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Brandon Thomas
47022cdeeb
master @ 1ca8b078c12d915bca1f57e822859fa20bd439c8 Date: Tue Oct 15 10:50:12 2019 -0400
18 lines
354 B
Python
18 lines
354 B
Python
import tensorflow as tf
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import os
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import random
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import numpy as np
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def l1_loss(y, y_hat):
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return tf.reduce_mean(tf.abs(y - y_hat))
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def l2_loss(y, y_hat):
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return tf.reduce_mean(tf.square(y - y_hat))
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def cross_entropy_loss(logits, labels):
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return tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits = logits, labels = labels))
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