run_GANMF.py

import os
import json
import shutil
import random
import numpy as np
import tensorflow as tf
# tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)    # TF > 1.12
tf.logging.set_verbosity(tf.logging.ERROR)
from warnings import simplefilter

# Seed for reproducibility of results
seed = 1337
random.seed(seed)
np.random.seed(seed)
tf.set_random_seed(seed)

from datasets.Movielens import Movielens
from GANRec.GANMF import GANMF
from Base.Evaluation.Evaluator import EvaluatorHoldout

# Supress Tensorflow logs
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
os.environ['KMP_WARNINGS'] = '0'
simplefilter(action='ignore', category=UserWarning)
simplefilter(action='ignore', category=FutureWarning)

use_gpu = False
verbose = False
only_build = False
transposed = False

if not use_gpu:
    os.environ['CUDA_VISIBLE_DEVICES'] = ''

reader = Movielens(version='100K', split_ratio=[0.6, 0.2, 0.2], use_local=True, implicit=True, verbose=False, seed=seed)

URM_train = reader.get_URM_train(transposed=transposed)
URM_validation = reader.get_URM_validation(transposed=transposed)
URM_test = reader.get_URM_test(transposed=transposed)

evaluator = EvaluatorHoldout(URM_test, [5, 20], exclude_seen=True)
evaluatorValidation = EvaluatorHoldout(URM_validation, [5], exclude_seen=True)

gan = GANMF(URM_train, mode='user')

gan.fit(num_factors=10,
        emb_dim=128,
        d_reg=1e-4,
        g_reg=0,
        epochs=300,
        batch_size=128,
        g_lr=1e-3,
        d_lr=1e-3,
        d_steps=1,
        g_steps=1,
        recon_coefficient=0.05,
        m=3,
        allow_worse=5,
        freq=5,
        validation_evaluator=evaluatorValidation,
        sample_every=10,
        validation_set=URM_validation)

if not only_build:
    results_dic, results_run_string = evaluator.evaluateRecommender(gan)
    print(results_run_string)

    map_folder = os.path.join('plots', gan.RECOMMENDER_NAME, 'MAP_' + str(results_dic[5]['MAP'])[:7])
    if os.path.exists(map_folder):
        shutil.rmtree(map_folder)
    shutil.move(src=gan.logsdir, dst=map_folder)