mirror of
https://github.com/jung-geun/PSO.git
synced 2025-12-19 20:44:39 +09:00
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(10, 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="loss",
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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="loss",
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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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