def __init__(self, name, in_ch, ch, res_scale_fac, act_type, bn_mom, use_se, shortcut, pool_type):
super(_RiseBlockB, self).__init__(name, ch, res_scale_fac, act_type, bn_mom, use_se, shortcut)
self.body = HybridSequential(prefix="")
self.branches = HybridConcurrent(axis=1, prefix="") # entry point for all branches
ch_0_0 = ch_1_0 = 32
ch_1_1 = ch_1_2 = ch_0_2 = ch_0_1 = 96
ch_2_0 = 192 # Too many local variables (18/15)
with self.name_scope():
# branch 0
self.b_0 = HybridSequential()
self.b_0.add(get_pool(pool_type, pool_size=(2, 2), strides=(2, 2)))
self.b_0.add(Conv2D(channels=ch_0_0, kernel_size=(1, 1), in_channels=in_ch))
self.b_0.add(get_act(act_type))
self.b_0.add(
Conv2D(channels=ch_0_1, kernel_size=(3, 1), padding=(0, 1), in_channels=ch_0_0, use_bias=False)
)
self.b_0.add(
Conv2D(channels=ch_0_2, kernel_size=(1, 3), padding=(1, 0), in_channels=ch_0_1, use_bias=False)
)
self.b_0.add(_UpsampleBlock("upsample0", scale=2))
# branch 1
self.b_1 = HybridSequential()
self.b_1.add(Conv2D(channels=ch_1_0, kernel_size=(1, 1), in_channels=in_ch))
self.b_1.add(get_act(act_type))
self.b_1.add(
Conv2D(channels=ch_1_1, kernel_size=(3, 1), padding=(0, 1), in_channels=ch_1_0, use_bias=False)
)
self.b_1.add(
Conv2D(channels=ch_1_2, kernel_size=(1, 3), padding=(1, 0), in_channels=ch_1_1, use_bias=False)
)
# branch 2
self.b_2 = HybridSequential()
self.b_2.add(Conv2D(channels=ch_2_0, kernel_size=(1, 1), in_channels=in_ch, use_bias=False))
# concatenate all branches and add them to the body
self.branches.add(self.b_0)
self.branches.add(self.b_1)
self.branches.add(self.b_2)
self.body.add(self.branches)
def __init__(self, name, in_ch, ch, res_scale_fac, act_type, bn_mom,
use_se, shortcut, pool_type):
"""
IN 8x8: 256 TOTAL
BRANCH 0
b_0 b_0 b_0_0
-> 24 Conv 1x1 -> POOL2D 2x2 -> 32 Conv 3x3
-> 24-> 32
BRANCH 1
b_0 b_0 b_0_0
-> 24 Conv 1x1 -> POOL2D 4x4 -> 32 Conv 2x2
-> 24-> 32
BRANCH 2
-> 24 Conv 1x1 -> 32 Conv 3x3
-> 24 -> 32
BRANCH 3
-> 24 Conv 1x1 -> 24 Conv 3x1
-> 24 Conv 1x3
-> 24 -> 48
BRANCH 4
-> 24 Conv 1x1 -> 24 Conv 5x1
-> 24 Conv 1x5
-> 24 -> 48
BRANCH 5
-> 24 Conv 1x1 -> 24 Conv 3x1 -> 32 Conv 1x3
-> 24 Conv 1x3 -> 32 Conv 3x1
-> 24 -> 64
"""
super(_RiseBlockA, self).__init__(name, ch, res_scale_fac, act_type,
bn_mom, use_se, shortcut)
self.body = HybridSequential(prefix="")
# entry point for all branches
self.branches = HybridConcurrent(axis=1, prefix="")
ch_0_0 = 42
ch_0_1 = 64
ch_1_0 = 32
ch_1_1 = 32
ch_2_0 = 64
ch_2_1 = 96
ch_2_2 = 128
with self.name_scope():
# branch 0
self.b_0 = HybridSequential()
self.b_0.add(get_pool(pool_type, pool_size=(2, 2), strides=(2, 2)))
self.b_0.add(
Conv2D(channels=ch_0_0, kernel_size=(1, 1), in_channels=in_ch))
self.b_0.add(get_act(act_type))
self.b_0.add(
Conv2D(channels=ch_0_1,
kernel_size=(3, 3),
padding=(1, 1),
in_channels=ch_0_0,
use_bias=True))
self.b_0.add(get_act(act_type))
self.b_0.add(_UpsampleBlock("upsample0", scale=2))
# branch 1
self.b_1 = HybridSequential()
self.b_1.add(get_pool(pool_type, pool_size=(4, 4), strides=(4, 4)))
self.b_1.add(
Conv2D(channels=ch_1_0,
kernel_size=(1, 1),
in_channels=in_ch,
use_bias=True))
self.b_1.add(get_act(act_type))
self.b_1.add(
Conv2D(channels=ch_1_1,
kernel_size=(3, 3),
padding=(1, 1),
in_channels=ch_1_0,
use_bias=True))
self.b_1.add(get_act(act_type))
self.b_1.add(_UpsampleBlock("upsample0", scale=4))
# branch 1
# self.b_1 = HybridSequential()
# self.b_1.add(Conv2D(channels=ch_1_0, kernel_size=(1, 1), in_channels=in_ch, use_bias=False))
# self.b_1.add(get_act(act_type))
# branch 2
self.b_2 = HybridSequential()
self.b_2.add(
Conv2D(channels=ch_2_0, kernel_size=(1, 1), in_channels=in_ch))
self.b_2.add(get_act(act_type))
self.b_2.add(
Conv2D(channels=ch_2_1,
kernel_size=(3, 3),
padding=(1, 1),
in_channels=ch_2_0,
use_bias=True))
self.b_2.add(get_act(act_type))
self.b_2.add(
Conv2D(channels=ch_2_2,
kernel_size=(3, 3),
padding=(1, 1),
in_channels=ch_2_1,
use_bias=True))
self.b_2.add(get_act(act_type))
# concatenate all branches and add them to the body
self.branches.add(self.b_0)
self.branches.add(self.b_1)
self.branches.add(self.b_2)
# self.branches.add(self.b_3)
# self.branches.add(self.b_4)
self.body.add(self.branches)
self.body.add(
Conv2D(
channels=ch,
kernel_size=(1, 1),
prefix="%s_conv0" % name,
in_channels=ch_0_1 + ch_1_1 + ch_2_2,
use_bias=False,
)) # +ch_3_2+ch_4_2