38 lines
891 B
Python
38 lines
891 B
Python
#!/usr/bin/env python3.6
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"""import os
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os.environ["PYTHONIOENCODING"] =""" "utf-8"
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import io
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import sys
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sys.stdout = io.open(sys.stdout.fileno(), 'w', encoding='utf8')
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import keras
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with io.open("Raps randoms.txt","r",encoding="utf8") as file:
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text=file.read()#.decode("utf8")
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print(type(file))
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print(type(text))
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print(text)
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"""
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data=[]
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(x_train,y_train),(x_test,y_test)=mnist.load_data()
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x_train
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x_train=tf.keras.utils.normalize(x_train,axis=1)
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x_test=tf.keras.utils.normalize(x_test,axis=1)
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model=tf.keras.models.Sequential()
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model.add(tf.keras.layers.Flatten())
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for i in range(4):
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model.add(tf.keras.layers.Dense(128,activation=tf.nn.relu))
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model.add(tf.keras.layers.Dense(10,activation=tf.nn.softmax))
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model.compile(optimizer="adam",
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loss="sparse_categorical_crossentropy",
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metrics=["accuracy"])
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model.fit(x_train,y_train,epochs=3)
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"""
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