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Update lstm_seq2seq.py(from 22% to 87% acc) #13269

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Merged
merged 3 commits into from
Sep 11, 2019
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Update lstm_seq2seq.py(from 22% to 87% acc) #13269

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c846308
#13266 Update lstm_seq2seq.py(from 22% to 87% acc)
tykimos Aug 30, 2019
aa65ae7
Update lstm_seq2seq.py
tykimos Sep 3, 2019
552ffce
Update lstm_seq2seq.py
tykimos Sep 3, 2019
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7 changes: 5 additions & 2 deletions examples/lstm_seq2seq.py
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Original file line number Diff line number Diff line change
Expand Up @@ -114,14 +114,16 @@
for i, (input_text, target_text) in enumerate(zip(input_texts, target_texts)):
for t, char in enumerate(input_text):
encoder_input_data[i, t, input_token_index[char]] = 1.
encoder_input_data[i, t + 1:, input_token_index[' ']] = 1.
for t, char in enumerate(target_text):
# decoder_target_data is ahead of decoder_input_data by one timestep
decoder_input_data[i, t, target_token_index[char]] = 1.
if t > 0:
# decoder_target_data will be ahead by one timestep
# and will not include the start character.
decoder_target_data[i, t - 1, target_token_index[char]] = 1.

decoder_input_data[i, t + 1:, target_token_index[' ']] = 1.
decoder_target_data[i, t:, target_token_index[' ']] = 1.
# Define an input sequence and process it.
encoder_inputs = Input(shape=(None, num_encoder_tokens))
encoder = LSTM(latent_dim, return_state=True)
Expand All @@ -145,7 +147,8 @@
model = Model([encoder_inputs, decoder_inputs], decoder_outputs)

# Run training
model.compile(optimizer='rmsprop', loss='categorical_crossentropy')
model.compile(optimizer='rmsprop', loss='categorical_crossentropy',
metrics=['accuracy'])
model.fit([encoder_input_data, decoder_input_data], decoder_target_data,
batch_size=batch_size,
epochs=epochs,
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