commit 7dc18207d86299cf605a2316e86dc9c098708729
author Keith Mok <ek9852@gmail.com> Sun Dec 20 13:45:51 2020 -0800
committer mike.kelly <mike.kelly@arm.com> Thu Jan 07 12:00:08 2021 +0000
tree 09cf0a95baf6da860f2829fdea110f113c3ff44c
parent 1b4e5d35eb5c51a4b4b2838b1098847ba3c717dc

Add Caffe Parser Dilation support

Signed-off-by: Keith Mok <ek9852@gmail.com>
Change-Id: I3a85de2d082d489fbf5a775c2ae551080d189294

src/armnnCaffeParser/CaffeParser.cpp

diff --git a/src/armnnCaffeParser/CaffeParser.cpp b/src/armnnCaffeParser/CaffeParser.cpp
index d11da46..51b58cc 100644
--- a/src/armnnCaffeParser/CaffeParser.cpp
+++ b/src/armnnCaffeParser/CaffeParser.cpp
@@ -479,12 +479,12 @@
     outputShape.add_dim(2);
     outputShape.set_dim(
         2, (static_cast<int>(
-                static_cast<float>(inputShape.dim(2) + 2 * desc.m_PadBottom - kernelH) /
+                static_cast<float>(inputShape.dim(2) + 2 * desc.m_PadBottom - (desc.m_DilationX * (kernelH - 1) + 1)) /
                 static_cast<float>(desc.m_StrideY)) + 1));
     outputShape.add_dim(3);
     outputShape.set_dim(
         3, (static_cast<int>(
-                static_cast<float>(inputShape.dim(3) + 2 * desc.m_PadRight - kernelW) /
+                static_cast<float>(inputShape.dim(3) + 2 * desc.m_PadRight - (desc.m_DilationY * (kernelW - 1)  + 1)) /
                 static_cast<float>(desc.m_StrideX)) + 1));
 
     // Load the weight data for ALL groups
@@ -609,6 +609,8 @@
     desc.m_PadBottom    = convDesc.m_PadBottom;
     desc.m_StrideX      = convDesc.m_StrideX;
     desc.m_StrideY      = convDesc.m_StrideY;
+    desc.m_DilationX    = convDesc.m_DilationX;
+    desc.m_DilationY    = convDesc.m_DilationY;
     desc.m_BiasEnabled  = convDesc.m_BiasEnabled;
 
     unsigned int numFilters = convParam.num_output();
@@ -621,12 +623,12 @@
     outputShape.add_dim(2);
     outputShape.set_dim(
         2, (static_cast<int>(
-                static_cast<float>(inputShape.dim(2) + 2 * desc.m_PadBottom - kernelH) /
+                static_cast<float>(inputShape.dim(2) + 2 * desc.m_PadBottom - (desc.m_DilationX * (kernelH - 1) + 1)) /
                 static_cast<float>(desc.m_StrideY)) + 1));
     outputShape.add_dim(3);
     outputShape.set_dim(
         3, (static_cast<int>(
-                static_cast<float>(inputShape.dim(3) + 2 * desc.m_PadRight - kernelW) /
+                static_cast<float>(inputShape.dim(3) + 2 * desc.m_PadRight - (desc.m_DilationY * (kernelW - 1) + 1)) /
                 static_cast<float>(desc.m_StrideX)) + 1));
 
     // Load the weight data
@@ -682,7 +684,6 @@
 void CaffeParserBase::ParseConvLayer(const LayerParameter& layerParam)
 {
     // Ignored Caffe Parameters
-    // * Dilation Size
     // * Weight Filler
     // * Bias Filler
     // * Engine
@@ -717,6 +718,10 @@
     unsigned int padW = GET_OPTIONAL_WITH_VECTOR_FALLBACK(convParam, ConvolutionParameter,
                                                           pad_w, pad, unsigned int, 0u);
 
+    unsigned int dilationH = convParam.dilation_size() > 0 ? convParam.dilation(0) : 1;
+    unsigned int dilationW = convParam.dilation_size() > 1 ? convParam.dilation(1) :
+        convParam.dilation_size() > 0 ? convParam.dilation(0) : 1;
+
     Convolution2dDescriptor convolution2dDescriptor;
     convolution2dDescriptor.m_PadLeft     = padW;
     convolution2dDescriptor.m_PadRight    = padW;
@@ -724,6 +729,8 @@
     convolution2dDescriptor.m_PadBottom   = padH;
     convolution2dDescriptor.m_StrideX     = strideW;
     convolution2dDescriptor.m_StrideY     = strideH;
+    convolution2dDescriptor.m_DilationX   = dilationW;
+    convolution2dDescriptor.m_DilationY   = dilationH;
     convolution2dDescriptor.m_BiasEnabled = convParam.has_bias_term() ? convParam.bias_term() : true;
 
     if (numGroups > numFilters)
@@ -789,12 +796,12 @@
     outputShape.add_dim(2);
     outputShape.set_dim(
         2, (static_cast<int>(
-                static_cast<float>(inputShape.dim(2) + 2 * padH - kernelH) /
+                static_cast<float>(inputShape.dim(2) + 2 * padH - (dilationH * (kernelH - 1) + 1)) /
                 static_cast<float>(strideH)) + 1));
     outputShape.add_dim(3);
     outputShape.set_dim(
         3, (static_cast<int>(
-                static_cast<float>(inputShape.dim(3) + 2 * padW - kernelW) /
+                static_cast<float>(inputShape.dim(3) + 2 * padW - (dilationW * (kernelW - 1) + 1)) /
                 static_cast<float>(strideW)) + 1));
 
     // Load the weight data for ALL groups