neupy.layers.Input

class neupy.layers.Input[source]

Input layer defines input’s feature shape.

Parameters:
size : int, tuple or None

Identifies input’s feature shape.

name : str or None

Layer’s identifier. If name is equal to None than name will be generated automatically. Defaults to None.

Examples

>>> from neupy import layers
>>> input_layer = layers.Input(10)
>>> input_layer
Input(10)
Attributes:
input_shape : tuple

Returns layer’s input shape in the form of a tuple. Shape will not include batch size dimension.

output_shape : tuple

Returns layer’s output shape in the form of a tuple. Shape will not include batch size dimension.

training_state : bool

Defines whether layer in training state or not. Training state will enable some operations inside of the layers that won’t work otherwise.

parameters : dict

Parameters that networks uses during propagation. It might include trainable and non-trainable parameters.

graph : LayerGraph instance

Graphs that stores all relations between layers.

Methods

disable_training_state() Context manager that switches off trainig state.
initialize() Set up important configurations related to the layer.
options = {'name': Option(class_name='BaseLayer', value=Property(name="name")), 'size': Option(class_name='Input', value=ArrayShapeProperty(name="size"))}[source]
size = None[source]