run_simple.py

from active_utils import *
from configs import *
from simple_learning import start_simple_learning
import sys

model_config = ModelConfig()
train_file = '/mnt/nfs-storage/data/english/train.txt'
test_file = '/mnt/nfs-storage/data/english/test.txt'
dev_file = '/mnt/nfs-storage/data/english/valid.txt'
train_vectors = "/mnt/nfs-storage/data/english/embeding/train_vectors_lists.txt"
test_vectors = "/mnt/nfs-storage/data/english/embeding/test_vectors_lists.txt"
dev_vectors = "/mnt/nfs-storage/data/english/embeding/dev_vectors_lists.txt"
vocab = '/mnt/nfs-storage/data/english/vocab.txt'


train = load_data(train_file, train_vectors)
dev = load_data(dev_file, dev_vectors)
test = load_data(test_file, test_vectors)

params = [300, 500, 800, 1000, 1100, 1300, 1500, 1750, 2000, 3000, 4000, 6000, 8000, 10000, 12000, 15000, 20000, 25000, 30000, 40000]
# params = [400, 600, 700, 900, 1200, 1400, 1600, 1700, 1800, 1900, 2500, 3500, 4500, 5000, 5500, 6500, 7000, 7500, 8500, 9000, 9500]
# params = [400000]
number = find_new_number("/mnt/nfs-storage/logs/simple")
model_config.loginfo = "/mnt/nfs-storage/logs/simple/" + number + "_loginfo.csv"
seed = 0
model_config.number = number

model_config.save_model_path = "saved_models/simple_model" + number + ".pth"

try:
    seed_cmd = sys.argv[1]
except:
    seed_cmd = "0"

for i in range(5):
        for param in params:
            for j in range(2):
                seed += 1
                if seed>=float(seed_cmd):
                    model_config.init_budget = param
                    model_config.seed = seed
                    stat_in_file(model_config.loginfo, ["\n\n"])
                    stat_in_file(model_config.loginfo, ['BEGIN', 'init_budget', model_config.init_budget, "lr", model_config.learning_rate,"batch_size", model_config.batch_size, 'seed', model_config.seed ])
                    start_simple_learning(train, dev, test, model_config)
                    clear_old_model(model_config.save_model_path)