deb

model/crf.py

@@ -233,7 +233,7 @@ def forward(self, scores, target, current):
             scores: crf scores, of size Word_Seq_len * Batch_size * target_size_from * target_size_to
             targer: golden list, of shape Word_Seq_len * Batch_size
             current: current state, of shape Word_Seq_len * Batch_size
-        output:
+        return:
             loss: Loss
         """
         ins_num = current.size(0)
@@ -254,9 +254,6 @@ class CRFLoss_vb(nn.Module):
     """
 
     def __init__(self, tagset_size, start_tag, end_tag, average_batch=True):
-        """Constructor
-
-        """
         super(CRFLoss_vb, self).__init__()
         self.tagset_size = tagset_size
         self.start_tag = start_tag
@@ -265,16 +262,12 @@ def __init__(self, tagset_size, start_tag, end_tag, average_batch=True):
 
     def forward(self, scores, target, mask):
         """
-        viterbi decode loss, :math:`\frac{ \prod_{j=1}^n \phi(\hat{y}_{j-1}, \hat{y}_j, \mathbf{z}_j) } { \sum_{\mathbf{y}' \in \mathbf{Y}(\mathbf{Z})} \prod_{j=1}^n \phi(y'_{j-1}, y'_j, \mathbf{z}_j)`
-        
-        .. math::
+        viterbi decode loss, 
 
-            \frac{ \prod_{j=1}^n \phi(\hat{y}_{j-1}, \hat{y}_j, \mathbf{z}_j) } { \sum_{\mathbf{y}' \in \mathbf{Y}(\mathbf{Z})} \prod_{j=1}^n \phi(y'_{j-1}, y'_j, \mathbf{z}_j)
-        
         args:
-            scores: crf scores, of size seq_len * bat_size * target_size_from * target_size_to
-            target: golden state, of size seq_len * bat_size * 1
-            mask: mask for padding, of size seq_len * bat_size
+            scores (seq_len, bat_size, target_size_from, target_size_to) : crf scores
+            target (seq_len, bat_size, 1) : golden state
+            mask (size seq_len, bat_size) : mask for padding
         output:
             loss: loss
         """