(‘train shape:’, (177, 1, 14, 100))
(‘valid shape:’, (177, 1, 14, 100))
(‘sentence max words’, 14)
(‘embedding size’, 100)
(‘vocab size’, -1)
The above data represents the shape of my data. I have reshaped it like this
x = np.reshape(x, (x.shape[0], 1, x.shape[1], x.shape[2]))
when i run my model.fit I am getting the following error :
RuntimeError: simple_bind error. Arguments:
data: (2, 1L, 14L, 100L)
softmax_label: (2, 1L)
Error in operator reshape0: [17:40:34] src/operator/tensor/./matrix_op-inl.h:182: Check failed: oshape.Size() == dshape.Size() Target shape size is different to source. Target: 1200
Source: 600
Any idea how to solve this error
szha
January 30, 2018, 6:08am
2
Would you follow the issue template here and provide more information to reproduce the problem? Feel free to skip the environment info part and make sure you include the mxnet version. Thanks!
Note: Providing complete information in the most concise form is the best way to get help. This issue template serves as the checklist for essential information to most of the technical issues and bug reports. For non-technical issues and feature requests, feel free to present the information in what you believe is the best form.
For Q & A and discussion, please start a discussion thread at https://discuss.mxnet.apache.org
## Description
(Brief description of the problem in no more than 2 sentences.)
## Environment info (Required)
```
What to do:
1. Download the diagnosis script from https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py
2. Run the script using `python diagnose.py` and paste its output here.
```
Package used (Python/R/Scala/Julia):
(I'm using ...)
For Scala user, please provide:
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