chainer.links.linearの精度

gistfile1.txt

# encoding: utf-8
from __future__ import division
from __future__ import print_function
import numpy as np
import chainer.links as L
from chainer import cuda

def test_linear():
	np.set_printoptions(precision=32)
	xp = cuda.cupy
	xp = np
	xp.random.seed(0)
	in_size = 10
	out_size = 4
	batchsize = 10
	layer = L.Linear(in_size, out_size)
	if xp is cuda.cupy:
		layer.to_gpu()
	data = xp.random.normal(size=(batchsize, in_size)).astype(xp.float32)
	num_to_take = 1		# xp = npの時にここを1にすると誤差が出る
	out1 = layer(data).data
	out2 = layer(data[:num_to_take]).data
	print("error:", xp.sum((out1[:num_to_take] - out2) ** 2))

if __name__ == "__main__":
	test_linear()