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xunge/deep_feedforward_networks_02.py

Last active July 3, 2019 01:39
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线性回归的训练过程
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deep_feedforward_networks_02.py
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for i in range(1000):
for j in range(4):
sess.run(train, feed_dict={x: np.expand_dims(X[j], 0), y: np.expand_dims(Y[j], 0)})
loss_ = sess.run(loss, feed_dict={x: X, y: Y})
print("step: %d, loss: %.3f" % (i, loss_))
print("X: %r" % X)
print("pred: %r" % sess.run(out, feed_dict={x: X}))
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