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Option --rnn_layer_number 2 gives dimensions / input shapes error #5

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jowagner opened this issue Sep 14, 2018 · 0 comments
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@jowagner
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Seeing --rnn_layer_number in the list of options, I gave it a go with 2 instead of the default 1 and got the following error (large number of tensorflow traceback lines removed):

Traceback (most recent call last):
  File "segmenter.py", line 261, in <module>
    rnn_num=args.rnn_layer_number, drop_out=args.dropout_rate, emb=emb)
  File "/[...]/model.py", line 130, in main_graph
    scope='BiRNN')(emb_out, input_v)
  File "/[...]/layers.py", line 236, in __call__
    scope=self.scope)
[...]
ValueError: Dimensions must be equal, but are 400 and 250 for 'tagger/BiRNN_1/fw/fw/while/fw/multi_rnn_cell/cell_0/gru_cell/MatMul_2' (op: 'MatMul') with input shapes: [?,400], [250,400].

If this option is currently unsupported it might be better to comment out the respective argparser line.

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