Input layer


Layer to be used as an entry point into a graph.


  shape = NULL, 
  batch_shape = NULL, 
  name = NULL, 
  dtype = NULL, 
  sparse = FALSE, 
  tensor = NULL, 
  ragged = FALSE 


Arguments Description
shape Shape, not including the batch size. For instance, shape=c(32) indicates that the expected input will be batches of 32-dimensional vectors.
batch_shape Shape, including the batch size. For instance, shape = c(10,32) indicates that the expected input will be batches of 10 32-dimensional vectors. batch_shape = list(NULL, 32) indicates batches of an arbitrary number of 32-dimensional vectors.
name An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn’t provided.
dtype The data type expected by the input, as a string (float32, float64, int32…)
sparse Boolean, whether the placeholder created is meant to be sparse.
tensor Existing tensor to wrap into the Input layer. If set, the layer will not create a placeholder tensor.
ragged A boolean specifying whether the placeholder to be created is ragged. Only one of ‘ragged’ and ‘sparse’ can be TRUE In this case, values of ‘NULL’ in the ‘shape’ argument represent ragged dimensions.


A tensor

See Also

Other core layers: layer_activation(), layer_activity_regularization(), layer_attention(), layer_dense_features(), layer_dense(), layer_dropout(), layer_flatten(), layer_lambda(), layer_masking(), layer_permute(), layer_repeat_vector(), layer_reshape()