ccbaf353bcd6121c50b4de0965177480b8f6eb48,adding_problem_100/rwa_model/train.py,,,#,25

Before Change

	q_greater = tf.maximum(q, 0.0)	// Greater of the exponent term or zero
	scale = tf.exp(-q_greater)
	a_scale = tf.exp(q-q_greater)

	n = tf.mul(n, scale)+tf.mul(tf.mul(u, tf.nn.tanh(g)), a_scale)	// Numerically stable update of numerator
	d = tf.mul(d, scale)+a_scale	// Numerically stable update of denominator
	h_new = activation(tf.div(n, d))

After Change

// Define model
//
error = tf.zeros([batch_size])
h += activation(tf.expand_dims(s, 0))

for i in range(max_steps):

Instances