o Ni @s<ddlZddlZddlmmZGdddejjj Z dS)Ncs@eZdZdZd fdd ZfddZdd Zdd d ZZS)CRFa Conditional Random Field layer (tf.keras) `CRF` can be used as the last layer in a network (as a classifier). Input shape (features) must be equal to the number of classes the CRF can predict (a linear layer is recommended). Args: units: Positive integer, dimensionality of the output space. If it is None, the last dim of input must be num_classes chain_initializer: the initialize method for transitions, default orthogonal. regularizer: Regularizer for crf transitions, can be 'l1', 'l2' or other tensorflow regularizers. Input shape: nD tensor with shape `(batch_size, sentence length, features)` or `(batch_size, sentence length, num_classes)`. Output shape: in training: viterbi_sequence: the predicted sequence tags with shape `(batch_size, sentence length)` inputs: the input tensor of the CRF layer with shape `(batch_size, sentence length, num_classes)` sequence_lengths: true sequence length of inputs with shape `(batch_size)` self.transitions: the internal transition parameters of CRF with shape `(num_classes, num_classes)` in predicting: viterbi_sequence: the predicted sequence tags with shape `(batch_size, sentence length)` Masking This layer supports keras masking for input data with a variable number of timesteps. To introduce masks to your data, use an embedding layer with the `mask_zero` parameter set to `True` or add a Masking Layer before this Layer N orthogonalc srtt|jdi|tjj||_||_d|_ d|_ d|_ tjj |_||_|dur7tjj||_dSdS)NT)superr__init__tfkeras initializersgetchain_initializer regularizer transitionssupports_maskingmaskmetricsAccuracy accuracy_fnunitslayersDensedense)selfrr r kwargs __class__r>/home/ubuntu/.local/lib/python3.10/site-packages/tf2crf/crf.pyr$sz CRF.__init__cs tt|}|ddi|S)Nr r)rr get_configupdate)rconfigrrrr0s zCRF.get_configcCsFt|dksJ|jr|j}n|d}|jd||g|j|jd|_dS)Nr )nameshape initializerr )lenr add_weightr r r )r input_shaperrrrbuild7s z CRF.buildFcCst|durtt|dgdg}t|}tjt|ddd}|jr(||}t j ||j |\}}||||j fS)Nrint32r )axis) rslicer"onesKsumcastrrtfatext crf_decoder )rinputsrtrainingraw_input_shapesequence_lengthsviterbi_sequence_rrrcallDs  zCRF.call)NrN)NF) __name__ __module__ __qualname____doc__rrr'r9 __classcell__rrrrrs   r) tensorflowrtensorflow_addonsr0tensorflow.keras.backendrbackendr-rLayerrrrrrs