# instantiate model
model = MemoryNet(hdim=300,
num_hops=1,
memsize=memsize,
window_size=window_size,
sentence_size=sentence_size,
vocab_size=vocab_size,
num_candidates=num_candidates,
lr1=0.001,
lr2=0.001)
# setup visualizer
# by default, writes to ./log/
vis = Visualizer()
vis.attach_scalars(model)
#vis.attach_params() # histograms of trainable variables
# gpu config
config = tf.ConfigProto()
#config.gpu_options.allow_growth = True
with tf.Session(config=config) as sess:
# init session
sess.run(tf.global_variables_initializer())
# add graph to visualizer
vis.attach_graph(sess.graph)
# init trainer
trainer = Trainer(sess, model, datasrc, batch_size)
