implement fold and unfold

.ci/linux-x64-cpu-gcc.yml

@@ -49,6 +49,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: install-deps
@@ -85,6 +87,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: build-nostdio

.ci/pnnx.yml

@@ -52,6 +52,7 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
         enableGitLfs: false
 
     - name: install-deps

.ci/test-coverage.yml

@@ -32,6 +32,7 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
         enableGitLfs: false
 
     - name: install-deps
@@ -105,6 +106,7 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
         enableGitLfs: false
 
     - name: install-deps
@@ -195,6 +197,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: install-deps
@@ -248,6 +252,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: install-deps
@@ -351,6 +357,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: install-deps
@@ -435,6 +443,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: install-deps
@@ -512,6 +522,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: install-deps
@@ -589,6 +601,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: install-deps
@@ -668,6 +682,8 @@ jobs:
     - name: checkout
       checkout: self
       with:
+        strategy: FRESH_CHECKOUT
+        enableSubmodule: false
         enableGitLfs: false
 
     - name: install-deps

src/CMakeLists.txt

@@ -157,6 +157,8 @@ ncnn_add_layer(DeconvolutionDepthWise3D)
 ncnn_add_layer(Einsum)
 ncnn_add_layer(DeformableConv2D)
 ncnn_add_layer(GLU)
+ncnn_add_layer(Fold)
+ncnn_add_layer(Unfold)
 
 if(NCNN_VULKAN)
     ncnn_add_shader(${CMAKE_CURRENT_SOURCE_DIR}/convert_ycbcr.comp)

src/layer/fold.cpp

@@ -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.
+
+#include "fold.h"
+
+namespace ncnn {
+
+Fold::Fold()
+{
+    one_blob_only = true;
+}
+
+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);
+
+    return 0;
+}
+
+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;
+
+    const int kernel_extent_w = dilation_w * (kernel_w - 1) + 1;
+    const int kernel_extent_h = dilation_h * (kernel_h - 1) + 1;
+
+    const int outw = output_w + pad_left + pad_right;
+    const int outh = output_h + pad_top + pad_bottom;
+
+    const int inw = (outw - kernel_extent_w) / stride_w + 1;
+    const int inh = (outh - kernel_extent_h) / stride_h + 1;
+
+    // assert inw * inh == size
+
+    const int maxk = kernel_w * kernel_h;
+    const int channels = max_channels / maxk;
+
+    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;
+
+    // col2im
+    const int gap = outw * stride_h - inw * stride_w;
+
+    #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);
+
+        outm.fill(0.f);
+
+        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;
+
+                for (int i = 0; i < inh; i++)
+                {
+                    for (int j = 0; j < inw; j++)
+                    {
+                        ptr[0] += sptr[0];
+
+                        ptr += stride_w;
+                        sptr += 1;
+                    }
+
+                    ptr += gap;
+                }
+            }
+        }
+    }
+
+    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;
+    }
+
+    return 0;
+}
+
+} // namespace ncnn

src/layer/fold.h

@@ -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.
+
+#ifndef LAYER_FOLD_H
+#define LAYER_FOLD_H
+
+#include "layer.h"
+
+namespace ncnn {
+
+class Fold : public Layer
+{
+public:
+    Fold();
+
+    virtual int load_param(const ParamDict& pd);
+
+    virtual int forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const;
+
+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;
+};
+
+} // namespace ncnn
+
+#endif // LAYER_FOLD_H