def stem(x):
"""
Stem fo the pure InceptionV4 and Inception-ResNet-V2
"""
out = conv3x3(x, 32, stride=2, padding="VALID", batch_norm=use_batch_norm)
out = conv3x3(out, 32, stride=1, padding="VALID", batch_norm=use_batch_norm)
out = conv3x3(out, 64, stride=1, padding="SAME", batch_norm=use_batch_norm)
out1 = max_pool_3x3(out, stride=2, padding="VALID")
out2 = conv3x3(out, 96, stride=2, padding="VALID", batch_norm=use_batch_norm)
out = concat(3, [out1, out2])
out1 = conv1x1(out, 64, batch_norm=use_batch_norm)
out1 = conv3x3(out1, 96, padding="VALID", batch_norm=use_batch_norm)
out2 = conv1x1(out, 64, batch_norm=use_batch_norm)
out2 = conv1x7(out2, 64, batch_norm=use_batch_norm)
out2 = conv7x1(out2, 64, batch_norm=use_batch_norm)
out2 = conv3x3(out2, 96, padding="VALID", batch_norm=use_batch_norm)
out = concat(3, [out1, out2])
out1 = conv3x3(out, 192, stride=2, padding="VALID", batch_norm=use_batch_norm)
out2 = max_pool_3x3(out, stride=2, padding="VALID")
out = concat(3, [out1, out2])
return out
def inceptionB(out):
out1 = conv1x1(out, 384, batch_norm=use_batch_norm)
out2 = conv1x1(out, 192, batch_norm=use_batch_norm)
out2 = conv1x7(out2, 224, batch_norm=use_batch_norm)
out2 = conv7x1(out2, 256, batch_norm=use_batch_norm)
out3 = conv1x1(out, 192, batch_norm=use_batch_norm)
out3 = conv7x1(out3, 192, batch_norm=use_batch_norm)
out3 = conv1x7(out3, 224, batch_norm=use_batch_norm)
out3 = conv7x1(out3, 224, batch_norm=use_batch_norm)
out3 = conv1x7(out3, 256, batch_norm=use_batch_norm)
out4 = avg_pool_3x3(out)
out4 = conv1x1(out4, 128, batch_norm=use_batch_norm)
return concat(3, [out1, out2, out3, out4])
def inception7C(out, num_1x1, num_d7_red, num_d7_1, num_d7_2, num_q7_red, num_q7_1, num_q7_2, num_q7_3, num_q7_4, proj):
out1 = conv1x1(out, num_1x1, batch_norm=use_batch_norm)
out2 = conv1x1(out, num_d7_red, batch_norm=use_batch_norm)
out2 = conv1x7(out2, num_d7_1, batch_norm=use_batch_norm)
out2 = conv7x1(out2, num_d7_2, batch_norm=use_batch_norm)
out3 = conv1x1(out, num_q7_red, batch_norm=use_batch_norm)
out3 = conv7x1(out3, num_q7_1, batch_norm=use_batch_norm)
out3 = conv1x7(out3, num_q7_2, batch_norm=use_batch_norm)
out3 = conv7x1(out3, num_q7_3, batch_norm=use_batch_norm)
out3 = conv1x7(out3, num_q7_4, batch_norm=use_batch_norm)
out4 = avg_pool_3x3(out)
out4 = conv1x1(out4, proj, batch_norm=use_batch_norm)
return concat(3, [out1, out2, out3, out4])
def inceptionB(out):
out1 = conv1x1(out, 384, batch_norm=use_batch_norm)
out2 = conv1x1(out, 192, batch_norm=use_batch_norm)
out2 = conv1x7(out2, 224, batch_norm=use_batch_norm)
out2 = conv7x1(out2, 256, batch_norm=use_batch_norm)
out3 = conv1x1(out, 192, batch_norm=use_batch_norm)
out3 = conv7x1(out3, 192, batch_norm=use_batch_norm)
out3 = conv1x7(out3, 224, batch_norm=use_batch_norm)
out3 = conv7x1(out3, 224, batch_norm=use_batch_norm)
out3 = conv1x7(out3, 256, batch_norm=use_batch_norm)
out4 = avg_pool_3x3(out)
out4 = conv1x1(out4, 128, batch_norm=use_batch_norm)
return concat(3, [out1, out2, out3, out4])
def inception7C(out, num_1x1, num_d7_red, num_d7_1, num_d7_2, num_q7_red,
num_q7_1, num_q7_2, num_q7_3, num_q7_4, proj):
out1 = conv1x1(out, num_1x1, batch_norm=use_batch_norm)
out2 = conv1x1(out, num_d7_red, batch_norm=use_batch_norm)
out2 = conv1x7(out2, num_d7_1, batch_norm=use_batch_norm)
out2 = conv7x1(out2, num_d7_2, batch_norm=use_batch_norm)
out3 = conv1x1(out, num_q7_red, batch_norm=use_batch_norm)
out3 = conv7x1(out3, num_q7_1, batch_norm=use_batch_norm)
out3 = conv1x7(out3, num_q7_2, batch_norm=use_batch_norm)
out3 = conv7x1(out3, num_q7_3, batch_norm=use_batch_norm)
out3 = conv1x7(out3, num_q7_4, batch_norm=use_batch_norm)
out4 = avg_pool_3x3(out)
out4 = conv1x1(out4, proj, batch_norm=use_batch_norm)
return concat(3, [out1, out2, out3, out4])
def inception7D(out, num_3x3_red, num_3x3, num_d7_3x3_red, num_d7_1, num_d7_2, num_d7_3x3):
out1 = conv1x1(out, num_3x3_red, batch_norm=use_batch_norm)
out1 = conv3x3(out1, num_3x3, stride=2, batch_norm=use_batch_norm)
out2 = conv1x1(out, num_d7_3x3_red, batch_norm=use_batch_norm)
out2 = conv1x7(out2, num_d7_1, batch_norm=use_batch_norm)
out2 = conv7x1(out2, num_d7_2, batch_norm=use_batch_norm)
out2 = conv3x3(out2, num_d7_3x3, stride=2, batch_norm=use_batch_norm)
out3 = max_pool_3x3(out, stride=2)
return concat(3, [out1, out2, out3])
def reductionB(out):
out1 = conv1x1(out, 192, batch_norm=use_batch_norm)
out1 = conv3x3(out1, 192, stride=2, padding="VALID", batch_norm=use_batch_norm)
out2 = conv1x1(out, 256, batch_norm=use_batch_norm)
out2 = conv1x7(out2, 256, batch_norm=use_batch_norm)
out2 = conv7x1(out2, 320, batch_norm=use_batch_norm)
out2 = conv3x3(out2, 320, stride=2, padding="VALID", batch_norm=use_batch_norm)
out3 = max_pool_3x3(out, stride=2, padding="VALID")
return concat(3, [out1, out2, out3])
def inception7D(out, num_3x3_red, num_3x3, num_d7_3x3_red, num_d7_1, num_d7_2,
num_d7_3x3):
out1 = conv1x1(out, num_3x3_red, batch_norm=use_batch_norm)
out1 = conv3x3(out1, num_3x3, stride=2, batch_norm=use_batch_norm)
out2 = conv1x1(out, num_d7_3x3_red, batch_norm=use_batch_norm)
out2 = conv1x7(out2, num_d7_1, batch_norm=use_batch_norm)
out2 = conv7x1(out2, num_d7_2, batch_norm=use_batch_norm)
out2 = conv3x3(out2, num_d7_3x3, stride=2, batch_norm=use_batch_norm)
out3 = max_pool_3x3(out, stride=2)
return concat(3, [out1, out2, out3])
def reductionB(out):
out1 = conv1x1(out, 192, batch_norm=use_batch_norm)
out1 = conv3x3(out1,
192,
stride=2,
padding="VALID",
batch_norm=use_batch_norm)
out2 = conv1x1(out, 256, batch_norm=use_batch_norm)
out2 = conv1x7(out2, 256, batch_norm=use_batch_norm)
out2 = conv7x1(out2, 320, batch_norm=use_batch_norm)
out2 = conv3x3(out2,
320,
stride=2,
padding="VALID",
batch_norm=use_batch_norm)
out3 = max_pool_3x3(out, stride=2, padding="VALID")
return concat(3, [out1, out2, out3])
def stem(x):
"""
Stem fo the pure InceptionV4 and Inception-ResNet-V2
"""
out = conv3x3(x, 32, stride=2, padding="VALID", batch_norm=use_batch_norm)
out = conv3x3(out,
32,
stride=1,
padding="VALID",
batch_norm=use_batch_norm)
out = conv3x3(out, 64, stride=1, padding="SAME", batch_norm=use_batch_norm)
out1 = max_pool_3x3(out, stride=2, padding="VALID")
out2 = conv3x3(out,
96,
stride=2,
padding="VALID",
batch_norm=use_batch_norm)
out = concat(3, [out1, out2])
out1 = conv1x1(out, 64, batch_norm=use_batch_norm)
out1 = conv3x3(out1, 96, padding="VALID", batch_norm=use_batch_norm)
out2 = conv1x1(out, 64, batch_norm=use_batch_norm)
out2 = conv1x7(out2, 64, batch_norm=use_batch_norm)
out2 = conv7x1(out2, 64, batch_norm=use_batch_norm)
out2 = conv3x3(out2, 96, padding="VALID", batch_norm=use_batch_norm)
out = concat(3, [out1, out2])
out1 = conv3x3(out,
192,
stride=2,
padding="VALID",
batch_norm=use_batch_norm)
out2 = max_pool_3x3(out, stride=2, padding="VALID")
out = concat(3, [out1, out2])
return out