Hi,
I am using MXNet gluon module for implementing seq2seq attention based neural language correction. The model is training for 10 epochs and after that I am getting the following error:
**"MXNetError: [19:12:27] include/mxnet/././tensor_blob.h:257: Check failed: this->shape_.Size() == shape.Size() (151 vs. 150) TBlob.get_with_shape: new and old shape do not match total elements
**
I am getting this error while printing the loss:
l_sum += l.asscalar()
Full stack trace:
Stack trace returned 10 entries:
[bt] (0) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x308362) [0x7efc4ffc0362]
[bt] (1) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x308938) [0x7efc4ffc0938]
[bt] (2) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x36ef49) [0x7efc50026f49]
[bt] (3) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x280babc) [0x7efc524c3abc]
[bt] (4) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x29c0926) [0x7efc52678926]
[bt] (5) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x293e123) [0x7efc525f6123]
[bt] (6) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x2946524) [0x7efc525fe524]
[bt] (7) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x294a071) [0x7efc52602071]
[bt] (8) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x2946beb) [0x7efc525febeb]
[bt] (9) /usr/lib/x86_64-linux-gnu/libstdc++.so.6(+0xb8c80) [0x7efcc834cc80]
I thought that one of the reason may be the memory issue. How to resolve this error.
Model summary:
Encoder has 2 LSTM layers with hidden size 200
Attention mechanism
Decoder has 2 LSTM layers with hidden size 200
Maximum_Sequence_length = 150
Total training sentences: 3500
Any suggestions on how to resolve this error…
Thanks in advance,
Harathi