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Please have a look at the FAQ section in the README - maybe your question is already answered there.
Only issues concerning the repositories code will be answered.
The following questions will not be answered:
How to convert dataset X into IAM format?
How to modify the model to recognize text-lines/more characters/...?
General/theoretical questions regarding (handwritten) text recognition.
If you create a new issue, please provide the following information:
Versions
TensorFlow version 2.4.0
Python version 3.6.9
Operating system Red Hat Enterprise Linux Server 7.9
Issue
Which result/error did you get?
ValueError: Paddings must be non-negative for '{{node Optimizer/gradients/RNN/Slice_grad/Pad}} = Pad[T=DT_FLOAT, Tpaddings=DT_INT32](Optimizer/gradients/RNN/Squeeze_grad/Reshape, Optimizer/gradients/RNN/Slice_grad/concat)' with input shapes: [50,102,1,512], [4,2] and with computed input tensors: input[1] = <[0 0][0 -2][0 3][0 0]>.
If you think the result is wrong - what result did you expect instead?
How to reproduce the issue? set maxTextLen = 102, replace 100 in setupRNN with Model.maxTextLen
Provide all necessary data
The text was updated successfully, but these errors were encountered:
Please have a look at the FAQ section in the README - maybe your question is already answered there.
Only issues concerning the repositories code will be answered.
The following questions will not be answered:
If you create a new issue, please provide the following information:
The text was updated successfully, but these errors were encountered: