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import tensorflow

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jakubknczny 2021-05-15 19:01:47 +02:00
parent 692cfe336b
commit db7a59f689
1 changed files with 6 additions and 6 deletions
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12
lab5/train/train.py
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@ -1,7 +1,7 @@
import numpy as np import numpy as np
import pandas as pd import pandas as pd
import sys import sys
import tensorflow as tf import tensorflow
from tensorflow.keras import layers from tensorflow.keras import layers
X_train = pd.read_csv('train.csv') X_train = pd.read_csv('train.csv')
@ -17,7 +17,7 @@ Y_test = pd.get_dummies(Y_test)
Y_valid = X_valid.pop('stabf') Y_valid = X_valid.pop('stabf')
Y_valid = pd.get_dummies(Y_valid) Y_valid = pd.get_dummies(Y_valid)
model = tf.keras.Sequential([ model = tensorflow.keras.Sequential([
layers.Input(shape=(12,)), layers.Input(shape=(12,)),
layers.Dense(32), layers.Dense(32),
layers.Dense(16), layers.Dense(16),
@ -25,12 +25,12 @@ model = tf.keras.Sequential([
]) ])
model.compile( model.compile(
loss=tf.keras.losses.BinaryCrossentropy(), loss=tensorflow.keras.losses.BinaryCrossentropy(),
optimizer=tf.keras.optimizers.Adam(lr=float(sys.argv[1])), optimizer=tensorflow.keras.optimizers.Adam(lr=float(sys.argv[1])),
metrics=[tf.keras.metrics.BinaryAccuracy()]) metrics=[tensorflow.keras.metrics.BinaryAccuracy()])
history = model.fit(tf.convert_to_tensor(X_train, np.float32), history = model.fit(tensorflow.convert_to_tensor(X_train, np.float32),
Y_train, epochs=2, validation_data=(X_valid, Y_valid)) Y_train, epochs=2, validation_data=(X_valid, Y_valid))
model.save('grid-stability-dense.h5') model.save('grid-stability-dense.h5')