def solve_iters(self, data, num_iters=1, batch_size=32):
'''Solves local optimization problem'''
for X, y in batch_data_multiple_iters(data, batch_size, num_iters):
with self.graph.as_default():
self.sess.run(self.train_op, feed_dict={self.features: X, self.labels: y})
soln = self.get_params()
comp = 0
return soln, comp
def solve_iters(self, data, num_iters=1, batch_size=32):
"""
运行指定数量的迭代次数
:param data:
:param num_iters: 当 num_iters = 1 时, 则运行的是标准的 SGD
:param batch_size:
:return:
"""
for X, y in batch_data_multiple_iters(data, batch_size, num_iters):
input_data = process_x(X)
target_data = process_y(y)
with self.graph.as_default():
self.sess.run(self.train_op,
feed_dict={
self.features: input_data,
self.labels: target_data
})
soln = self.get_params()
comp = 0
return soln, comp
