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Merge pull request #22362 from fengyuentau:conv_asym_pad_fuse

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Remove asymmetric padding in Conv layer since it is supported in CPU backend
This commit is contained in:
Alexander Smorkalov
2022-08-29 17:56:17 +03:00
committed by GitHub
parent 2619099fe5 2959286eb5
commit 1fd45a1b85
6 changed files with 46 additions and 86 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+18 -19
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@@ -101,10 +101,6 @@ public:
if (kernel_size.size() == 2) {
kernel = Size(kernel_size[1], kernel_size[0]);
stride = Size(strides[1], strides[0]);
for (int i = 0; i < pads_begin.size(); i++) {
if (pads_begin[i] != pads_end[i])
CV_Error(Error::StsNotImplemented, "Unsupported asymmetric padding in convolution layer");
}
pad = Size(pads_begin[1], pads_begin[0]);
dilation = Size(dilations[1], dilations[0]);
@@ -166,10 +162,6 @@ public:
}
getConvPoolPaddings(inpShape, kernel_size, strides, padMode, pads_begin, pads_end);
if (pads_begin.size() == 2) {
for (int i = 0; i < pads_begin.size(); i++) {
if (pads_begin[i] != pads_end[i])
CV_Error(Error::StsNotImplemented, "Unsupported asymmetric padding in convolution layer");
}
pad = Size(pads_begin[1], pads_begin[0]);
}
fusedWeights = false;
@@ -1811,7 +1803,10 @@ public:
config.in_shape = shape(inputs[0]);
config.out_shape = shape(outputs[0]);
config.kernel = kernel;
config.pad = pad;
// pads_begin: 0 - pad_top, 1 - pad_left
// pads_end: 0 - pad_bottom, 1 - pad_right
std::vector<int> pads = {int(pads_begin[0]), int(pads_end[0]), int(pads_begin[1]), int(pads_end[1])};
config.pads = pads;
config.stride = stride;
config.dilation = dilation;
if (inputs[0].dims != 4 && inputs[0].dims != umat_blobs[0].dims)
@@ -2025,7 +2020,7 @@ public:
}
#ifdef HAVE_TENGINE
bool tengine_ret = false; ;
bool tengine_ret = false;
std::vector<Mat> teng_in, teng_out;
inputs_arr.getMatVector(teng_in);
@@ -2050,20 +2045,24 @@ public:
/* tengine_init will run when first time. */
if(NULL == tengine_graph)
{
// pads_begin: 0 - pad_top, 1 - pad_left
// pads_end: 0 - pad_bottom, 1 - pad_right
// pad_h0: pad_top, pad_h1: pad_bottom
// pad_w0: pad_left, pad_w1: pad_right
tengine_graph = tengine_init(name.c_str(), input_, inch, ngroups, in_h, in_w,
output_, out_b, outch, out_h, out_w,
kernel_, kernel_size.size(), kernel.height, kernel.width,
teg_bias, stride.height, stride.width,
pad.height, pad.width, dilation.height, dilation.width,
pads_begin[0], pads_end[0], pads_begin[1], pads_end[1], dilation.height, dilation.width,
weightsMat.step1(), padMode, tengine_graph, nstripes);
/*printf("Init(%s): input=%p(%d %d %d %d ),output=%p(%d %d %d %d ),kernel=%p(%ld %d %d ), bias=%p ,"
"stride(%d %d), pad(%d %d), dilation(%d %d) ,weightsMat=%ld, padMode=%s ,tengine_graph = %p \n",
name.c_str(),input_, inch, ngroups, in_h, in_w,
output_, out_b, outch, out_h, out_w,
kernel_, kernel_size.size(), kernel.height, kernel.width,
teg_bias, stride.height, stride.width,
pad.height, pad.width, dilation.height, dilation.width,
weightsMat.step1(), padMode.c_str() ,tengine_graph);*/
// printf("Init(%s): input=%p(%d %d %d %d ),output=%p(%d %d %d %d ),kernel=%p(%ld %d %d ), bias=%p ,"
// "stride(%d %d), pad(%d %d %d %d), dilation(%d %d) ,weightsMat=%ld, padMode=%s ,tengine_graph = %p \n",
// name.c_str(),input_, inch, ngroups, in_h, in_w,
// output_, out_b, outch, out_h, out_w,
// kernel_, kernel_size.size(), kernel.height, kernel.width,
// teg_bias, stride.height, stride.width,
// pads_begin[0], pads_end[0], pads_begin[1], pads_end[1], dilation.height, dilation.width,
// weightsMat.step1(), padMode.c_str() ,tengine_graph);
}
if(NULL != tengine_graph)
{