Question

我正在尝试执行以下示例：https://keras.rstudio.com/articles/examples/imdb_lstm.html

library(keras)

max_features <- 20000
batch_size <- 32

# Cut texts after this number of words (among top max_features most common words)
maxlen <- 80  

cat('Loading data...\n')
imdb <- dataset_imdb(num_words = max_features)
x_train <- imdb$train$x
y_train <- imdb$train$y
x_test <- imdb$test$x
y_test <- imdb$test$y

cat(length(x_train), 'train sequences\n')
cat(length(x_test), 'test sequences\n')

cat('Pad sequences (samples x time)\n')
x_train <- pad_sequences(x_train, maxlen = maxlen)
x_test <- pad_sequences(x_test, maxlen = maxlen)
cat('x_train shape:', dim(x_train), '\n')
cat('x_test shape:', dim(x_test), '\n')

cat('Build model...\n')
model <- keras_model_sequential()
model %>%
  layer_embedding(input_dim = max_features, output_dim = 128) %>% 
  layer_lstm(units = 64, dropout = 0.2, recurrent_dropout = 0.2) %>% 
  layer_dense(units = 1, activation = 'sigmoid')

# Try using different optimizers and different optimizer configs
model %>% compile(
  loss = 'binary_crossentropy',
  optimizer = 'adam',
  metrics = c('accuracy')
)

cat('Train...\n')
model %>% fit(
  x_train, y_train,
  batch_size = batch_size,
  epochs = 15,
  validation_data = list(x_test, y_test)
)

scores <- model %>% evaluate(
  x_test, y_test,
  batch_size = batch_size
)

cat('Test score:', scores[[1]])
cat('Test accuracy', scores[[2]])

但对以下行进行了小的更改：

layer_lstm(units = 64, dropout = 0.2, return_sequences = T, recurrent_dropout = 0.2)

我制作了return_sequences= TRUE，因为我希望在每个时期查看隐藏的状态值。

您能帮我解决错误吗？

检查目标时出错：预期密度为3维，但阵列的形状为（25000，1）

0 个答案: