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,
ragged = FALSE
)

## Arguments

shape Shape, not including the batch size. For instance, shape=c(32) indicates that the expected input will be batches of 32-dimensional vectors. 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. 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 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.

## Value

A tensor

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()