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Spelling errors (#6232)

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Mohanson 2017-04-13 13:10:15 +08:00 committed by François Chollet
parent 9eb7ecd3e5
commit 5bd3976e79
1 changed files with 6 additions and 6 deletions
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12
examples/addition_rnn.py
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@ -78,7 +78,7 @@ INVERT = True
# Maximum length of input is 'int + int' (e.g., '345+678'). Maximum length of
# int is DIGITS.
MAxLEN = DIGITS + 1 + DIGITS
MAXLEN = DIGITS + 1 + DIGITS
# All the numbers, plus sign and space for padding.
chars = '0123456789+ '
@ -98,9 +98,9 @@ while len(questions) < TRAINING_SIZE:
if key in seen:
continue
seen.add(key)
# Pad the data with spaces such that it is always MAxLEN.
# Pad the data with spaces such that it is always MAXLEN.
q = '{}+{}'.format(a, b)
query = q + ' ' * (MAxLEN - len(q))
query = q + ' ' * (MAXLEN - len(q))
ans = str(a + b)
# Answers can be of maximum size DIGITS + 1.
ans += ' ' * (DIGITS + 1 - len(ans))
@ -113,10 +113,10 @@ while len(questions) < TRAINING_SIZE:
print('Total addition questions:', len(questions))
print('Vectorization...')
x = np.zeros((len(questions), MAxLEN, len(chars)), dtype=np.bool)
x = np.zeros((len(questions), MAXLEN, len(chars)), dtype=np.bool)
y = np.zeros((len(questions), DIGITS + 1, len(chars)), dtype=np.bool)
for i, sentence in enumerate(questions):
x[i] = ctable.encode(sentence, MAxLEN)
x[i] = ctable.encode(sentence, MAXLEN)
for i, sentence in enumerate(expected):
y[i] = ctable.encode(sentence, DIGITS + 1)
@ -151,7 +151,7 @@ model = Sequential()
# "Encode" the input sequence using an RNN, producing an output of HIDDEN_SIZE.
# Note: In a situation where your input sequences have a variable length,
# use input_shape=(None, num_feature).
model.add(RNN(HIDDEN_SIZE, input_shape=(MAxLEN, len(chars))))
model.add(RNN(HIDDEN_SIZE, input_shape=(MAXLEN, len(chars))))
# As the decoder RNN's input, repeatedly provide with the last hidden state of
# RNN for each time step. Repeat 'DIGITS + 1' times as that's the maximum
# length of output, e.g., when DIGITS=3, max output is 999+999=1998.