Open hoyeunglee opened 5 years ago
from seq2seq import SimpleSeq2Seq, Seq2Seq, AttentionSeq2Seq import os import csv import sys import logging import time input_dim=1 input_length=6 hidden_dim=10 output_length=6 output_dim=1 depth=4 models = [] model = Seq2Seq(output_dim=output_dim, hidden_dim=hidden_dim, output_length=output_length, input_shape=(input_length, input_dim)) #models += [Seq2Seq(output_dim=output_dim, hidden_dim=hidden_dim, output_length=output_length, input_shape=(input_length, input_dim), peek=True)] #models += [Seq2Seq(output_dim=output_dim, hidden_dim=hidden_dim, output_length=output_length, input_shape=(input_length, input_dim), depth=2)] #models += [Seq2Seq(output_dim=output_dim, hidden_dim=hidden_dim, output_length=output_length, input_shape=(input_length, input_dim), peek=True, depth=2)] model.compile(loss='mse', optimizer='sgd') y = [] x = [] with open('./Mark Six.csv', 'rt') as csvfile: reader = csv.DictReader(csvfile) count = 1 for row in reader: if count <= 1626: x = x + [[[int(row['Winning Number 1'].strip())],[int(row['2'].strip())],[int(row['3'].strip())],[int(row['4'].strip())],[int(row['5'].strip())],[int(row['6'].strip())]]] count = count + 1 with open('./Mark Six.csv', 'rt') as csvfile: reader = csv.DictReader(csvfile) count = 1 for row in reader: if count > 1 and count <= 1627: y = y + [[[int(row['Winning Number 1'].strip())],[int(row['2'].strip())],[int(row['3'].strip())],[int(row['4'].strip())],[int(row['5'].strip())],[int(row['6'].strip())]]] count = count + 1 model.fit(np.array(x), np.array(y), epochs=1) #model = Seq2Seq(output_dim=output_dim, hidden_dim=hidden_dim, output_length=output_length, input_shape=(input_length, input_dim), peek=True, depth=2, teacher_force=True) #model.compile(loss='mse', optimizer='sgd') #model.fit([np.array(x), np.array(y)], np.array(y), epochs=1) x_test = [] with open('./Mark Six.csv', 'rt') as csvfile: reader = csv.DictReader(csvfile) count = 1 for row in reader: if count > 1627-2: x_test = x_test + [[[int(row['Winning Number 1'].strip())],[int(row['2'].strip())],[int(row['3'].strip())],[int(row['4'].strip())],[int(row['5'].strip())],[int(row['6'].strip())]]] count = count + 1 y_test = [] with open('./Mark Six.csv', 'rt') as csvfile: reader = csv.DictReader(csvfile) count = 1 for row in reader: if count > 1627-2: y_test = y_test + [[[int(row['Winning Number 1'].strip())],[int(row['2'].strip())],[int(row['3'].strip())],[int(row['4'].strip())],[int(row['5'].strip())],[int(row['6'].strip())]]] count = count + 1 model.predict(np.array([x_test[3]]))