A Keras tensor is a symbolic tensor-like object, which we augment with certain attributes that allow us to build a Keras model just by knowing the inputs and outputs of the model.
For instance, if a, b and c are Keras tensors,
it becomes possible to do:
model <- keras_model(input = c(a, b), output = c)
Usage
keras_input(
  shape = NULL,
  batch_size = NULL,
  dtype = NULL,
  sparse = NULL,
  ragged = NULL,
  batch_shape = NULL,
  name = NULL,
  tensor = NULL,
  optional = FALSE
)Arguments
- shape
- A shape list (list of integers or - NULLobjects), not including the batch size. For instance,- shape = c(32)indicates that the expected input will be batches of 32-dimensional vectors. Elements of this list can be- NULLor- NA;- NULL/- NAelements represent dimensions where the shape is not known and may vary (e.g. sequence length).
- batch_size
- Optional static batch size (integer). 
- dtype
- The data type expected by the input, as a string (e.g. - "float32",- "int32"...)
- sparse
- A boolean specifying whether the expected input will be sparse tensors. Note that, if - sparseis- FALSE, sparse tensors can still be passed into the input - they will be densified with a default value of 0. This feature is only supported with the TensorFlow backend. Defaults to- FALSE.
- ragged
- A boolean specifying whether the expected input will be ragged tensors. Note that, if - raggedis- FALSE, ragged tensors can still be passed into the input - they will be densified with a default value of 0. This feature is only supported with the TensorFlow backend. Defaults to- FALSE.
- batch_shape
- Optional shape list (list of integers or - NULLobjects), including the batch size.
- name
- 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. 
- tensor
- Optional existing tensor to wrap into the - Inputlayer. If set, the layer will use this tensor rather than creating a new placeholder tensor.
- optional
- Boolean, whether the input is optional or not. An optional input can accept - NULLvalues.
Value
A Keras tensor,
which can passed to the inputs argument of (keras_model()).
Examples
# This is a logistic regression in Keras
input <- layer_input(shape=c(32))
output <- input |> layer_dense(16, activation='softmax')
model <- keras_model(input, output)See also
Other model creation: keras_model() keras_model_sequential()