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tune for opencl

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This commit is contained in:
fengyuentau
2022-08-14 17:47:48 +08:00
parent e7e814fa8c
commit 0cdff46725
3 changed files with 13 additions and 12 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+4 -1
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@@ -1807,7 +1807,10 @@ 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)
modules/dnn/src/ocl4dnn/include/ocl4dnn.hpp
+4 -3
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@@ -55,17 +55,18 @@ struct OCL4DNNConvConfig
{
OCL4DNNConvConfig() :
kernel(1, 1),
pad(0, 0),
stride(1, 1),
dilation(1, 1),
group(1),
bias_term(false),
use_half(false)
{}
{
pads = {0, 0, 0, 0};
}
MatShape in_shape;
MatShape out_shape;
Size kernel;
Size pad;
std::vector<int> pads; // [pad_top, pad_bottom, pad_left, pad_right]
Size stride;
Size dilation;
int group; // = 1;
modules/dnn/src/ocl4dnn/src/ocl4dnn_conv_spatial.cpp
+5 -8
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@@ -181,8 +181,11 @@ OCL4DNNConvSpatial<Dtype>::OCL4DNNConvSpatial(OCL4DNNConvConfig config)
// assumption: spatial dimension is 2.
kernel_h_ = config.kernel.height;
kernel_w_ = config.kernel.width;
pad_h_ = config.pad.height;
pad_w_ = config.pad.width;
// pads: [pad_top, pad_bottom, pad_left, pad_right]
pad_h_ = config.pads[0]; // pad_top
pad_bottom_ = config.pads[1];
pad_w_ = config.pads[2]; // pad_left
pad_right_ = config.pads[3];
stride_h_ = config.stride.height;
stride_w_ = config.stride.width;
dilation_h_ = config.dilation.height;
@@ -194,12 +197,6 @@ OCL4DNNConvSpatial<Dtype>::OCL4DNNConvSpatial(OCL4DNNConvConfig config)
output_w_ = config.out_shape[dims - spatial_dims + 1];
bottom_dim_ = channels_ * width_ * height_;
top_dim_ = num_output_ * output_w_ * output_h_;
int Ph = (output_h_ - 1) * stride_h_ + (dilation_h_ * (kernel_h_ - 1) + 1) - height_;
int Pw = (output_w_ - 1) * stride_w_ + (dilation_w_ * (kernel_w_ - 1) + 1) - width_;
Ph = (Ph > 0) ? Ph : 0;
Pw = (Pw > 0) ? Pw : 0;
pad_right_ = (Pw + 1) / 2;
pad_bottom_ = (Ph + 1) / 2;
cache_path_ = utils::getConfigurationParameterString("OPENCV_OCL4DNN_CONFIG_PATH", "");
dwconv_ = (num_output_ == channels_ && channels_ == group_);