r编程错误中的py_call_impl（可呼叫，点$ args，dots $ keywords）：value eRror：数据基数模棱两可：x尺寸：13704 y尺寸：5710

Question

我正在尝试使用R编程学习深度学习。但是卡住了这个错误。 py_call_impl中的错误（可呼叫，点$ args，点$关键字）： ValueError：数据基数模棱两可： X尺寸：13704 Y尺寸：5710 确保所有阵列都包含相同数量的样本。

代码：

# Libraries required
install_tensorflow(method = "auto")
library(keras)
library(tensorflow)
library(caret)
library(reticulate)
library(stringr)

data <- fnd2
head(data)
x <- data[,c(2:4)]    
y <- data[,5]       

head(x)
head(y)

train_data_percentage <- 0.75
train_number <- round(nrow(x)*train_data_percentage)  
set.seed(1234)

index <- sample( c(1:nrow(data)), train_number, replace = F )

train_x <- as.matrix(x[index,])
train_y <- as.matrix(y[index])

test_x <- as.matrix(x[-index,])
test_y <- as.matrix(y[-index])

length(train_x); length(test_x); length(train_y); length(test_y)

table(train_y)
table(test_y)

# Padding sequences
train_x <- str_pad(train_x, width = 0, pad = " ")
test_x <- str_pad(test_x, width = 0, pad = " ")

# Model
model <- keras_model_sequential() 
model %>% 
  layer_embedding(input_dim = 500, output_dim = 32) %>%
  layer_simple_rnn(units = 32) %>%  
  layer_dense(units = 1, activation = "sigmoid")

# Compile
model %>% compile(optimizer = "rmsprop",
              loss = "binary_crossentropy",
              metrics = c("acc"))

# Fit model
history <- model %>% fit(train_x, train_y,
                     epochs = 25,
                     batch_size = 128,
                     validation_split = 0.2)

执行拟合模型部分后，此错误弹出。有人可以帮忙吗？谢谢..