Investigating Sparsity in Recurrent Neural Networks
Paper • 2407.20601 • Published
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The JWT signature verification failed. Check the signing key and the algorithm.
Error code: JWTInvalidSignature
Exception: InvalidSignatureError
Message: Signature verification failed
Traceback: Traceback (most recent call last):
File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
decoded = jwt.decode(
jwt=token,
...<2 lines>...
options=options,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
decoded = self.decode_complete(
jwt,
...<8 lines>...
leeway=leeway,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
decoded = self._jws.decode_complete(
jwt,
...<3 lines>...
detached_payload=detached_payload,
)
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
self._verify_signature(
~~~~~~~~~~~~~~~~~~~~~~^
signing_input,
^^^^^^^^^^^^^^
...<4 lines>...
options=merged_options,
^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
raise InvalidSignatureError("Signature verification failed")
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A Reber sequence is a grammar string made of finite states, in simple words, formed by using a confined set of characters. In the research paper that proposed the LSTM, the authors use embedded Reber grammar due to its short time lags.
Here is the chapter from my Master's thesis that briefly explains the dataset, and also includes various plots about its statistics.
Data visualiations available at about_reber.
Master's thesis: Investigating Sparsity in Recurrent Neural Networks
@article{darji2024investigating,
title={Investigating Sparsity in Recurrent Neural Networks},
author={Darji, Harshil},
journal={arXiv preprint arXiv:2407.20601},
year={2024}
}
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