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)

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.

batch_shape

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.

name

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.

dtype

The data type expected by the input, as a string (float32, float64, int32...)

sparse

Boolean, whether the placeholder created is meant to be sparse.

tensor

Existing tensor to wrap into the Input layer. If set, the layer will not create a placeholder tensor.

Value

A tensor

Details

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