1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
|
#include "caffe2/operators/quantized/int8_roi_align_op.h"
namespace caffe2 {
REGISTER_CPU_OPERATOR(Int8RoIAlign, int8::Int8RoIAlignOp);
OPERATOR_SCHEMA(Int8RoIAlign)
.NumInputs(2)
.NumOutputs(1)
.SetDoc(R"DOC(
Region of Interest (RoI) align operation as used in Mask R-CNN.
)DOC")
.Arg("Y_scale", "Output tensor quantization scale")
.Arg("Y_zero_point", "Output tensor quantization offset")
.Arg(
"spatial_scale",
"(float) default 1.0; Spatial scale of the input feature map X "
"relative to the input image. E.g., 0.0625 if X has a stride of 16 "
"w.r.t. the input image.")
.Arg("pooled_h", "(int) default 1; Pooled output Y's height.")
.Arg("pooled_w", "(int) default 1; Pooled output Y's width.")
.Arg(
"sampling_ratio",
"(int) default -1; number of sampling points in the interpolation grid "
"used to compute the output value of each pooled output bin. If > 0, "
"then exactly sampling_ratio x sampling_ratio grid points are used. If "
"<= 0, then an adaptive number of grid points are used (computed as "
"ceil(roi_width / pooled_w), and likewise for height).")
.Input(0, "X", "4D Int8 Tensor feature map input of shape (N, C, H, W).")
.Input(
1,
"RoIs",
"2D input of shape (R, 4 or 5) specifying R RoIs "
"representing: batch index in [0, N - 1], x1, y1, x2, y2. The RoI "
"coordinates are in the coordinate system of the input image. For "
"inputs corresponding to a single image, batch index can be excluded "
"to have just 4 columns.")
.Output(
0,
"Y",
"4D Int8 Tensor output of shape (R, C, pooled_h, pooled_w). "
"The r-th batch element "
"is a pooled feature map cooresponding to the r-th RoI.");
} // namespace caffe2
|
