def _init_data(self):
self.train = _get_data(Config.train_save_file)
self.valid = _get_data(Config.valid_save_file)
self.test = _get_data(Config.test_save_file)
# init = tf.global_variables_initializer()
# sess.run(init)
graph = tf.get_default_graph()
ph, train_phase = _init_placeholder(graph)
print(ph)
prediction = tf.get_collection('pred_network')[0]
# loss = tf.get_collection('loss')[0]
loss = graph.get_tensor_by_name('loss:0')
total_emb, single_size, numerical_size, multi_size = _get_conf()
field_size = single_size + numerical_size + multi_size
embedding_length = field_size * Config.embedding_size
test = _get_data(Config.test_save_file)
test = test[:30000]
test_batch = _get_batch(test,
-1,
single_size=single_size,
numerical_size=numerical_size,
multi_size=multi_size)
test_label = get_label(test_batch[0], 2)
test_dict = {
ph['single_index']: test_batch[1],
ph['numerical_index']: test_batch[2],
ph['numerical_value']: test_batch[3],
ph['value']: test_batch[-1],
ph['label']: test_label,
train_phase: False