import math
import pprint
import torch
import torch.nn as nn
import torch.nn.functional as F
from pcfg import PCFG
def p(s):
print(s)
return s
gen_a = lambda terminals_per_category: PCFG.fromstring(
" A -> " + " | ".join([
"\"a" + str(i) + "\" [" + str(1 / terminals_per_category) + "]"
for i in range(terminals_per_category)
]))
generate_test_grammar = lambda p1, terminals_per_category: PCFG.fromstring(
" S -> NP-s VP-s [" + str((1 - p1) / 2) + "] | NP-s S VP-s [" + str(
p1 / 2) + "] | NP-p VP-p [" + str(
(1 - p1) / 2) + "] | NP-p S VP-p [" + str(p1 / 2) + "]\n" +
" NP-s -> N-s [" + str(1) + "]\n" + " NP-p -> N-p [" + str(1) +
"]\n" + " VP-s -> V-s [" + str(1) + "]\n" + " VP-p -> V-p [" + str(
1) + "]\n" + " N-s -> " + " | ".join([
"\"n" + str(i) + "-s\" [" + str(1 / terminals_per_category) + "]"
for i in range(terminals_per_category)
]) + "\n" + " N-p -> " + " | ".join([
"\"n" + str(i) + "-p\" [" + str(1 / terminals_per_category) + "]"
for i in range(terminals_per_category)
from typing import TextIO
from pcfg import PCFG
import os
BASEPATH: str = os.path.dirname(__file__)
f: TextIO
with open(os.path.join(BASEPATH, "subject_adjectives.txt")) as f:
subject_adjectives: PCFG = PCFG.fromstring(f.read())
n: int = int(input("How many sentences do you want generated? "))
sentence: str
for sentence in subject_adjectives.generate(n):
print()
print(sentence.capitalize())
