tf.layers.dense
tf.layers.dense
tf.layers.dense
dense( inputs, units, activation=None, use_bias=True, kernel_initializer=None, bias_initializer=tf.zeros_initializer(), kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, trainable=True, name=None, reuse=None )
Defined in tensorflow/python/layers/core.py
.
Functional interface for the densely-connected layer.
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
).
Note: if theinputs
tensor has a rank greater than 2, then it is flattened prior to the initial matrix multiply bykernel
.
Arguments:
-
inputs
: Tensor input. -
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. -
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. -
trainable
: Boolean, ifTrue
also add variables to the graph collectionGraphKeys.TRAINABLE_VARIABLES
(seetf.Variable
). -
name
: String, the name of the layer. -
reuse
: Boolean, whether to reuse the weights of a previous layer by the same name.
Returns:
Output tensor.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/layers/dense