Dense

neuralpy.layers.linear.Dense(n_nodes, n_inputs=None, bias=True, name=None)

info

Dense Layer is mostly stable and can be used for any project. In the future, any chance of breaking changes is very low.

A Dense layer is a densely connected Neural Network layer. It performs a linear transformation of the input.

To learn more about Dense layers, please check pytorch documentation for it.

Supported Arguments

• n_nodes: (Integer) Size of the output sample
• n_inputs=None: (Integer) Size of the input sample, no need for this argument layers except the initial layer
• bias=True: (Boolean) If true then uses the bias
• name=None: (String) Name of the layer, if not provided then automatically calculates a unique name for the layer

Example Code

from neuralpy.models import Sequential

from neuralpy.layers.linear import Dense

# Making the model

model = Sequential()

model.add(Dense(n_nodes=256, n_inputs=28, bias=True, name="Input Layer"))

model.add(Dense(n_nodes=512, bias=True, name="Hidden Layer 1"))

model.add(Dense(n_nodes=10, bias=True, name="Output Layer"))