a b/mains/main_AE.py 

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#!/usr/bin/env python





  
  

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import tensorflow as tf





  
  

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from models import autoencoder





  
  

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from trainers.AE import AE





  
  

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from utils import Evaluation





  
  

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from utils.default_config_setup import get_config, get_options, get_datasets, Dataset





  
  

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tf.reset_default_graph()





  
  

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dataset = Dataset.BRAINWEB





  
  

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options = get_options(batchsize=128, learningrate=0.0001, numEpochs=2, zDim=128, outputWidth=128, outputHeight=128)





  
  

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options['data']['dir'] = options["globals"][dataset.value]





  
  

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datasetHC, datasetPC = get_datasets(options, dataset=dataset)





  
  

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config = get_config(trainer=AE, options=options, optimizer='ADAM', intermediateResolutions=[8, 8], dropout_rate=0.2, dataset=datasetHC)





  
  

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# Create an instance of the model and train it





  
  

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model = AE(tf.Session(), config, network=autoencoder.autoencoder)





  
  

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# Train it





  
  

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model.train(datasetHC)





  
  

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# Evaluate





  
  

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Evaluation.evaluate(datasetPC, model, options, description=f"{type(datasetHC).__name__}-{options['threshold']}", epoch=str(options['train']['numEpochs']))