'''
Created on Jul 10, 2017

@author: David
'''

from train_classifier import train_classifier
from evaluate2 import evaluate

svalex_file  = "svalex-r-nh-"
swellex_file = "siwoco-swellex-topic-bigram-compact-nh.csv"

files = [svalex_file]
layer_sizes = [(100,)]
learning_rates = [0.001]

best_svalex  = None
best_swellex = None
best_svalex_f1  = 0
best_swellex_f1 = 0

for f in files:
    for lr in learning_rates:
        for layer_size in layer_sizes:
            pname = train_classifier(f+"dev.csv", layer_size, lr)
            avg_f1 = evaluate(pname, f+"test.csv")
            if avg_f1 > best_svalex_f1:
                best_svalex_f1 = avg_f1
                best_svalex = pname
            print("Best classifier: {}".format(pname))

print("Done with Grid Search!")