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Remove unnecessary dispatcher/registration code #4205

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dbbf111
maybe we can remove some stuff
NicolasHug Jul 23, 2021
c56ea13
Merge branch 'master' into remove_dead_code_maybe
NicolasHug Jul 23, 2021
4737985
remove more stuff
NicolasHug Jul 24, 2021
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101 changes: 0 additions & 101 deletions torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -121,67 +121,6 @@ class DeformConv2dFunction
}
};

// TODO: There should be an easier way to do this
class DeformConv2dBackwardFunction
: public torch::autograd::Function<DeformConv2dBackwardFunction> {
public:
static torch::autograd::variable_list forward(
torch::autograd::AutogradContext* ctx,
const torch::autograd::Variable& grad,
const torch::autograd::Variable& input,
const torch::autograd::Variable& weight,
const torch::autograd::Variable& offset,
const torch::autograd::Variable& mask,
const torch::autograd::Variable& bias,
int64_t stride_h,
int64_t stride_w,
int64_t pad_h,
int64_t pad_w,
int64_t dilation_h,
int64_t dilation_w,
int64_t groups,
int64_t offset_groups,
bool use_mask) {
at::AutoDispatchBelowADInplaceOrView g;
auto result = detail::_deform_conv2d_backward(
grad,
input,
weight,
offset,
mask,
bias,
stride_h,
stride_w,
pad_h,
pad_w,
dilation_h,
dilation_w,
groups,
offset_groups,
use_mask);

auto grad_input = std::get<0>(result);
auto grad_weight = std::get<1>(result);
auto grad_offset = std::get<2>(result);
auto grad_mask = std::get<3>(result);
auto grad_bias = std::get<4>(result);

return {
grad_input,
grad_weight,
grad_offset,
grad_mask,
grad_bias,
};
}

static torch::autograd::variable_list backward(
torch::autograd::AutogradContext* ctx,
const torch::autograd::variable_list& grad_output) {
TORCH_CHECK(0, "double backwards on deform_conv2d not supported");
}
};

at::Tensor deform_conv2d_autograd(
const at::Tensor& input,
const at::Tensor& weight,
Expand Down Expand Up @@ -214,52 +153,12 @@ at::Tensor deform_conv2d_autograd(
use_mask)[0];
}

std::tuple<at::Tensor, at::Tensor, at::Tensor, at::Tensor, at::Tensor>
deform_conv2d_backward_autograd(
const at::Tensor& grad,
const at::Tensor& input,
const at::Tensor& weight,
const at::Tensor& offset,
const at::Tensor& mask,
const at::Tensor& bias,
int64_t stride_h,
int64_t stride_w,
int64_t pad_h,
int64_t pad_w,
int64_t dilation_h,
int64_t dilation_w,
int64_t groups,
int64_t offset_groups,
bool use_mask) {
auto result = DeformConv2dBackwardFunction::apply(
grad,
input,
weight,
offset,
mask,
bias,
stride_h,
stride_w,
pad_h,
pad_w,
dilation_h,
dilation_w,
groups,
offset_groups,
use_mask);

return std::make_tuple(result[0], result[1], result[2], result[3], result[4]);
}

} // namespace

TORCH_LIBRARY_IMPL(torchvision, Autograd, m) {
m.impl(
TORCH_SELECTIVE_NAME("torchvision::deform_conv2d"),
TORCH_FN(deform_conv2d_autograd));
m.impl(
TORCH_SELECTIVE_NAME("torchvision::_deform_conv2d_backward"),
TORCH_FN(deform_conv2d_backward_autograd));
}

} // namespace ops
Expand Down
70 changes: 0 additions & 70 deletions torchvision/csrc/ops/autograd/ps_roi_align_kernel.cpp
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -72,47 +72,6 @@ class PSROIAlignFunction
}
};

// TODO: There should be an easier way to do this
class PSROIAlignBackwardFunction
: public torch::autograd::Function<PSROIAlignBackwardFunction> {
public:
static torch::autograd::variable_list forward(
torch::autograd::AutogradContext* ctx,
const torch::autograd::Variable& grad,
const torch::autograd::Variable& rois,
const torch::autograd::Variable& 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) {
at::AutoDispatchBelowADInplaceOrView g;
auto grad_in = detail::_ps_roi_align_backward(
grad,
rois,
channel_mapping,
spatial_scale,
pooled_height,
pooled_width,
sampling_ratio,
batch_size,
channels,
height,
width);

return {grad_in};
}

static torch::autograd::variable_list backward(
torch::autograd::AutogradContext* ctx,
const torch::autograd::variable_list& grad_output) {
TORCH_CHECK(0, "double backwards on ps_roi_align not supported");
}
};

std::tuple<at::Tensor, at::Tensor> ps_roi_align_autograd(
const at::Tensor& input,
const at::Tensor& rois,
Expand All @@ -126,41 +85,12 @@ std::tuple<at::Tensor, at::Tensor> ps_roi_align_autograd(
return std::make_tuple(result[0], result[1]);
}

at::Tensor ps_roi_align_backward_autograd(
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) {
return PSROIAlignBackwardFunction::apply(
grad,
rois,
channel_mapping,
spatial_scale,
pooled_height,
pooled_width,
sampling_ratio,
batch_size,
channels,
height,
width)[0];
}

} // namespace

TORCH_LIBRARY_IMPL(torchvision, Autograd, m) {
m.impl(
TORCH_SELECTIVE_NAME("torchvision::ps_roi_align"),
TORCH_FN(ps_roi_align_autograd));
m.impl(
TORCH_SELECTIVE_NAME("torchvision::_ps_roi_align_backward"),
TORCH_FN(ps_roi_align_backward_autograd));
}

} // namespace ops
Expand Down
66 changes: 0 additions & 66 deletions torchvision/csrc/ops/autograd/ps_roi_pool_kernel.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -62,45 +62,6 @@ class PSROIPoolFunction : public torch::autograd::Function<PSROIPoolFunction> {
}
};

// TODO: There should be an easier way to do this
class PSROIPoolBackwardFunction
: public torch::autograd::Function<PSROIPoolBackwardFunction> {
public:
static torch::autograd::variable_list forward(
torch::autograd::AutogradContext* ctx,
const torch::autograd::Variable& grad,
const torch::autograd::Variable& rois,
const torch::autograd::Variable& channel_mapping,
double spatial_scale,
int64_t pooled_height,
int64_t pooled_width,
int64_t batch_size,
int64_t channels,
int64_t height,
int64_t width) {
at::AutoDispatchBelowADInplaceOrView g;
auto grad_in = detail::_ps_roi_pool_backward(
grad,
rois,
channel_mapping,
spatial_scale,
pooled_height,
pooled_width,
batch_size,
channels,
height,
width);

return {grad_in};
}

static torch::autograd::variable_list backward(
torch::autograd::AutogradContext* ctx,
const torch::autograd::variable_list& grad_output) {
TORCH_CHECK(0, "double backwards on ps_roi_pool not supported");
}
};

std::tuple<at::Tensor, at::Tensor> ps_roi_pool_autograd(
const at::Tensor& input,
const at::Tensor& rois,
Expand All @@ -113,39 +74,12 @@ std::tuple<at::Tensor, at::Tensor> ps_roi_pool_autograd(
return std::make_tuple(result[0], result[1]);
}

at::Tensor ps_roi_pool_backward_autograd(
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 batch_size,
int64_t channels,
int64_t height,
int64_t width) {
return PSROIPoolBackwardFunction::apply(
grad,
rois,
channel_mapping,
spatial_scale,
pooled_height,
pooled_width,
batch_size,
channels,
height,
width)[0];
}

} // namespace

TORCH_LIBRARY_IMPL(torchvision, Autograd, m) {
m.impl(
TORCH_SELECTIVE_NAME("torchvision::ps_roi_pool"),
TORCH_FN(ps_roi_pool_autograd));
m.impl(
TORCH_SELECTIVE_NAME("torchvision::_ps_roi_pool_backward"),
TORCH_FN(ps_roi_pool_backward_autograd));
}

} // namespace ops
Expand Down
69 changes: 0 additions & 69 deletions torchvision/csrc/ops/autograd/roi_align_kernel.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -68,46 +68,6 @@ class ROIAlignFunction : public torch::autograd::Function<ROIAlignFunction> {
}
};

// TODO: There should be an easier way to do this
class ROIAlignBackwardFunction
: public torch::autograd::Function<ROIAlignBackwardFunction> {
public:
static torch::autograd::variable_list forward(
torch::autograd::AutogradContext* ctx,
const torch::autograd::Variable& grad,
const torch::autograd::Variable& rois,
double spatial_scale,
int64_t pooled_height,
int64_t pooled_width,
int64_t batch_size,
int64_t channels,
int64_t height,
int64_t width,
int64_t sampling_ratio,
bool aligned) {
at::AutoDispatchBelowADInplaceOrView g;
auto result = detail::_roi_align_backward(
grad,
rois,
spatial_scale,
pooled_height,
pooled_width,
batch_size,
channels,
height,
width,
sampling_ratio,
aligned);
return {result};
}

static torch::autograd::variable_list backward(
torch::autograd::AutogradContext* ctx,
const torch::autograd::variable_list& grad_output) {
TORCH_CHECK(0, "double backwards on roi_align not supported");
}
};

at::Tensor roi_align_autograd(
const at::Tensor& input,
const at::Tensor& rois,
Expand All @@ -126,41 +86,12 @@ at::Tensor roi_align_autograd(
aligned)[0];
}

at::Tensor roi_align_backward_autograd(
const at::Tensor& grad,
const at::Tensor& rois,
double spatial_scale,
int64_t pooled_height,
int64_t pooled_width,
int64_t batch_size,
int64_t channels,
int64_t height,
int64_t width,
int64_t sampling_ratio,
bool aligned) {
return ROIAlignBackwardFunction::apply(
grad,
rois,
spatial_scale,
pooled_height,
pooled_width,
batch_size,
channels,
height,
width,
sampling_ratio,
aligned)[0];
}

} // namespace

TORCH_LIBRARY_IMPL(torchvision, Autograd, m) {
m.impl(
TORCH_SELECTIVE_NAME("torchvision::roi_align"),
TORCH_FN(roi_align_autograd));
m.impl(
TORCH_SELECTIVE_NAME("torchvision::_roi_align_backward"),
TORCH_FN(roi_align_backward_autograd));
}

} // namespace ops
Expand Down
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