Comments (6)
The order of arguments for tf.concat and tf.split have changed in TF > 0.12.
So, the actual error is in line 47 dual_encoder_model..
Replace these lines below ( # commented) and corrected below.
This should help..
Also, you may have to replace tf.batch_matmul with tf.matmul and
losses = tf.nn.sigmoid_cross_entropy_with_logits(logits=logits, labels=tf.to_float(targets))
rnn_outputs, rnn_states = tf.nn.dynamic_rnn(
cell,
#tf.concat(0, [context_embedded, utterance_embedded]),
tf.concat( [context_embedded, utterance_embedded], 0),
#sequence_length=tf.concat(0, [context_len, utterance_len]),
sequence_length=tf.concat([context_len, utterance_len], 0),
dtype=tf.float32)
#encoding_context, encoding_utterance = tf.split(0, 2, rnn_states.h)
encoding_context, encoding_utterance = tf.split(rnn_states.h, 2 , 0)
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I have same problem as @nikky78
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You don't really have to @nikky78 , @logust79 .
All you gotta do is change the order of concat and split parameters as mentioned before, replace batch_matmul with matmul and then alter line 81 in dual_encoder.py
losses = tf.nn.sigmoid_cross_entropy_with_logits(logits, tf.to_float(targets))
with
losses = tf.nn.sigmoid_cross_entropy_with_logits(logits=logits, labels=tf.to_float(targets))
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Fixing tf.concat does not fix this problem.
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No, it fixes the problem in the trace above at line 47 in dual_encoder.py, which is due to a change in the order of arguments for tf.concat and tf.split in versions of TF > 0.12
There is a disconnect between the title of this issue and the actual stack trace.
The solution for Monitors being deprecated is to use tf.train.SessionRunHook. It's in the title itself.
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How do you use tf.train.SessionRunHook ?
for instance I have :
hooks = [tf.train.LoggingTensorHook({'loss'}, every_n_iter = 4)]
learn.Experiment(estimator = estimator, train_input_fn = get_train_inputs, eval_input_fn = get_eval_inputs, train_monitors = hooks, eval_hooks = hooks)
It says: Monitors are deprecated. Please use tf.train.SessionRunHook., but I don't know how to change it.
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