sequential_model_input_layer

sequential_model_input_layer(
  input_shape = NULL,
  batch_size = NULL,
  dtype = NULL,
  input_tensor = NULL,
  sparse = NULL,
  name = NULL,
  ragged = NULL,
  type_spec = NULL,
  ...,
  input_layer_name = NULL
)

Arguments

input_shape

an integer vector of dimensions (not including the batch axis), or a tf$TensorShape instance (also not including the batch axis).

batch_size

Optional input batch size (integer or NULL).

dtype

Optional datatype of the input. When not provided, the Keras default float type will be used.

input_tensor

Optional tensor to use as layer input. If set, the layer will use the tf$TypeSpec of this tensor rather than creating a new placeholder tensor.

sparse

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

ragged

Boolean, whether the placeholder created is meant to be ragged. In this case, values of 'NULL' in the 'shape' argument represent ragged dimensions. For more information about RaggedTensors, see this guide. Default to FALSE.

type_spec

A tf$TypeSpec object to create Input from. This tf$TypeSpec represents the entire batch. When provided, all other args except name must be NULL.

...

additional arguments passed on to keras$layers$InputLayer.

input_layer_name, name

Optional name of the input layer (string).