我有一段代码应该构建一个带有 5 个滞后变量的 RNN 模型，用于观察时间序列数据。这是代码：
library(Quandl)
key<-"*******************"
Quandl.api_key(key)
sh_stock_ex <- Quandl("YAHOO/SS_600292", type="xts")
library(xts)
data <- scale(sh_stock_ex[-1,5])
feat <- merge(na.trim(lag(data,1)), na.trim(lag(data,2)), na.trim(lag(data,3)), na.trim(lag(data,4)),
na.trim(lag(data,5)), all=FALSE)
dataset <- merge(feat, data, all = FALSE)
colnames(dataset) <- c("lag.1", "lag.2","lag.3","lag.4","lag.5", "obj")
index <- 1:4000
training <- as.data.frame(dataset[index,])
testing <- as.data.frame(dataset[-index,])
library(mxnet)
train.x <- data.matrix(training[,-6])
train.y <- training[,6]
test.x <- data.matrix(testing[,-6])
test.y <- testing[,6]
get.label <- function(X) {
label <- array(0, dim=dim(X))
d <- dim(X)[1]
w <- dim(X)[2]
for (i in 0:(w-1)) {
for (j in 1:d) {
label[i*d+j] <- X[(i*d+j)%%(w*d)+1]
}
}
return (label)
}
X.train.label <- get.label(t(train.x))
X.val.label <- get.label(t(test.x))
X.train <- list(data=t(train.x), label=X.train.label)
X.val <- list(data=t(test.x), label=X.val.label)
#X.train <- list(data=t(train.x), label=X.train.label)
#X.val <- list(data=t(test.x), label=X.val.label)
batch.size = 5
seq.len = 5
num.hidden = 3
num.embed = 3
num.rnn.layer = 1
num.lstm.layer = 1
num.round = 1
update.period = 1
learning.rate= 0.1
wd=0.00001
clip_gradient=1
mx.set.seed(0)
model <- mx.rnn(X.train, X.val, num.rnn.layer=num.rnn.layer, seq.len=seq.len, num.hidden=num.hidden,
num.embed=num.embed, num.label=5, batch.size=batch.size, input.size=5, ctx = mx.cpu(),
num.round = num.round, update.period = update.period, initializer = mx.init.uniform(0.01),
dropout = 0, optimizer = "sgd", batch.norm = FALSE,
learning.rate=learning.rate, wd=wd, clip_gradient=clip_gradient)
#preds = predict(model,t(test.x))
mx.rnn.inference(num.rnn.layer = num.rnn.layer,input.size = 5,num.hidden = num.hidden,
num.embed = num.embed,num.label = 5,batch.size = batch.size,ctx = mx.cpu(),
dropout = 0,batch.norm = FALSE,arg.params = model$arg.params)
在调用 mx.rnn 时会引发以下错误：
[15:36:29] src/operator/./reshape-inl.h:311: Using target_shape will be deprecated.
[15:36:29] src/operator/./reshape-inl.h:311: Using target_shape will be deprecated.
[15:36:29] src/operator/./reshape-inl.h:311: Using target_shape will be deprecated.
[15:36:29] src/operator/./reshape-inl.h:311: Using target_shape will be deprecated.
[15:36:29] C:/Users/qkou/mxnet/dmlc-core/include/dmlc/logging.h:235: [15:36:29] src/ndarray/ndarray.cc:231: Check failed: from.shape() == to->shape() operands shape mismatch
Error in exec$update.arg.arrays(arg.arrays, match.name, skip.null) :
[15:36:29] src/ndarray/ndarray.cc:231: Check failed: from.shape() == to->shape() operands shape mismatch
是不是我每次都得到这个。在此代码实际运行之前运行了几次。你能帮我弄清楚发生了什么吗？