Fix non-maxout parser
@@ -117,7 +117,7 @@ cdef class precompute_hiddens:
cached = gpu_cached
self.nF = cached.shape[1]
self.nP = getattr(lower_model, 'nP', 1)
- self.nO = cached.shape[2] // self.nP
+ self.nO = cached.shape[2]
self.ops = lower_model.ops
self.bias = lower_model.b
self._is_synchronized = False
@@ -150,7 +150,7 @@ cdef class precompute_hiddens:
sum_state_features(<float*>state_vector.data,
feat_weights, &ids[0,0],
token_ids.shape[0], self.nF, self.nO*self.nP)
- state_vector += self.bias.ravel()
+ state_vector += self.bias
state_vector, bp_nonlinearity = self._nonlinearity(state_vector)
def backward(d_state_vector, sgd=None):
@@ -164,6 +164,7 @@ cdef class precompute_hiddens:
def _nonlinearity(self, state_vector):
if self.nP == 1:
+ state_vector = state_vector.reshape(state_vector.shape[:-1])
mask = state_vector >= 0.
state_vector *= mask
else:
@@ -171,7 +172,9 @@ cdef class precompute_hiddens:
def backprop_nonlinearity(d_best, sgd=None):
if self.nP == 1:
- return d_best * mask
+ d_best *= mask
+ d_best = d_best.reshape((d_best.shape + (1,)))
+ return d_best
else:
return self.ops.backprop_maxout(d_best, mask, self.nP)
return state_vector, backprop_nonlinearity
