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).

See also

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