layer_input()
is an alias for keras_input()
.
See ?
keras_input()
for the full documentation.
Usage
layer_input(
shape = NULL,
batch_size = NULL,
dtype = NULL,
sparse = NULL,
batch_shape = NULL,
name = NULL,
tensor = NULL,
optional = FALSE
)
Arguments
- shape
A shape list (list of integers or
NULL
objects), 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 beNULL
orNA
;NULL
/NA
elements 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
sparse
isFALSE
, 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 toFALSE
.- batch_shape
Optional shape list (list of integers or
NULL
objects), 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
Input
layer. 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
NULL
values.
Value
A Keras tensor,
which can passed to the inputs
argument of (keras_model()
).