TypeError: Can't Pickle _thread.lock Objects In Seq2Seq

I'm having trouble using buckets in my Tensorflow model. When I run it with buckets = [(100, 100)], it works fine. When I run it with buckets = [(100, 100), (200, 200)] it doesn't

Solution 1:

The problem is with latest changes in seq2seq.py. Add this to your script and it will avoid deep-coping of the cells:

setattr(tf.contrib.rnn.GRUCell, '__deepcopy__', lambda self, _: self)
setattr(tf.contrib.rnn.BasicLSTMCell, '__deepcopy__', lambda self, _: self)
setattr(tf.contrib.rnn.MultiRNNCell, '__deepcopy__', lambda self, _: self)

Solution 2:

This solution does not work for me. Any new solution?

These two solutions work for me:

change seq2seq.py under /yourpath/tensorflow/contrib/legacy_seq2seq/python/ops/

#encoder_cell = copy.deepcopy(cell)
encoder_cell = core_rnn_cell.EmbeddingWrapper(
    cell, #encoder_cell,

or

for nextBatch in tqdm(batches, desc="Training"):
    _, step_loss = model.step(...)

fed one bucket at a step