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def feature_template(self, state, sentence): | |
feature_list = np.empty((0), int) | |
stack = state.stack | |
buffer = state.buffer | |
ld = state.ld | |
rd = state.rd | |
form = sentence.form | |
pos = sentence.pos | |
lemma = sentence.lemma | |
morph = sentence.morph |
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def train(self, train_data): | |
print("In trainer...") | |
u= np.zeros(self.weights.shape, dtype=np.int32) | |
q=0 | |
for epoch in range(0,1): | |
correct=0 | |
print("epoch: ",epoch+1) | |
i=0 | |
for data in train_data: | |
q += 1 |
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def generate_tree(self, node): | |
#print(node) | |
if isinstance(self.find(self.copy_table, node)[1], (list,)): | |
item = self.find(self.copy_table, node)[1] | |
item_x = self.find(self.copy_table, node)[2] | |
item_y = self.find(self.copy_table, node)[3] | |
self.copy_table.remove(node) | |
if item_x[0]==0: | |
x=self.copy_table_reversed[item_x[1]] |
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#prod -> right-hand side one element | |
nt -> left-hand side non-terminal | |
count -> true, if prod is in left | |
def create_prod_combinations(prod, nt, count): | |
numset = 1 << count | |
new_prods = [] | |
for i in range(numset): | |
nth_nt = 0 |