sequential_model_input_layer: sequential_model_input_layer

In keras: R Interface to 'Keras'

sequential_model_input_layer

Description

sequential_model_input_layer

Usage

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).

keras documentation built on Dec. 28, 2022, 2:20 a.m.