tf layer with keras

library(tfestimators)
library(keras)
latitude_buckets <- list(33.641336, 33.887157, 99)
latitude_fc <- column_bucketized(column_numeric('latitude'), latitude_buckets)
longitude_buckets <- list(-84.558798, -84.287259, 99)
longitude_fc <- column_bucketized(column_numeric('longitude'), longitude_buckets)
boxed_fc <- column_crossed(c(latitude_fc, longitude_fc), hash_bucket_size = 1000)

features <- reticulate::dict(list(
  latitude = tf$placeholder(tf$float32, shape = list(NULL, 1L)),
  longitude = tf$placeholder(tf$float32, shape = list(NULL, 1L))
))

tf_input_layer <- input_layer(features, column_indicator(boxed_fc))
model <- keras_model_sequential()
model$add(tf$keras$layers$InputLayer(input_tensor = tf_input_layer))
model
# Model
# _______________________________________________________________
# Layer (type)                Output Shape             Param #
# ===============================================================
#   input_7 (InputLayer)        (None, 1000)             0
# ===============================================================
#   Total params: 0
# Trainable params: 0
# Non-trainable params: 0
# _______________________________________________________________