"If u want to accelerate this process, please see read_me -> transform_data_to_feature_and_dump"
)
accu_dict, reverse_accu_dict = generator.read_accu()
word_dict, embedding, reverse_dictionary = generator.get_dictionary_and_embedding(
)
train_data_x, train_data_y = generator.read_data_in_accu_format(
constant.DATA_TRAIN, embedding, word_dict, accu_dict, one_hot=True)
valid_data_x, valid_data_y = generator.read_data_in_accu_format(
constant.DATA_VALID, embedding, word_dict, accu_dict, one_hot=True)
test_data_x, test_data_y = generator.read_data_in_accu_format(
constant.DATA_TEST, embedding, word_dict, accu_dict, one_hot=True)
print("reading complete!")
# just test generate_accu_batch
x, y = generator.generate_batch(training_batch_size, train_data_x,
train_data_y)
print(x.shape)
print("data load complete")
print("The model begin here")
print(len(train_data_y[0]))
model = AccusationNN()
# run part
with model.graph.as_default():
with tf.Session() as sess:
# 初始化变量
sess.run(tf.global_variables_initializer())
# 保存参数所用的保存器
saver = tf.train.Saver(max_to_keep=1)
"No dump file read original file! Please wait... "
"If u want to accelerate this process, please see read_me -> transform_data_to_feature_and_dump"
)
accu_dict, reverse_accu_dict = generator.read_accu()
word_dict, embedding, reverse_dictionary = generator.get_dictionary_and_embedding(
)
train_data_x, train_data_y = generator.read_data_in_accu_format(
constant.DATA_TRAIN, embedding, word_dict, accu_dict, one_hot=True)
valid_data_x, valid_data_y = generator.read_data_in_accu_format(
constant.DATA_VALID, embedding, word_dict, accu_dict, one_hot=True)
print("reading complete!")
# just test generate_accu_batch
x, y = generator.generate_batch(training_batch_size, train_data_x,
train_data_y)
print(x.shape)
print("data load complete")
print("The model begin here")
print(len(train_data_y[0]))
model = AccusationNN()
# run part
with model.graph.as_default():
with tf.Session() as sess:
# 初始化变量
sess.run(tf.global_variables_initializer())
# 保存参数所用的保存器
saver = tf.train.Saver(max_to_keep=1)
"No dump file read original file! Please wait... "
"If u want to accelerate this process, please see read_me -> transform_data_to_feature_and_dump"
)
accu_dict, reverse_accu_dict = generator.read_accu()
word_dict, embedding, reverse_dictionary = generator.get_dictionary_and_embedding(
)
train_data_x, train_data_y = generator.read_data_in_accu_format(
constant.DATA_TRAIN, embedding, word_dict, accu_dict, one_hot=False)
valid_data_x, valid_data_y = generator.read_data_in_accu_format(
constant.DATA_VALID, embedding, word_dict, accu_dict, one_hot=False)
print("reading complete!")
# just test generate_accu_batch
train_data_x_for_validate, train_data_y_for_validate = generator.generate_batch(
valid_batch_size, train_data_x, train_data_y)
print("data load complete")
print("The model begin here")
clf = xgb.XGBClassifier(learning_rate=0.05,
objective='multi:softmax',
n_estimators=100,
max_depth=4,
reg_alpha=0.2,
min_child_weight=3)
print(valid_data_y.shape)
# try to load model
# try:
# boost = xgb.Booster()