//目录

填充与步幅

padding & stride

from mxnet import autograd,nd
from mxnet import gluon,init
from mxnet.gluon import nn,loss as gloss
from mxnet.gluon import data as gdata

def comp_conv2d(conv2d,X):
    conv2d.initialize()
    # (样本,通道,高,宽)
    X = X.reshape((1,1)+X.shape)
    #print(X.shape)
    Y = conv2d(X)
    return Y

conv2d = nn.Conv2D(1,kernel_size=(3,3),padding=1)
X = nd.random.uniform(shape=(8,8))
#print(X)
#print(comp_conv2d(conv2d,X).shape)

conv2d = nn.Conv2D(1,kernel_size=(5,3),padding=(2,1))
#print(comp_conv2d(conv2d,X).shape)

conv2d = nn.Conv2D(1,kernel_size=3,padding=1,strides=2)
print(comp_conv2d(conv2d,X).shape)

conv2d = nn.Conv2D(1,kernel_size=(3,5),padding=(0,1),strides=(3,4))
print(comp_conv2d(conv2d,X).shape)

 

posted @ 2018-11-29 14:33  小草的大树梦  阅读(202)  评论(0编辑  收藏  举报