y = T.imatrix()
mask = T.ivector()
# Construct RNN class
classifier = RNN(
input=x,
n_in=INPUT_DIM,
n_hidden=NEURONS_PER_LAYER,
n_out=OUTPUT_DIM,
n_layers=HIDDEN_LAYERS,
n_total=max_length,
batch=BATCH_SIZE,
mask=mask
)
classifier.load_model(args.model_in)
# Build Test Model
print "Building Test Model"
test_model = theano.function(
inputs=[x,mask],
outputs=classifier.y_pred
)
# Create Phone Map
f = open('data/48_39.map','r')
phone_map = {}
i = 0
for l in f:
phone_map[i] = l.strip(' \n').split('\t')[1]
i += 1
