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MxNet Convert json to symbol
Convert network written in json format to mxnet symbol code
If you have a pretrained model in mxnet *.json format.
Using the Fine-tuning strategy to transfer learned recognition capabilities from general domains to the specific challenge.
You can use the example code below directly in the R console.
For example for the DesNet.
Dense_model = mx.model.load('model/densenet-imagenet-169-0', 125)
all_layers = Dense_model$symbol$get.internals()
relu1_output = which(all_layers$outputs == 'relu1_output') %>% all_layers$get.output()
softmax_output = which(all_layers$outputs == 'softmax_output') %>% all_layers$get.output()
out = mx.symbol.Group(c(relu1_output, softmax_output))
executor = mx.simple.bind(symbol = out, data = c(224, 224, 3, 1), ctx = mx.cpu())
mx.exec.update.arg.arrays(executor, Dense_model$arg.params, match.name = TRUE)
mx.exec.update.aux.arrays(executor, Dense_model$aux.params, match.name = TRUE)
And run the executor or train by other mxnet function.
Using symbol.get_internals to get the internal parts, can only get symbol from start.
When you want to use specific layers or
Changing some specific layers architecture in pre-train model.
You may rewrite the whole Net.
Or you may use function in '1. LeNet/3. convert json to symbol.R', converting json files to R code for the example of LeNet.
Also, there is an example of DesNet.
The example code in here'1. LeNet/3. convert json to symbol.R'
Pre-Train densenet model is downloading from