ValueError: in user code while using keras model in R

I am trying to run 1 dimensional CNN in R using keras package. I am using the following code

library(MASS)
library(keras)

##Create some data
data("Boston")
data <- Boston
# create a list of 70% of the rows in the original dataset we can use for training
set.seed(123)
training <- sample(nrow(data), 0.7 * nrow(data))

dataTrain <- data[training,]
dataTest <- data[-training,]

dataTrain_y <- as.matrix(dataTrain$medv)
dataTrain_x <- as.matrix(subset(dataTrain, select = -c(medv)))

dataTest_y <- as.matrix(dataTest$medv)
dataTest_x <- as.matrix(subset(dataTest, select = -c(medv)))

#Reshaping the data for CNN
dataTrain_x <- array_reshape(dataTrain_x, c(ncol(dataTrain_x), nrow(dataTrain_x), 1))
dataTest_x <- array_reshape(dataTest_x, c(ncol(dataTest_x), nrow(dataTest_x), 1))

#CNN model
model <- keras_model_sequential() %>%
  layer_conv_1d(filters=32, kernel_size=4, activation="relu", 
                input_shape=c(ncol(dataTrain_x), nrow(dataTrain_x))) %>%
  layer_max_pooling_1d(pool_size=2) %>%
  layer_conv_1d(filters=64, kernel_size=2, activation="relu") %>%
  layer_max_pooling_1d(pool_size=2) %>%
  layer_dropout(rate=0.4) %>%
  layer_flatten() %>%
  layer_dense(units=100, activation="relu") %>%
  layer_dropout(rate=0.2) %>%
  layer_dense(units=1, activation="linear")

model %>% compile(
  loss = "mse",
  optimizer =  "adam", #'sgd' can also be used
  metrics = list("mean_absolute_error")
)

model %>% summary()

history <- model %>% fit(dataTrain_x, dataTrain_y, 
                         epochs = 100, batch_size = 50, 
                         #callbacks = callback_tensorboard("logs/run_a"),
                         validation_split = 0.2)

But it returns me the following error

Error in py_call_impl(callable, dots$args, dots$keywords) : ValueError: in user code: C:\Python37\lib\site-packages\tensorflow\python\keras\engine\training.py:805 train_function * return step_function(self, iterator) C:\Python37\lib\site-packages\tensorflow\python\keras\engine\training.py:795 step_function ** outputs = model.distribute_strategy.run(run_step, args=(data,)) C:\Python37\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1259 run return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs) C:\Python37\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2730 call_for_each_replica return self._call_for_each_replica(fn, args, kwargs) C:\Python37\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:3417 _call_for_each_replica return fn(*args, **kwargs) C:\Python37\lib\site-packages\tensorflow\python\keras\engine\training.py:788 run_step ** outputs = model.train_step(data) C:\Python37\lib\site-pac

Now how can I solve this error?

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