theanets.losses.Loss¶
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class
theanets.losses.
Loss
(target, weight=1.0, weighted=False, output_name='out')¶ A loss function base class.
Parameters: target : int or Theano variable
If this is an integer, it specifies the number of dimensions required to store the target values for computing the loss. If it is a Theano variable, this variable will be used directly to access target values.
weight : float, optional
The importance of this loss for the model being trained. Defaults to 1.
weighted : bool, optional
If True, a floating-point array of weights with the same dimensions as
target
will be required to compute the “weighted” loss. Defaults to False.output_name : str, optional
Name of the network output to tap for computing the loss. Defaults to ‘out:out’, the name of the default output of the last layer in a linear network.
Attributes
weight (float) The importance of this loss for the model being trained. output_name (str) Name of the network output to tap for computing the loss. -
__init__
(target, weight=1.0, weighted=False, output_name='out')¶
Methods
__init__
(target[, weight, weighted, output_name])log
()Log some diagnostic info about this loss. Attributes
variables
A list of Theano variables used in this loss. -
log
()¶ Log some diagnostic info about this loss.
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variables
¶ A list of Theano variables used in this loss.
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