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cost.rst

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API - Cost

To make TensorLayer simple, we minimize the number of cost functions as much as we can. So we encourage you to use TensorFlow's function, , see TensorFlow API.

Note

Please refer to Getting Started for getting specific weights for weight regularization.

.. automodule:: tensorlayer.cost


.. autosummary::

   cross_entropy
   sigmoid_cross_entropy
   binary_cross_entropy
   mean_squared_error
   normalized_mean_square_error
   absolute_difference_error
   dice_coe
   dice_hard_coe
   iou_coe
   cross_entropy_seq
   cross_entropy_seq_with_mask
   cosine_similarity
   li_regularizer
   lo_regularizer
   maxnorm_regularizer
   maxnorm_o_regularizer
   maxnorm_i_regularizer
   huber_loss

Softmax cross entropy

.. autofunction:: cross_entropy

Sigmoid cross entropy

.. autofunction:: sigmoid_cross_entropy

Binary cross entropy

.. autofunction:: binary_cross_entropy

Mean squared error (L2)

.. autofunction:: mean_squared_error

Normalized mean square error

.. autofunction:: normalized_mean_square_error

Absolute difference error (L1)

.. autofunction:: absolute_difference_error

Dice coefficient

.. autofunction:: dice_coe

Hard Dice coefficient

.. autofunction:: dice_hard_coe

IOU coefficient

.. autofunction:: iou_coe

Cross entropy for sequence

.. autofunction:: cross_entropy_seq

Cross entropy with mask for sequence

.. autofunction:: cross_entropy_seq_with_mask

Cosine similarity

.. autofunction:: cosine_similarity

Regularization functions

For tf.nn.l2_loss, tf.contrib.layers.l1_regularizer, tf.contrib.layers.l2_regularizer and tf.contrib.layers.sum_regularizer, see tensorflow API. Maxnorm ^^^^^^^^^^ .. autofunction:: maxnorm_regularizer

Special

.. autofunction:: li_regularizer

.. autofunction:: lo_regularizer

.. autofunction:: maxnorm_o_regularizer

.. autofunction:: maxnorm_i_regularizer

Huber Loss

.. autofunction:: huber_loss