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[FBCode->GH] Revert "SymIntify roi_align (#7448)" #7483

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[FBCode->GH] Revert "SymIntify roi_align (#7448)" #7483

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2 changes: 1 addition & 1 deletion torchvision/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
from modulefinder import Module

import torch
from torchvision import _meta_registrations, datasets, io, models, ops, transforms, utils
from torchvision import datasets, io, models, ops, transforms, utils

from .extension import _HAS_OPS

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48 changes: 0 additions & 48 deletions torchvision/_meta_registrations.py
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54 changes: 27 additions & 27 deletions torchvision/csrc/ops/autograd/roi_align_kernel.cpp
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Expand Up @@ -15,19 +15,19 @@ class ROIAlignFunction : public torch::autograd::Function<ROIAlignFunction> {
const torch::autograd::Variable& input,
const torch::autograd::Variable& rois,
double spatial_scale,
c10::SymInt pooled_height,
c10::SymInt pooled_width,
int64_t pooled_height,
int64_t pooled_width,
int64_t sampling_ratio,
bool aligned) {
ctx->saved_data["spatial_scale"] = spatial_scale;
ctx->saved_data["pooled_height"] = pooled_height;
ctx->saved_data["pooled_width"] = pooled_width;
ctx->saved_data["sampling_ratio"] = sampling_ratio;
ctx->saved_data["aligned"] = aligned;
ctx->saved_data["input_shape"] = input.sym_sizes();
ctx->saved_data["input_shape"] = input.sizes();
ctx->save_for_backward({rois});
at::AutoDispatchBelowADInplaceOrView g;
auto result = roi_align_symint(
auto result = roi_align(
input,
rois,
spatial_scale,
Expand All @@ -44,17 +44,17 @@ class ROIAlignFunction : public torch::autograd::Function<ROIAlignFunction> {
// Use data saved in forward
auto saved = ctx->get_saved_variables();
auto rois = saved[0];
auto input_shape = ctx->saved_data["input_shape"].toList();
auto grad_in = detail::_roi_align_backward_symint(
auto input_shape = ctx->saved_data["input_shape"].toIntList();
auto grad_in = detail::_roi_align_backward(
grad_output[0],
rois,
ctx->saved_data["spatial_scale"].toDouble(),
ctx->saved_data["pooled_height"].toSymInt(),
ctx->saved_data["pooled_width"].toSymInt(),
input_shape[0].get().toSymInt(),
input_shape[1].get().toSymInt(),
input_shape[2].get().toSymInt(),
input_shape[3].get().toSymInt(),
ctx->saved_data["pooled_height"].toInt(),
ctx->saved_data["pooled_width"].toInt(),
input_shape[0],
input_shape[1],
input_shape[2],
input_shape[3],
ctx->saved_data["sampling_ratio"].toInt(),
ctx->saved_data["aligned"].toBool());
return {
Expand All @@ -77,16 +77,16 @@ class ROIAlignBackwardFunction
const torch::autograd::Variable& grad,
const torch::autograd::Variable& rois,
double spatial_scale,
c10::SymInt pooled_height,
c10::SymInt pooled_width,
c10::SymInt batch_size,
c10::SymInt channels,
c10::SymInt height,
c10::SymInt width,
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_symint(
auto result = detail::_roi_align_backward(
grad,
rois,
spatial_scale,
Expand All @@ -112,8 +112,8 @@ at::Tensor roi_align_autograd(
const at::Tensor& input,
const at::Tensor& rois,
double spatial_scale,
c10::SymInt pooled_height,
c10::SymInt pooled_width,
int64_t pooled_height,
int64_t pooled_width,
int64_t sampling_ratio,
bool aligned) {
return ROIAlignFunction::apply(
Expand All @@ -130,12 +130,12 @@ at::Tensor roi_align_backward_autograd(
const at::Tensor& grad,
const at::Tensor& rois,
double spatial_scale,
c10::SymInt pooled_height,
c10::SymInt pooled_width,
c10::SymInt batch_size,
c10::SymInt channels,
c10::SymInt height,
c10::SymInt width,
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(
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59 changes: 2 additions & 57 deletions torchvision/csrc/ops/roi_align.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -32,31 +32,6 @@ at::Tensor roi_align(
aligned);
}

at::Tensor roi_align_symint(
const at::Tensor& input, // Input feature map.
const at::Tensor& rois, // List of ROIs to pool over.
double spatial_scale, // The scale of the image features. ROIs will be
// scaled to this.
c10::SymInt pooled_height, // The height of the pooled feature map.
c10::SymInt pooled_width, // The width of the pooled feature
int64_t sampling_ratio, // The number of points to sample in each bin
bool aligned) // The flag for pixel shift
// along each axis.
{
C10_LOG_API_USAGE_ONCE("torchvision.csrc.ops.roi_align.roi_align");
static auto op = c10::Dispatcher::singleton()
.findSchemaOrThrow("torchvision::roi_align", "")
.typed<decltype(roi_align_symint)>();
return op.call(
input,
rois,
spatial_scale,
pooled_height,
pooled_width,
sampling_ratio,
aligned);
}

namespace detail {

at::Tensor _roi_align_backward(
Expand Down Expand Up @@ -89,43 +64,13 @@ at::Tensor _roi_align_backward(
aligned);
}

at::Tensor _roi_align_backward_symint(
const at::Tensor& grad,
const at::Tensor& rois,
double spatial_scale,
c10::SymInt pooled_height,
c10::SymInt pooled_width,
c10::SymInt batch_size,
c10::SymInt channels,
c10::SymInt height,
c10::SymInt width,
int64_t sampling_ratio,
bool aligned) {
static auto op =
c10::Dispatcher::singleton()
.findSchemaOrThrow("torchvision::_roi_align_backward", "")
.typed<decltype(_roi_align_backward_symint)>();
return op.call(
grad,
rois,
spatial_scale,
pooled_height,
pooled_width,
batch_size,
channels,
height,
width,
sampling_ratio,
aligned);
}

} // namespace detail

TORCH_LIBRARY_FRAGMENT(torchvision, m) {
m.def(TORCH_SELECTIVE_SCHEMA(
"torchvision::roi_align(Tensor input, Tensor rois, float spatial_scale, SymInt pooled_height, SymInt pooled_width, int sampling_ratio, bool aligned) -> Tensor"));
"torchvision::roi_align(Tensor input, Tensor rois, float spatial_scale, int pooled_height, int pooled_width, int sampling_ratio, bool aligned) -> Tensor"));
m.def(TORCH_SELECTIVE_SCHEMA(
"torchvision::_roi_align_backward(Tensor grad, Tensor rois, float spatial_scale, SymInt pooled_height, SymInt pooled_width, SymInt batch_size, SymInt channels, SymInt height, SymInt width, int sampling_ratio, bool aligned) -> Tensor"));
"torchvision::_roi_align_backward(Tensor grad, Tensor rois, float spatial_scale, int pooled_height, int pooled_width, int batch_size, int channels, int height, int width, int sampling_ratio, bool aligned) -> Tensor"));
}

} // namespace ops
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22 changes: 0 additions & 22 deletions torchvision/csrc/ops/roi_align.h
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Expand Up @@ -15,15 +15,6 @@ VISION_API at::Tensor roi_align(
int64_t sampling_ratio,
bool aligned);

VISION_API at::Tensor 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,
bool aligned);

namespace detail {

at::Tensor _roi_align_backward(
Expand All @@ -39,19 +30,6 @@ at::Tensor _roi_align_backward(
int64_t sampling_ratio,
bool aligned);

at::Tensor _roi_align_backward_symint(
const at::Tensor& grad,
const at::Tensor& rois,
double spatial_scale,
c10::SymInt pooled_height,
c10::SymInt pooled_width,
c10::SymInt batch_size,
c10::SymInt channels,
c10::SymInt height,
c10::SymInt width,
int64_t sampling_ratio,
bool aligned);

} // namespace detail

} // namespace ops
Expand Down