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implement ncnn fold and unfold (#4326)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,124 @@ | ||
| // Tencent is pleased to support the open source community by making ncnn available. | ||
| // | ||
| // Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved. | ||
| // | ||
| // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | ||
| // in compliance with the License. You may obtain a copy of the License at | ||
| // | ||
| // https://opensource.org/licenses/BSD-3-Clause | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software distributed | ||
| // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR | ||
| // CONDITIONS OF ANY KIND, either express or implied. See the License for the | ||
| // specific language governing permissions and limitations under the License. | ||
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| #include "fold.h" | ||
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| namespace ncnn { | ||
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| Fold::Fold() | ||
| { | ||
| one_blob_only = true; | ||
| } | ||
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| int Fold::load_param(const ParamDict& pd) | ||
| { | ||
| kernel_w = pd.get(1, 0); | ||
| kernel_h = pd.get(11, kernel_w); | ||
| dilation_w = pd.get(2, 1); | ||
| dilation_h = pd.get(12, dilation_w); | ||
| stride_w = pd.get(3, 1); | ||
| stride_h = pd.get(13, stride_w); | ||
| pad_left = pd.get(4, 0); | ||
| pad_right = pd.get(15, pad_left); | ||
| pad_top = pd.get(14, pad_left); | ||
| pad_bottom = pd.get(16, pad_top); | ||
| output_w = pd.get(20, 0); | ||
| output_h = pd.get(21, output_w); | ||
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| return 0; | ||
| } | ||
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| int Fold::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const | ||
| { | ||
| const int size = bottom_blob.w; | ||
| const int max_channels = bottom_blob.h; | ||
| size_t elemsize = bottom_blob.elemsize; | ||
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| const int kernel_extent_w = dilation_w * (kernel_w - 1) + 1; | ||
| const int kernel_extent_h = dilation_h * (kernel_h - 1) + 1; | ||
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| const int outw = output_w + pad_left + pad_right; | ||
| const int outh = output_h + pad_top + pad_bottom; | ||
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| const int inw = (outw - kernel_extent_w) / stride_w + 1; | ||
| const int inh = (outh - kernel_extent_h) / stride_h + 1; | ||
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| // assert inw * inh == size | ||
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| const int maxk = kernel_w * kernel_h; | ||
| const int channels = max_channels / maxk; | ||
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| Mat top_blob_bordered; | ||
| if (pad_left > 0 || pad_right > 0 || pad_top > 0 || pad_bottom > 0) | ||
| { | ||
| top_blob_bordered.create(outw, outh, channels, elemsize, opt.workspace_allocator); | ||
| } | ||
| else | ||
| { | ||
| top_blob_bordered = top_blob; | ||
| top_blob_bordered.create(outw, outh, channels, elemsize, opt.blob_allocator); | ||
| } | ||
| if (top_blob_bordered.empty()) | ||
| return -100; | ||
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| // col2im | ||
| const int gap = outw * stride_h - inw * stride_w; | ||
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| #pragma omp parallel for num_threads(opt.num_threads) | ||
| for (int p = 0; p < channels; p++) | ||
| { | ||
| const float* sptr = bottom_blob.row(p * maxk); | ||
| Mat outm = top_blob_bordered.channel(p); | ||
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| outm.fill(0.f); | ||
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| for (int u = 0; u < kernel_h; u++) | ||
| { | ||
| for (int v = 0; v < kernel_w; v++) | ||
| { | ||
| float* ptr = outm.row(dilation_h * u) + dilation_w * v; | ||
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| for (int i = 0; i < inh; i++) | ||
| { | ||
| for (int j = 0; j < inw; j++) | ||
| { | ||
| ptr[0] += sptr[0]; | ||
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| ptr += stride_w; | ||
| sptr += 1; | ||
| } | ||
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| ptr += gap; | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| if (pad_left > 0 || pad_right > 0 || pad_top > 0 || pad_bottom > 0) | ||
| { | ||
| Option opt_b = opt; | ||
| opt_b.use_packing_layout = false; | ||
| copy_cut_border(top_blob_bordered, top_blob, pad_top, pad_bottom, pad_left, pad_right, opt_b); | ||
| if (top_blob.empty()) | ||
| return -100; | ||
| } | ||
| else | ||
| { | ||
| top_blob = top_blob_bordered; | ||
| } | ||
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| return 0; | ||
| } | ||
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| } // namespace ncnn |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,48 @@ | ||
| // Tencent is pleased to support the open source community by making ncnn available. | ||
| // | ||
| // Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved. | ||
| // | ||
| // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | ||
| // in compliance with the License. You may obtain a copy of the License at | ||
| // | ||
| // https://opensource.org/licenses/BSD-3-Clause | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software distributed | ||
| // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR | ||
| // CONDITIONS OF ANY KIND, either express or implied. See the License for the | ||
| // specific language governing permissions and limitations under the License. | ||
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| #ifndef LAYER_FOLD_H | ||
| #define LAYER_FOLD_H | ||
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| #include "layer.h" | ||
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| namespace ncnn { | ||
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| class Fold : public Layer | ||
| { | ||
| public: | ||
| Fold(); | ||
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| virtual int load_param(const ParamDict& pd); | ||
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| virtual int forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const; | ||
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| public: | ||
| int kernel_w; | ||
| int kernel_h; | ||
| int dilation_w; | ||
| int dilation_h; | ||
| int stride_w; | ||
| int stride_h; | ||
| int pad_left; // -233=SAME_UPPER -234=SAME_LOWER | ||
| int pad_right; | ||
| int pad_top; | ||
| int pad_bottom; | ||
| int output_w; | ||
| int output_h; | ||
| }; | ||
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| } // namespace ncnn | ||
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| #endif // LAYER_FOLD_H |
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