3h4 · November 18, 2016 14:45 · Danielv123 · Sep 1, 2018
diff --git a/1-7-loss.py b/1-7-loss.py
 logits_series = [tf.matmul(state, W2) + b2 for state in states_series] #Broadcasted addition
 predictions_series = [tf.nn.softmax(logits) for logits in logits_series]

 losses = [tf.nn.sparse_softmax_cross_entropy_with_logits(logits, labels) for logits, labels in zip(logits_series,labels_series)]
 total_loss = tf.reduce_mean(losses)

 train_step = tf.train.AdagradOptimizer(0.3).minimize(total_loss)
	logits_series = [tf.matmul(state, W2) + b2 for state in states_series] #Broadcasted addition
	predictions_series = [tf.nn.softmax(logits) for logits in logits_series]

	losses = [tf.nn.sparse_softmax_cross_entropy_with_logits(logits, labels) for logits, labels in zip(logits_series,labels_series)]
	total_loss = tf.reduce_mean(losses)

	train_step = tf.train.AdagradOptimizer(0.3).minimize(total_loss)