TF 2.0 is out! Get hands-on practice at TF World, Oct 28-31. Use code TF20 for 20% off select passes. Register now

tf.layers.Dense

View source on GitHub

Class Dense

Densely-connected layer class.

Inherits From: Dense, Layer

Aliases:

  • Class tf.compat.v1.layers.Dense

This layer implements the operation: outputs = activation(inputs * kernel + bias) Where activation is the activation function passed as the activation argument (if not None), kernel is a weights matrix created by the layer, and bias is a bias vector created by the layer (only if use_bias is True).

Arguments:

  • units: Integer or Long, dimensionality of the output space.
  • activation: Activation function (callable). Set it to None to maintain a linear activation.
  • use_bias: Boolean, whether the layer uses a bias.
  • kernel_initializer: Initializer function for the weight matrix. If None (default), weights are initialized using the default initializer used by tf.compat.v1.get_variable.
  • bias_initializer: Initializer function for the bias.
  • kernel_regularizer: Regularizer function for the weight matrix.
  • bias_regularizer: Regularizer function for the bias.
  • activity_regularizer: Regularizer function for the output.
  • kernel_constraint: An optional projection function to be applied to the kernel after being updated by an Optimizer (e.g. used to implement norm constraints or value constraints for layer weights). The function must take as input the unprojected variable and must return the projected variable (which must have the same shape). Constraints are not safe to use when doing asynchronous distributed training.
  • bias_constraint: An optional projection function to be applied to the bias after being updated by an Optimizer.
  • trainable: Boolean, if True also add variables to the graph collection GraphKeys.TRAINABLE_VARIABLES (see tf.Variable).
  • name: String, the name of the layer. Layers with the same name will share weights, but to avoid mistakes we require reuse=True in such cases.
  • _reuse: Boolean, whether to reuse the weights of a previous layer by the same name.

Properties:

  • units: Python integer, dimensionality of the output space.
  • activation: Activation function (callable).
  • use_bias: Boolean, whether the layer uses a bias.
  • kernel_initializer: Initializer instance (or name) for the kernel matrix.
  • bias_initializer: Initializer instance (or name) for the bias.
  • kernel_regularizer: Regularizer instance for the kernel matrix (callable)
  • bias_regularizer: Regularizer instance for the bias (callable).
  • activity_regularizer: Regularizer instance for the output (callable)
  • kernel_constraint: Constraint function for the kernel matrix.
  • bias_constraint: Constraint function for the bias.
  • kernel: Weight matrix (TensorFlow variable or tensor).
  • bias: Bias vector, if applicable (TensorFlow variable or tensor).

__init__

View source

__init__(
    units,
    activation=None,
    use_bias=True,
    kernel_initializer=None,
    bias_initializer=tf.zeros_initializer(),
    kernel_regularizer=None,
    bias_regularizer=None,
    activity_regularizer=None,
    kernel_constraint=None,
    bias_constraint=None,
    trainable=True,
    name=None,
    **kwargs
)

Properties

graph

DEPRECATED FUNCTION

scope_name