def model_core_squeezenet12(x, mode, params, info):
y, info = layer.conv2d_batch_norm_relu_dropout_l(x, mode, params, info, filters=32, kernel_size=6, strides=2) # output 128x128
y, info = layer.maxpool_l(y, info) # output 64x64
y, info = layer.sqnet_squeeze(y, mode, params, info, 21)
y, info = layer.sqnet_expand(y, mode, params, info, 2*26)
y, info = layer.sqnet_squeeze(y, mode, params, info, 36)
y, info = layer.sqnet_expand(y, mode, params, info, 2*46)
y, info = layer.maxpool_l(y, info) # output 32x32
y, info = layer.sqnet_squeeze(y, mode, params, info, 41)
y, info = layer.sqnet_expand(y, mode, params, info, 2*36)
y, info = layer.sqnet_squeeze(y, mode, params, info, 31)
y, info = layer.sqnet_expand(y, mode, params, info, 2*26)
y, info = layer.maxpool_l(y, info) # output 16x16
y, info = layer.sqnet_squeeze(y, mode, params, info, 21)
y, info = layer.sqnet_expand(y, mode, params, info, 2*16, last=True)
return y, info
def sqnet_squeeze_expand(x, mode, params, info, depth_increment, last=False):
"""Squeezenet "fire" module, i.e. a "squeeze" module followed by an "expand" module."""
depth = int(x.get_shape()[3])//2
depth += depth_increment
x, info = layer.sqnet_squeeze(x, mode, params, info, depth)
depth += depth_increment
x, info = layer.sqnet_expand(x, mode, params, info, 2*depth, last=last)
return x, info
def model_core_squeezenet17(x, mode, params, info):
y, info = layer.conv2d_batch_norm_relu_dropout_l(x, mode, params, info, filters=128, kernel_size=3, strides=1)
y, info = layer.sqnet_expand(y, mode, params, info, 2*64)
y, info = layer.maxpool_l(y, info) # output 128x128
#y, info = layer.sqnet_squeeze_pool(y, mode, params, info, 80)
y, info = layer.sqnet_squeeze(y, mode, params, info, 80)
y, info = layer.sqnet_expand(y, mode, params, info, 2*96)
y, info = layer.maxpool_l(y, info) # output 64x64
#y, info = layer.sqnet_squeeze_pool(y, mode, params, info, 104)
y, info = layer.sqnet_squeeze(y, mode, params, info, 104)
y, info = layer.sqnet_expand(y, mode, params, info, 2*112)
y, info = layer.sqnet_squeeze(y, mode, params, info, 120)
y, info = layer.sqnet_expand(y, mode, params, info, 2*128)
y, info = layer.maxpool_l(y, info) # output 32x32
#y, info = layer.sqnet_squeeze_pool(y, mode, params, info, 120)
y, info = layer.sqnet_squeeze(y, mode, params, info, 120)
y, info = layer.sqnet_expand(y, mode, params, info, 2*112)
y, info = layer.sqnet_squeeze(y, mode, params, info, 104)
y, info = layer.sqnet_expand(y, mode, params, info, 2*96)
y, info = layer.maxpool_l(y, info) # output 16x16
#y, info = layer.sqnet_squeeze_pool(y, mode, params, info, 88)
y, info = layer.sqnet_squeeze(y, mode, params, info, 88)
y, info = layer.sqnet_expand(y, mode, params, info, 2*80)
y, info = layer.sqnet_squeeze(y, mode, params, info, 72)
y, info = layer.sqnet_expand(y, mode, params, info, 2*65, last=True)
return y, info