if __name__ == '__main__':
itokens = TokenList(list('0123456789'))
otokens = TokenList(list('0123456789abcdefx'))
def GenSample():
x = random.randint(0, 99999)
y = hex(x); x = str(x)
return x, y
X, Y = [], []
for _ in range(100000):
x, y = GenSample()
X.append(list(x))
Y.append(list(y))
X, Y = pad_to_longest(X, itokens), pad_to_longest(Y, otokens)
print(X.shape, Y.shape)
s2s = Transformer(itokens, otokens, 10, 15)
lr_scheduler = LRSchedulerPerStep(256, 4000)
s2s.compile('adam')
s2s.model.summary()
class TestCallback(Callback):
def on_epoch_end(self, epoch, logs = None):
print('\n')
for test in [123, 13245, 33467]:
ret = s2s.decode_sequence(str(test))
print(test, ret, hex(test))
print('\n')
x1 = random.randint(0, 99999)
x2 = random.randint(0, 99999)
x2 = str(x2)
y = hex(x1);
x1 = str(x1)
return x1, x2, y
X1, X2, Y = [], [], []
for _ in range(100000):
x1, x2, y = GenSample()
X1.append(list(x1))
X2.append(list(x1))
Y.append(list(y))
X1, X2, Y = pad_to_longest(X1, itokens1), pad_to_longest(X2, itokens2), pad_to_longest(Y, otokens)
print(X1.shape, X2.shape, Y.shape)
s2s = Transformer(itokens1, itokens2, otokens, 10, 15)
lr_scheduler = LRSchedulerPerStep(256, 4000)
s2s.compile('adam')
s2s.model.summary()
class TestCallback(Callback):
def on_epoch_end(self, epoch, logs=None):
print('\n')
for test in [123, 13245, 33467]:
ret = s2s.decode_sequence(str(test))
print(test, ret, hex(test))
print('\n')