add Sigmoid, Volumetric{FullConvolution, BatchNormalization}

Author: mschrimpf

convert_torch.py

@@ -65,9 +65,16 @@ def lua_recursive_model(module,seq):
             n = nn.BatchNorm2d(m.running_mean.size(0), m.eps, m.momentum, m.affine)
             copy_param(m,n)
             add_submodule(seq,n)
+        elif name == 'VolumetricBatchNormalization':
+            n = nn.BatchNorm3d(m.running_mean.size(0), m.eps, m.momentum, m.affine)
+            copy_param(m, n)
+            add_submodule(seq, n)
         elif name == 'ReLU':
             n = nn.ReLU()
             add_submodule(seq,n)
+        elif name == 'Sigmoid':
+            n = nn.Sigmoid()
+            add_submodule(seq,n)
         elif name == 'SpatialMaxPooling':
             n = nn.MaxPool2d((m.kW,m.kH),(m.dW,m.dH),(m.padW,m.padH),ceil_mode=m.ceil_mode)
             add_submodule(seq,n)
@@ -103,6 +110,9 @@ def lua_recursive_model(module,seq):
         elif name == 'SpatialFullConvolution':
             n = nn.ConvTranspose2d(m.nInputPlane,m.nOutputPlane,(m.kW,m.kH),(m.dW,m.dH),(m.padW,m.padH))
             add_submodule(seq,n)
+        elif name == 'VolumetricFullConvolution':
+            n = nn.ConvTranspose3d(m.nInputPlane,m.nOutputPlane,(m.kT,m.kW,m.kH),(m.dT,m.dW,m.dH),(m.padT,m.padW,m.padH))
+            add_submodule(seq, n)
         elif name == 'SpatialReplicationPadding':
             n = nn.ReplicationPad2d((m.pad_l,m.pad_r,m.pad_t,m.pad_b))
             add_submodule(seq,n)
@@ -156,8 +166,12 @@ def lua_recursive_source(module):
                 m.nOutputPlane,(m.kW,m.kH),(m.dW,m.dH),(m.padW,m.padH),1,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':
+            s += ['nn.BatchNorm3d({},{},{},{}),#BatchNorm3d'.format(m.running_mean.size(0), m.eps, m.momentum, m.affine)]
         elif name == 'ReLU':
             s += ['nn.ReLU()']
+        elif name == 'Sigmoid':
+            s += ['nn.Sigmoid()']
         elif name == 'SpatialMaxPooling':
             s += ['nn.MaxPool2d({},{},{},ceil_mode={}),#MaxPool2d'.format((m.kW,m.kH),(m.dW,m.dH),(m.padW,m.padH),m.ceil_mode)]
         elif name == 'SpatialAveragePooling':
@@ -181,6 +195,9 @@ def lua_recursive_source(module):
         elif name == 'SpatialFullConvolution':
             s += ['nn.ConvTranspose2d({},{},{},{},{})'.format(m.nInputPlane,
                 m.nOutputPlane,(m.kW,m.kH),(m.dW,m.dH),(m.padW,m.padH))]
+        elif name == 'VolumetricFullConvolution':
+            s += ['nn.ConvTranspose3d({},{},{},{},{})'.format(m.nInputPlane,
+                m.nOutputPlane,(m.kT,m.kW,m.kH),(m.dT,m.dW,m.dH),(m.padT,m.padW,m.padH))]
         elif name == 'SpatialReplicationPadding':
             s += ['nn.ReplicationPad2d({})'.format((m.pad_l,m.pad_r,m.pad_t,m.pad_b))]
         elif name == 'SpatialReflectionPadding':