From 13638ab03003483252b8798a31da4177ed9c6cc9 Mon Sep 17 00:00:00 2001
From: Yury Adamov <yury.adamov@promwad.com>
Date: Sat, 6 Oct 2018 01:20:34 +0300
Subject: [PATCH] Added SpatialDilatedConvolution handling
---
convert_torch.py | 9 +++++++++
1 file changed, 9 insertions(+)
diff --git a/convert_torch.py b/convert_torch.py
index b639f73..479ce2f 100644
--- a/convert_torch.py
+++ b/convert_torch.py
@@ -149,6 +149,11 @@ def lua_recursive_model(module,seq):
n = LambdaReduce(lambda x,y,dim=dim: torch.cat((x,y),dim))
lua_recursive_model(m,n)
add_submodule(seq,n)
+ elif name == 'SpatialDilatedConvolution':
+ if not hasattr(m,'groups') or m.groups is None: m.groups=1
+ n = nn.Conv2d(m.nInputPlane,m.nOutputPlane,(m.kW,m.kH),(m.dW,m.dH),(m.padW,m.padH),(m.dilationW,m.dilationH),m.groups,bias=(m.bias is not None))
+ copy_param(m,n)
+ add_submodule(seq,n)
elif name == 'TorchObject':
print('Not Implement',name,real._typename)
else:
@@ -168,6 +173,10 @@ def lua_recursive_source(module):
if not hasattr(m,'groups') or m.groups is None: m.groups=1
s += ['nn.Conv2d({},{},{},{},{},{},{},bias={}),#Conv2d'.format(m.nInputPlane,
m.nOutputPlane,(m.kW,m.kH),(m.dW,m.dH),(m.padW,m.padH),1,m.groups,m.bias is not None)]
+ elif name == 'SpatialDilatedConvolution':
+ if not hasattr(m,'groups') or m.groups is None: m.groups=1
+ s += ['nn.Conv2d({},{},{},{},{},{},{},bias={}),#Conv2d'.format(m.nInputPlane,
+ m.nOutputPlane,(m.kW,m.kH),(m.dW,m.dH),(m.padW,m.padH),(m.dilationW,m.dilationH),m.groups,m.bias is not None)]
elif name == 'SpatialBatchNormalization':
s += ['nn.BatchNorm2d({},{},{},{}),#BatchNorm2d'.format(m.running_mean.size(0), m.eps, m.momentum, m.affine)]
elif name == 'VolumetricBatchNormalization':