");
AT_ASSERTM(attn_weight.device().is_cuda(), "attn_weight must be a CUDA tensor");
AT_ASSERTM(grad_output.device().is_cuda(), "grad_output must be a CUDA tensor");

const int batch = value.size(0);
const int spatial_size = value.size(1);
Expand Down Expand Up @@ -132,18 +132,18 @@ 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,
spatial_shapes.data<int64_t>(),
level_start_index.data<int64_t>(),
sampling_loc.data<scalar_t>() + n * im2col_step_ * per_sample_loc_size,
attn_weight.data<scalar_t>() + n * im2col_step_ * per_attn_weight_size,
grad_output_g.data_ptr<scalar_t>(),
value.data_ptr<scalar_t>() + n * im2col_step_ * per_value_size,
spatial_shapes.data_ptr<int64_t>(),
level_start_index.data_ptr<int64_t>(),
sampling_loc.data_ptr<scalar_t>() + n * im2col_step_ * per_sample_loc_size,
attn_weight.data_ptr<scalar_t>() + n * im2col_step_ * per_attn_weight_size,
batch_n, spatial_size, num_heads, channels, num_levels, num_query, num_point,
grad_value.data<scalar_t>() + n * im2col_step_ * per_value_size,
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);
grad_value.data_ptr<scalar_t>() + n * im2col_step_ * per_value_size,
grad_sampling_loc.data_ptr<scalar_t>() + n * im2col_step_ * per_sample_loc_size,
grad_attn_weight.data_ptr<scalar_t>() + n * im2col_step_ * per_attn_weight_size);

}));
}
Expand Down
14 changes: 7 additions & 7 deletions detrex/layers/csrc/MsDeformAttn/ms_deform_im2col_cuda.cuh
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Original file line number Diff line number Diff line change
Expand Up @@ -266,7 +266,7 @@ __global__ void ms_deformable_im2col_gpu_kernel(const int n,
int data_weight_ptr = sampling_index * num_levels * num_point;
int data_loc_w_ptr = data_weight_ptr << 1;
const int qid_stride = num_heads * channels;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride + q_col * qid_stride;
scalar_t col = 0;

for (int l_col=0; l_col < num_levels; ++l_col)
Expand Down Expand Up @@ -342,7 +342,7 @@ __global__ void ms_deformable_col2im_gpu_kernel_shm_blocksize_aware_reduce_v1(co
const int grad_weight_stride = 1;
const int grad_loc_stride = 2;
const int qid_stride = num_heads * channels;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride + q_col * qid_stride;

for (int l_col=0; l_col < num_levels; ++l_col)
{
Expand Down Expand Up @@ -447,7 +447,7 @@ __global__ void ms_deformable_col2im_gpu_kernel_shm_blocksize_aware_reduce_v2(co
const int grad_weight_stride = 1;
const int grad_loc_stride = 2;
const int qid_stride = num_heads * channels;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride + q_col * qid_stride;

for (int l_col=0; l_col < num_levels; ++l_col)
{
Expand Down Expand Up @@ -555,7 +555,7 @@ __global__ void ms_deformable_col2im_gpu_kernel_shm_reduce_v1(const int n,
const int grad_weight_stride = 1;
const int grad_loc_stride = 2;
const int qid_stride = num_heads * channels;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride + q_col * qid_stride;

for (int l_col=0; l_col < num_levels; ++l_col)
{
Expand Down Expand Up @@ -660,7 +660,7 @@ __global__ void ms_deformable_col2im_gpu_kernel_shm_reduce_v2(const int n,
const int grad_weight_stride = 1;
const int grad_loc_stride = 2;
const int qid_stride = num_heads * channels;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride + q_col * qid_stride;

for (int l_col=0; l_col < num_levels; ++l_col)
{
Expand Down Expand Up @@ -773,7 +773,7 @@ __global__ void ms_deformable_col2im_gpu_kernel_shm_reduce_v2_multi_blocks(const
const int grad_weight_stride = 1;
const int grad_loc_stride = 2;
const int qid_stride = num_heads * channels;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride + q_col * qid_stride;

for (int l_col=0; l_col < num_levels; ++l_col)
{
Expand Down Expand Up @@ -883,7 +883,7 @@ __global__ void ms_deformable_col2im_gpu_kernel_gm(const int n,
const int grad_weight_stride = 1;
const int grad_loc_stride = 2;
const int qid_stride = num_heads * channels;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride;
const int data_value_ptr_init_offset = b_col * spatial_size * qid_stride + q_col * qid_stride;

for (int l_col=0; l_col < num_levels; ++l_col)
{
Expand Down