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#include "ps_roi_align.h"
#include <ATen/core/dispatch/Dispatcher.h>
#include <torch/library.h>
#include <torch/types.h>
namespace vision {
namespace ops {
std::tuple<at::Tensor, at::Tensor> ps_roi_align(
const at::Tensor& input,
const at::Tensor& rois,
double spatial_scale,
int64_t pooled_height,
int64_t pooled_width,
int64_t sampling_ratio) {
C10_LOG_API_USAGE_ONCE("torchvision.csrc.ops.ps_roi_align.ps_roi_align");
static auto op = c10::Dispatcher::singleton()
.findSchemaOrThrow("torchvision::ps_roi_align", "")
.typed<decltype(ps_roi_align)>();
return op.call(
input, rois, spatial_scale, pooled_height, pooled_width, sampling_ratio);
}
std::tuple<at::Tensor, at::Tensor> ps_roi_align_symint(
const at::Tensor& input,
const at::Tensor& rois,
double spatial_scale,
c10::SymInt pooled_height,
c10::SymInt pooled_width,
int64_t sampling_ratio) {
C10_LOG_API_USAGE_ONCE("torchvision.csrc.ops.ps_roi_align.ps_roi_align");
static auto op = c10::Dispatcher::singleton()
.findSchemaOrThrow("torchvision::ps_roi_align", "")
.typed<decltype(ps_roi_align_symint)>();
return op.call(
input, rois, spatial_scale, pooled_height, pooled_width, sampling_ratio);
}
namespace detail {
at::Tensor _ps_roi_align_backward(
const at::Tensor& grad,
const at::Tensor& rois,
const at::Tensor& channel_mapping,
double spatial_scale,
int64_t pooled_height,
int64_t pooled_width,
int64_t sampling_ratio,
int64_t batch_size,
int64_t channels,
int64_t height,
int64_t width) {
static auto op =
c10::Dispatcher::singleton()
.findSchemaOrThrow("torchvision::_ps_roi_align_backward", "")
.typed<decltype(_ps_roi_align_backward)>();
return op.call(
grad,
rois,
channel_mapping,
spatial_scale,
pooled_height,
pooled_width,
sampling_ratio,
batch_size,
channels,
height,
width);
}
at::Tensor _ps_roi_align_backward_symint(
const at::Tensor& grad,
const at::Tensor& rois,
const at::Tensor& channel_mapping,
double spatial_scale,
c10::SymInt pooled_height,
c10::SymInt pooled_width,
int64_t sampling_ratio,
c10::SymInt batch_size,
c10::SymInt channels,
c10::SymInt height,
c10::SymInt width) {
static auto op =
c10::Dispatcher::singleton()
.findSchemaOrThrow("torchvision::_ps_roi_align_backward", "")
.typed<decltype(_ps_roi_align_backward_symint)>();
return op.call(
grad,
rois,
channel_mapping,
spatial_scale,
pooled_height,
pooled_width,
sampling_ratio,
batch_size,
channels,
height,
width);
}
} // namespace detail
TORCH_LIBRARY_FRAGMENT(torchvision, m) {
m.def(TORCH_SELECTIVE_SCHEMA(
"torchvision::ps_roi_align(Tensor input, Tensor rois, float spatial_scale, SymInt pooled_height, SymInt pooled_width, int sampling_ratio) -> (Tensor, Tensor)"));
m.def(TORCH_SELECTIVE_SCHEMA(
"torchvision::_ps_roi_align_backward(Tensor grad, Tensor rois, Tensor channel_mapping, float spatial_scale, SymInt pooled_height, SymInt pooled_width, int sampling_ratio, SymInt batch_size, SymInt channels, SymInt height, SymInt width) -> Tensor"));
}
} // namespace ops
} // namespace vision
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