Comments (2)
You need to fix all instances of tf.concat and tf.split as follows.
For tf.concat, Eg. in dual_encody.py, line 54, change:
tf.concat(0, [context_embedded, utterance_embedded]),
to this:
tf.concat([context_embedded, utterance_embedded], 0),
(ie switch order of arguments)
Same thing for all the tf.split cases, Eg. line 57 in same file, change:
encoding_context, encoding_utterance = tf.split(0, 2, rnn_states.h)
to this:
encoding_context, encoding_utterance = tf.split(rnn_states.h, 2, 0)
by switching the first and last arguments.
There were a few more things I had to change to get training running, too.
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Thanks, I have updated all of these, as well as
tf.histogram_summary -> tf.summary.histogram
and
tf.scalar_summary -> tf.summary.scalar
However, there is a new error:
I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla M60, pci bus id: 88f8:00:00.0)
W tensorflow/core/framework/op_kernel.cc:993] Out of range: Reached limit of 1
[[Node: read_batch_features_eval/file_name_queue/limit_epochs/CountUpTo = CountUpToT=DT_INT64, _class=["loc:@read_batch_features_eval/file_name_queue/limit_epochs/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/cpu:0"]]
Any idea?
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