from mxnet.gluon.model_zoo import vision
res_net50 = vision.resnet50_v1()
how to modify the kernel size of the first layer "conv " .
7x7 -> 3x3
You can use register_child to replace the layer:
from mxnet.gluon.model_zoo import vision
from mxnet import gluon
import mxnet as mx
net = vision.resnet50_v1()
new_layer = gluon.nn.Conv2D(64, kernel_size=(8, 8), strides=(4, 4), padding=(3, 3))
f = net.features
f.register_child( new_layer, "0")
new_layer.initialize(mx.init.Xavier())
print(net)
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How to modify output?
for example:
train_net = gcv.model_zoo.get_model(“ResNet34_v1”, pretrained = True)
print(train_net.output)
#print result
Dense(512 -> 1000, linear)
Now I want to modify the train_net.output
it has three output,for example
output_1:Dense(512 -> 1000, linear)
output_2:Dense(512 -> 1000, linear)
output_3:Dense(512 -> 1000, linear)
how to modify train_net.output
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