Layer to be used as an entry point into a graph.
layer_input(shape = NULL, batch_shape = NULL, name = NULL, dtype = NULL,
sparse = FALSE, tensor = NULL)Shape, not including the batch size. For instance,
shape=c(32) indicates that the expected input will be batches
of 32-dimensional vectors.
Shapes, including the batch size. For instance,
batch_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.
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.
The data type expected by the input, as a string (float32,
float64, int32...)
Boolean, whether the placeholder created is meant to be sparse.
Existing tensor to wrap into the Input layer. If set, the
layer will not create a placeholder tensor.
A tensor
It can either wrap an existing tensor (pass an input_tensor
argument) or create its a placeholder tensor (pass arguments input_shape
or batch_input_shape as well as input_dtype).
Other core layers: layer_activation,
layer_activity_regularization,
layer_dense, layer_dropout,
layer_flatten, layer_lambda,
layer_masking, layer_permute,
layer_repeat_vector,
layer_reshape