lcamposgarrido

import tensorflow as tf
import tensorflow_ranking as tfr

_TRAIN_DATA_PATH="/data/train.txt"
_TEST_DATA_PATH="/data/test.txt"
_LOSS="approx_ndcg_loss"
_N_ASSETS=100
_N_FEATURES=16
_BATCH_SIZE=32
_HIDDEN_LAYER_DIMS=["20", "10"]

lcamposgarrido

from agent.agent import Agent
from functions import *
import sys

if len(sys.argv) != 4:
	print("Usage: python train.py [stock] [window] [episodes]")
	exit()

stock_name, window_size, episode_count = sys.argv[1], int(sys.argv[2]), int(sys.argv[3])

lcamposgarrido

import keras
from keras.models import Sequential
from keras.models import load_model
from keras.layers import Dense
from keras.optimizers import Adam

import numpy as np
import random
from collections import deque