怎么在不降TensorFlow版本的情况下使用TrainingHelper
时间: 2024-05-07 18:21:33 浏览: 12
如果您使用的是TensorFlow 2.x版本,则TrainingHelper已经被tf.compat.v1.seq2seq.TrainingHelper替代了。因此,您可以使用以下代码在不降低TensorFlow版本的情况下使用TrainingHelper:
```python
import tensorflow as tf
# define inputs
encoder_inputs = ...
decoder_inputs = ...
decoder_lengths = ...
# define decoder cell and initial state
decoder_cell = ...
decoder_initial_state = ...
# define output projection layer
output_layer = tf.keras.layers.Dense(...)
# create TrainingHelper
training_helper = tf.compat.v1.seq2seq.TrainingHelper(
inputs=decoder_inputs,
sequence_length=decoder_lengths,
time_major=False
)
# create BasicDecoder
decoder = tf.compat.v1.seq2seq.BasicDecoder(
cell=decoder_cell,
helper=training_helper,
initial_state=decoder_initial_state,
output_layer=output_layer
)
# get final outputs and state
outputs, state, _ = tf.compat.v1.seq2seq.dynamic_decode(
decoder=decoder,
output_time_major=False,
impute_finished=True,
maximum_iterations=...
)
```
请注意,由于TrainingHelper是tf.compat.v1.seq2seq.TrainingHelper,因此您需要从tf.compat.v1中导入它。此外,您还需要使用impute_finished=True来告诉dynamic_decode在解码完成后填充剩余的时间步骤。