diff --git a/metacode/pso_meta.py b/metacode/pso_meta.py index b7042b2..2cfdfe8 100644 --- a/metacode/pso_meta.py +++ b/metacode/pso_meta.py @@ -16,7 +16,7 @@ class PSO(object): """ self.func = func self.n_particles = n_particles - self.init_pos = init_pos # 곰샥헐 차원 + self.init_pos = init_pos # 검색할 차원 self.particle_dim = len(init_pos) # 검색할 차원의 크기 self.particles_pos = np.random.uniform(size=(n_particles, self.particle_dim)) \ * self.init_pos diff --git a/mnist.py b/mnist.py index 42f7952..34fd717 100644 --- a/mnist.py +++ b/mnist.py @@ -79,9 +79,9 @@ loss = 'huber_loss' # loss = 'mean_squared_error' -pso_mnist = Optimizer(model, loss=loss, n_particles=75, c0=0.4, c1=0.8, w_min=0.6, w_max=0.95, random=0.3) +pso_mnist = Optimizer(model, loss=loss, n_particles=50, c0=0.4, c1=0.8, w_min=0.4, w_max=0.95, negative_swarm=0.3) weight, score = pso_mnist.fit( - x_test, y_test, epochs=500, save=True, save_path="./result/mnist", renewal="acc", empirical_balance=False, Dispersion=False, check_point=10) + x_test, y_test, epochs=500, save=True, save_path="./result/mnist", renewal="acc", empirical_balance=True, Dispersion=False, check_point=10) # pso_mnist.model_save("./result/mnist") # pso_mnist.save_info("./result/mnist") diff --git a/plt.ipynb b/plt.ipynb index aef8bb8..d7f568b 100644 --- a/plt.ipynb +++ b/plt.ipynb @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 2, "metadata": { "tags": [] }, @@ -28,12 +28,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "(33, 100)\n" + "(316, 150)\n" ] }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -44,16 +44,16 @@ { "data": { "text/plain": [ - "13995" + "16646" ] }, - "execution_count": 35, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "iris = pd.read_csv(\"./result/iris/05-31-19-49_50_500_0.4_0.8_0.7_acc.csv\", header=None)\n", + "iris = pd.read_csv(\"./result/mnist/05-31-19-54_75_500_0.4_0.8_0.6_acc.csv\", header=None)\n", "print(iris.shape)\n", "# print(iris.head)\n", "loss = []\n", diff --git a/pso/optimizer.py b/pso/optimizer.py index 625697e..75dac86 100644 --- a/pso/optimizer.py +++ b/pso/optimizer.py @@ -12,11 +12,11 @@ from tqdm import tqdm from datetime import datetime import json import gc +from copy import copy, deepcopy from pso.particle import Particle - class Optimizer: """ Args: @@ -27,18 +27,19 @@ class Optimizer: c1 (float): global rate - 전역 최적값 관성 수치 w_min (float): 최소 관성 수치 w_max (float): 최대 관성 수치 - random (float): 랜덤 파티클 비율 - 0 ~ 1 사이의 값 + nefative_swarm (float): 최적해와 반대로 이동할 파티클 비율 - 0 ~ 1 사이의 값 """ + def __init__( self, model: keras.models, - loss = "mse", + loss="mse", n_particles: int = 10, c0=0.5, c1=1.5, w_min=0.5, w_max=1.5, - random:float = 0, + negative_swarm: float = 0, ): self.model = model # 모델 구조 self.loss = loss # 손실함수 @@ -61,10 +62,11 @@ class Optimizer: w_ = np.random.uniform(-1.5, 1.5, len(w_)) m.set_weights(self._decode(w_, sh_, len_)) m.compile(loss=self.loss, optimizer="sgd", metrics=["accuracy"]) - if i < random * self.n_particles: - self.particles[i] = Particle(m, loss, random=True) + if i < negative_swarm * self.n_particles: + self.particles[i] = Particle(m, loss, negative=True) else: - self.particles[i] = Particle(m, loss, random=False) + self.particles[i] = Particle(m, loss, negative=False) + gc.collect() """ Args: @@ -74,6 +76,7 @@ class Optimizer: (list) : 가중치의 원본 shape (list) : 가중치의 원본 shape의 길이 """ + def _encode(self, weights): # w_gpu = cp.array([]) w_gpu = np.array([]) @@ -86,6 +89,8 @@ class Optimizer: # w_gpu = cp.append(w_gpu, w_) w_gpu = np.append(w_gpu, w_) + del weights + gc.collect() return w_gpu, shape, lenght """ @@ -119,6 +124,8 @@ class Optimizer: self.model.set_weights(weights) self.model.compile(loss=self.loss, optimizer="sgd", metrics=["accuracy"]) score = self.model.evaluate(x, y, verbose=0)[1] + + gc.collect() if score > 0: return 1 / (1 + score) else: @@ -136,6 +143,7 @@ class Optimizer: Dispersion : bool - True : g_best 의 값을 분산시켜 전역해를 찾음, False : g_best 의 값만 사용 check_point : int - 저장할 위치 - None : 저장 안함 """ + def fit( self, x, @@ -149,24 +157,27 @@ class Optimizer: check_point: int = None, ): self.save_path = save_path - + self.renewal = renewal if renewal == "acc": self.g_best_score = 0 elif renewal == "loss": self.g_best_score = np.inf - - if save: - if save_path is None: - raise ValueError("save_path is None") - else: - self.save_path = save_path - os.makedirs(save_path, exist_ok=True) - self.day = datetime.now().strftime("%m-%d-%H-%M") - + try: + if save: + if save_path is None: + raise ValueError("save_path is None") + else: + self.save_path = save_path + if not os.path.exists(save_path): + os.makedirs(save_path, exist_ok=True) + self.day = datetime.now().strftime("%m-%d-%H-%M") + except ValueError as e: + print(e) + sys.exit(1) # for i, p in enumerate(self.particles): for i in tqdm(range(self.n_particles), desc="Initializing Particles"): - p = self.particles[i] + p = copy(self.particles[i]) local_score = p.get_score(x, y, renewal=renewal) if renewal == "acc": @@ -179,9 +190,12 @@ class Optimizer: self.g_best_score = local_score[0] self.g_best = p.get_best_weights() self.g_best_ = p.get_best_weights() - + del local_score + del p + gc.collect() + print(f"initial g_best_score : {self.g_best_score}") - + try: for _ in range(epochs): print(f"epoch {_ + 1}/{epochs}") @@ -192,6 +206,12 @@ class Optimizer: min_loss = np.inf max_loss = 0 + ts = self.c0 + np.random.rand() * (self.c1 - self.c0) + g_, g_sh, g_len = self._encode(self.g_best) + decrement = (epochs - (_) + 1) / epochs + g_ = (1 - decrement) * g_ + decrement * ts + self.g_best_ = self._decode(g_, g_sh, g_len) + # for i in tqdm(range(len(self.particles)), desc=f"epoch {_ + 1}/{epochs}", ascii=True): for i in range(len(self.particles)): w = self.w_max - (self.w_max - self.w_min) * _ / epochs @@ -215,11 +235,19 @@ class Optimizer: g_a = self.avg_score l_b = p_b - g_a l_b = np.sqrt(np.power(l_b, 2)) - p_ = 1 / (self.n_particles * np.linalg.norm(self.c1 - self.c0)) * l_b + p_ = ( + 1 + / (self.n_particles * np.linalg.norm(self.c1 - self.c0)) + * l_b + ) p_ = np.exp(-1 * p_) w_p = p_ w_g = 1 - p_ - + del p_b + del g_a + del l_b + del p_ + score = self.particles[i].step_w( x, y, self.c0, self.c1, w, g_best, w_p, w_g, renewal=renewal ) @@ -238,8 +266,8 @@ class Optimizer: self.g_best_score = score[0] self.g_best = self.particles[i].get_best_weights() - loss += score[0] - acc += score[1] + loss = loss + score[0] + acc = acc + score[1] if score[0] < min_loss: min_loss = score[0] if score[0] > max_loss: @@ -258,19 +286,8 @@ class Optimizer: f.write(f"{score[0]}, {score[1]}") if i != self.n_particles - 1: f.write(", ") - - TS = self.c0 + np.random.rand() * (self.c1 - self.c0) - g_, g_sh, g_len = self._encode(self.g_best) - decrement = (epochs - (_) + 1) / epochs - g_ = (1 - decrement) * g_ + decrement * TS - self.g_best_ = self._decode(g_, g_sh, g_len) - - if save: - with open( - f"./{save_path}/{self.day}_{self.n_particles}_{epochs}_{self.c0}_{self.c1}_{self.w_min}_{renewal}.csv", - "a", - ) as f: - f.write("\n") + else: + f.write("\n") # print(f"loss min : {min_loss} | loss max : {max_loss} | acc min : {min_score} | acc max : {max_score}") # print(f"loss avg : {loss/self.n_particles} | acc avg : {acc/self.n_particles} | Best {renewal} : {self.g_best_score}") @@ -279,12 +296,13 @@ class Optimizer: ) gc.collect() - + if check_point is not None: if _ % check_point == 0: os.makedirs(f"./{save_path}/{self.day}", exist_ok=True) self._check_point_save(f"./{save_path}/{self.day}/ckpt-{_}") - self.avg_score = acc/self.n_particles + self.avg_score = acc / self.n_particles + except KeyboardInterrupt: print("Ctrl + C : Stop Training") except MemoryError: @@ -296,8 +314,8 @@ class Optimizer: print("model save") self.save_info(save_path) print("save info") + return self.g_best, self.g_best_score - def get_best_model(self): model = keras.models.model_from_json(self.model.to_json()) @@ -329,12 +347,11 @@ class Optimizer: "a", ) as f: json.dump(json_save, f, indent=4) - f.write(",\n") - + def _check_point_save(self, save_path: str = f"./result/check_point"): model = self.get_best_model() model.save_weights(save_path) - + def model_save(self, save_path: str = "./result"): model = self.get_best_model() model.save( diff --git a/pso/particle.py b/pso/particle.py index 0aed61b..27e12f1 100644 --- a/pso/particle.py +++ b/pso/particle.py @@ -1,21 +1,26 @@ - import tensorflow as tf from tensorflow import keras # import cupy as cp import numpy as np +import gc + class Particle: - def __init__(self, model:keras.models, loss, random:bool = False): + def __init__(self, model: keras.models, loss, negative: bool = False): self.model = model self.loss = loss - self.init_weights = self.model.get_weights() - i_w_,s_,l_ = self._encode(self.init_weights) + init_weights = self.model.get_weights() + i_w_, s_, l_ = self._encode(init_weights) i_w_ = np.random.rand(len(i_w_)) / 5 - 0.10 - self.velocities = self._decode(i_w_,s_,l_) - self.random = random + self.velocities = self._decode(i_w_, s_, l_) + self.negative = negative self.best_score = 0 - self.best_weights = self.init_weights + self.best_weights = init_weights + + del i_w_, s_, l_ + del init_weights + gc.collect() """ Returns: @@ -23,7 +28,8 @@ class Particle: (list) : 가중치의 원본 shape (list) : 가중치의 원본 shape의 길이 """ - def _encode(self, weights:list): + + def _encode(self, weights: list): # w_gpu = cp.array([]) w_gpu = np.array([]) lenght = [] @@ -34,6 +40,7 @@ class Particle: lenght.append(len(w_)) # w_gpu = cp.append(w_gpu, w_) w_gpu = np.append(w_gpu, w_) + gc.collect() return w_gpu, shape, lenght """ @@ -41,7 +48,7 @@ class Particle: (list) : 가중치 원본 shape으로 복원 """ - def _decode(self, weight:list, shape, lenght): + def _decode(self, weight: list, shape, lenght): weights = [] start = 0 for i in range(len(shape)): @@ -52,10 +59,13 @@ class Particle: # w_ = w_.reshape(shape[i]) weights.append(w_) start = end - + del start, end, w_ + del shape, lenght + del weight + gc.collect() return weights - def get_score(self, x, y, renewal:str = "acc"): + def get_score(self, x, y, renewal: str = "acc"): self.model.compile(loss=self.loss, optimizer="sgd", metrics=["accuracy"]) score = self.model.evaluate(x, y, verbose=0) # print(score) @@ -67,56 +77,97 @@ class Particle: if score[0] < self.best_score: self.best_score = score[0] self.best_weights = self.model.get_weights() - + gc.collect() return score + def _update_velocity(self, local_rate, global_rate, w, g_best): - encode_w, w_sh, w_len = self._encode(weights = self.model.get_weights()) - encode_v, _, _ = self._encode(weights = self.velocities) - encode_p, _, _ = self._encode(weights = self.best_weights) - encode_g, _, _ = self._encode(weights = g_best) + encode_w, w_sh, w_len = self._encode(weights=self.model.get_weights()) + encode_v, v_sh, v_len = self._encode(weights=self.velocities) + encode_p, p_sh, p_len = self._encode(weights=self.best_weights) + encode_g, g_sh, g_len = self._encode(weights=g_best) r0 = np.random.rand() r1 = np.random.rand() - new_v = w * encode_v + local_rate * r0 * (encode_p - encode_w) + global_rate * r1 * (encode_g - encode_w) + if self.negative: + new_v = ( + w * encode_v + + -1 * local_rate * r0 * (encode_p - encode_w) + + -1 * global_rate * r1 * (encode_g - encode_w) + ) + else: + new_v = ( + w * encode_v + + local_rate * r0 * (encode_p - encode_w) + + global_rate * r1 * (encode_g - encode_w) + ) self.velocities = self._decode(new_v, w_sh, w_len) - + del encode_w, w_sh, w_len + del encode_v, v_sh, v_len + del encode_p, p_sh, p_len + del encode_g, g_sh, g_len + del r0, r1 + gc.collect() + def _update_velocity_w(self, local_rate, global_rate, w, w_p, w_g, g_best): - encode_w, w_sh, w_len = self._encode(weights = self.model.get_weights()) - encode_v, _, _ = self._encode(weights = self.velocities) - encode_p, _, _ = self._encode(weights = self.best_weights) - encode_g, _, _ = self._encode(weights = g_best) + encode_w, w_sh, w_len = self._encode(weights=self.model.get_weights()) + encode_v, v_sh, v_len = self._encode(weights=self.velocities) + encode_p, p_sh, p_len = self._encode(weights=self.best_weights) + encode_g, g_sh, g_len = self._encode(weights=g_best) r0 = np.random.rand() r1 = np.random.rand() - new_v = w * encode_v + local_rate * r0 * (w_p * encode_p - encode_w) + global_rate * r1 * (w_g * encode_g - encode_w) + if self.negative: + new_v = ( + w * encode_v + + -1 * local_rate * r0 * (w_p * encode_p - encode_w) + + -1 * global_rate * r1 * (w_g * encode_g - encode_w) + ) + else: + new_v = ( + w * encode_v + + local_rate * r0 * (w_p * encode_p - encode_w) + + global_rate * r1 * (w_g * encode_g - encode_w) + ) self.velocities = self._decode(new_v, w_sh, w_len) - + del encode_w, w_sh, w_len + del encode_v, v_sh, v_len + del encode_p, p_sh, p_len + del encode_g, g_sh, g_len + del r0, r1 + gc.collect() + def _update_weights(self): - encode_w, w_sh, w_len = self._encode(weights = self.model.get_weights()) - encode_v, _, _ = self._encode(weights = self.velocities) - if self.random: - encode_v = -0.5 * encode_v + encode_w, w_sh, w_len = self._encode(weights=self.model.get_weights()) + encode_v, v_sh, v_len = self._encode(weights=self.velocities) new_w = encode_w + encode_v self.model.set_weights(self._decode(new_w, w_sh, w_len)) + del encode_w, w_sh, w_len + del encode_v, v_sh, v_len + gc.collect() def f(self, x, y, weights): self.model.set_weights(weights) - score = self.model.evaluate(x, y, verbose = 0)[1] + score = self.model.evaluate(x, y, verbose=0)[1] + gc.collect() if score > 0: return 1 / (1 + score) else: return 1 + np.abs(score) - def step(self, x, y, local_rate, global_rate, w, g_best, renewal:str = "acc"): + def step(self, x, y, local_rate, global_rate, w, g_best, renewal: str = "acc"): self._update_velocity(local_rate, global_rate, w, g_best) self._update_weights() + gc.collect() return self.get_score(x, y, renewal) - - def step_w(self, x, y, local_rate, global_rate, w, g_best, w_p, w_g, renewal:str = "acc"): + + def step_w( + self, x, y, local_rate, global_rate, w, g_best, w_p, w_g, renewal: str = "acc" + ): self._update_velocity_w(local_rate, global_rate, w, w_p, w_g, g_best) self._update_weights() + gc.collect() return self.get_score(x, y, renewal) - + def get_best_score(self): return self.best_score - + def get_best_weights(self): - return self.best_weights \ No newline at end of file + return self.best_weights diff --git a/readme.md b/readme.md index da5583c..7008668 100644 --- a/readme.md +++ b/readme.md @@ -72,7 +72,7 @@ pso 알고리즘을 이용하여 오차역전파 함수를 최적화 하는 방
위의 아이디어는 원래의 목표와 다른 방향으로 가고 있습니다. 따라서 다른 방법을 모색해야할 것 같습니다 -

+
### Trouble Shooting @@ -89,5 +89,11 @@ pso 알고리즘을 이용하여 오차역전파 함수를 최적화 하는 방 > > > pso 와 random forest 방식이 매우 유사하다고 생각하여 학습할 때 뿐만 아니라 예측 할 때도 이러한 방식으로 사용할 수 있을 것 같습니다 -이곳의 코드를 참고하여 좀더 효율적인 코드로 수정하였습니다 -> +# 참고 자료 + +> A partilce swarm optimization algorithm with empirical balance stategy -
+> psokeras -
+> PSO의 다양한 영역 탐색과 +지역적 미니멈 인식을 위한 전략 -
+> PC 클러스터 기반의 Multi-HPSO를 이용한 안전도 제약의 경제 급전 -
+> Particle 2-Swarm Optimization for Robust Search -