def AddInceptionA(img, in_channels, pool_features):
branch1x1 = AddBasicConv(img, (64, in_channels, 1, 1))
branch5x5 = AddBasicConv(img, (48, in_channels, 1, 1))
branch5x5 = AddBasicConv(branch5x5.GetOutTensor(0), (64, 48, 5, 5),
padding=2)
branch3x3dbl = AddBasicConv(img, (64, in_channels, 1, 1))
branch3x3dbl = AddBasicConv(branch3x3dbl.GetOutTensor(0),
(96, 64, 3, 3),
padding=1)
branch3x3dbl = AddBasicConv(branch3x3dbl.GetOutTensor(0),
(96, 96, 3, 3),
padding=1)
branch_pool = nn_ops.Pooling(img, (3, 3), stride=1, pad=1)
branch_pool = AddBasicConv(branch_pool.GetOutTensor(0),
(pool_features, in_channels, 1, 1))
outputs = nn_ops.Concat([
branch1x1.GetOutTensor(0),
branch5x5.GetOutTensor(0),
branch3x3dbl.GetOutTensor(0),
branch_pool.GetOutTensor(0)
], 1)
return outputs
def AddInceptionE(img, in_channels):
branch1x1 = AddBasicConv(img, (320, in_channels, 1, 1))
branch3x3 = AddBasicConv(img, (384, in_channels, 1, 1))
branch3x3_2a = AddBasicConv(branch3x3.GetOutTensor(0),
(384, 384, 1, 3),
padding=(0, 1))
branch3x3_2b = AddBasicConv(branch3x3.GetOutTensor(0),
(384, 384, 3, 1),
padding=(1, 0))
branch3x3 = nn_ops.Concat(
[branch3x3_2a.GetOutTensor(0),
branch3x3_2b.GetOutTensor(0)], 1)
branch3x3dbl = AddBasicConv(img, (448, in_channels, 1, 1))
branch3x3dbl = AddBasicConv(branch3x3dbl.GetOutTensor(0),
(384, 448, 3, 3),
padding=1)
branch3x3dbl_3a = AddBasicConv(branch3x3dbl.GetOutTensor(0),
(384, 384, 1, 3),
padding=(0, 1))
branch3x3dbl_3b = AddBasicConv(branch3x3dbl.GetOutTensor(0),
(384, 384, 3, 1),
padding=(1, 0))
branch3x3dbl = nn_ops.Concat(
[branch3x3dbl_3a.GetOutTensor(0),
branch3x3dbl_3b.GetOutTensor(0)], 1)
branch_pool = nn_ops.Pooling(img, (3, 3), stride=1, pad=1)
branch_pool = AddBasicConv(branch_pool.GetOutTensor(0),
(192, in_channels, 1, 1))
outputs = nn_ops.Concat([
branch1x1.GetOutTensor(0),
branch3x3.GetOutTensor(0),
branch3x3dbl.GetOutTensor(0),
branch_pool.GetOutTensor(0)
], 1)
return outputs
def AddInceptionB(img, in_channels):
branch3x3 = AddBasicConv(img, (384, in_channels, 3, 3), stride=2)
branch3x3dbl = AddBasicConv(img, (64, in_channels, 1, 1))
branch3x3dbl = AddBasicConv(branch3x3dbl.GetOutTensor(0),
(96, 64, 3, 3),
padding=1)
branch3x3dbl = AddBasicConv(branch3x3dbl.GetOutTensor(0),
(96, 96, 3, 3),
stride=2)
branch_pool = nn_ops.Pooling(img, (3, 3), stride=2)
outputs = nn_ops.Concat([
branch3x3.GetOutTensor(0),
branch3x3dbl.GetOutTensor(0),
branch_pool.GetOutTensor(0)
], 1)
return outputs
def AddInceptionD(img, in_channels):
branch3x3 = AddBasicConv(img, (192, in_channels, 1, 1))
branch3x3 = AddBasicConv(branch3x3.GetOutTensor(0), (320, 192, 3, 3),
stride=2)
branch7x7x3 = AddBasicConv(img, (192, in_channels, 1, 1))
branch7x7x3 = AddBasicConv(branch7x7x3.GetOutTensor(0),
(192, 192, 1, 7),
padding=(0, 3))
branch7x7x3 = AddBasicConv(branch7x7x3.GetOutTensor(0),
(192, 192, 7, 1),
padding=(3, 0))
branch7x7x3 = AddBasicConv(branch7x7x3.GetOutTensor(0),
(192, 192, 3, 3),
stride=2)
branch_pool = nn_ops.Pooling(img, (3, 3), stride=2)
outputs = nn_ops.Concat([
branch3x3.GetOutTensor(0),
branch7x7x3.GetOutTensor(0),
branch_pool.GetOutTensor(0)
], 1)
return outputs
def AddInceptionC(img, in_channels, channels_7x7):
branch1x1 = AddBasicConv(img, (192, in_channels, 1, 1))
branch7x7 = AddBasicConv(img, (channels_7x7, in_channels, 1, 1))
branch7x7 = AddBasicConv(branch7x7.GetOutTensor(0),
(channels_7x7, channels_7x7, 1, 7),
padding=(0, 3))
branch7x7 = AddBasicConv(branch7x7.GetOutTensor(0),
(192, channels_7x7, 7, 1),
padding=(3, 0))
branch7x7_dbl = AddBasicConv(img, (channels_7x7, in_channels, 1, 1))
branch7x7_dbl = AddBasicConv(branch7x7_dbl.GetOutTensor(0),
(channels_7x7, channels_7x7, 7, 1),
padding=(3, 0))
branch7x7_dbl = AddBasicConv(branch7x7_dbl.GetOutTensor(0),
(channels_7x7, channels_7x7, 1, 7),
padding=(0, 3))
branch7x7_dbl = AddBasicConv(branch7x7_dbl.GetOutTensor(0),
(channels_7x7, channels_7x7, 7, 1),
padding=(3, 0))
branch7x7_dbl = AddBasicConv(branch7x7_dbl.GetOutTensor(0),
(192, channels_7x7, 1, 7),
padding=(0, 3))
branch_pool = nn_ops.Pooling(img, (3, 3), stride=1, pad=1)
branch_pool = AddBasicConv(branch_pool.GetOutTensor(0),
(192, in_channels, 1, 1))
outputs = nn_ops.Concat([
branch1x1.GetOutTensor(0),
branch7x7.GetOutTensor(0),
branch7x7_dbl.GetOutTensor(0),
branch_pool.GetOutTensor(0)
], 1)
return outputs