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80695f304d
tensorboard 선택 시 자동으로 프로세스 실행 비어있는 포트를 자동으로 탐색하여 오픈 이전 최적해와 비교하여 관성치를 높게 주는 방법을 일시 폐기 digits 테스트 추가 tensorboard 자동 설치 추가
76 lines
1.5 KiB
Python
76 lines
1.5 KiB
Python
import os
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import sys
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import pandas as pd
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import tensorflow as tf
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from sklearn.datasets import load_digits
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from sklearn.model_selection import train_test_split
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from tensorflow import keras
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from tensorflow.keras import layers
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from tensorflow.keras.layers import Dense
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from tensorflow.keras.models import Sequential
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from tensorflow.keras.utils import to_categorical
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from pso import optimizer
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os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
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def make_model():
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model = Sequential()
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model.add(Dense(12, input_dim=64, activation="relu"))
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model.add(Dense(8, activation="relu"))
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model.add(Dense(10, activation="softmax"))
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return model
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def get_data():
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digits = load_digits()
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X = digits.data
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y = digits.target
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x = X.astype("float32")
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y_class = to_categorical(y)
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x_train, x_test, y_train, y_test = train_test_split(
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x, y_class, test_size=0.2, random_state=42, shuffle=True
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)
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return x_train, x_test, y_train, y_test
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x_train, x_test, y_train, y_test = get_data()
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model = make_model()
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digits_pso = optimizer(
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model,
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loss="categorical_crossentropy",
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n_particles=300,
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c0=0.5,
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c1=0.3,
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w_min=0.2,
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w_max=0.9,
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negative_swarm=0,
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mutation_swarm=0.1,
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convergence_reset=True,
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convergence_reset_patience=10,
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convergence_reset_monitor="acc",
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convergence_reset_min_delta=0.001,
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)
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digits_pso.fit(
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x_train,
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y_train,
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epochs=500,
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validate_data=(x_test, y_test),
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log=2,
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save_info=True,
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renewal="acc",
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log_name="digits",
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)
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print("Done!")
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sys.exit(0)
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