[ALBERT]: LookupError: gradient registry has no entry for: AddV2
See original GitHub issueWhen run run_classifier_with_tfhub.py
, but the training crashed. The error is:
LookupError: No gradient defined for operation 'module_apply_tokens/bert/encoder/transformer/group_0_11/layer_11/inner_group_0/LayerNorm_1/batchnorm/add_1' (op type: AddV2)
My tensorflow-gpu version is 1.14.0
Anyone knows the reason, pls help… Thanks
Issue Analytics
- State:
- Created 4 years ago
- Comments:8
Top Results From Across the Web
Tensorflow RandomContrast Layer Error "LookupError: ...
Tensorflow RandomContrast Layer Error "LookupError: gradient registry has no entry for: AdjustContrastv2" · Ask Question. Asked 10 months ago.
Read more >LookupError: gradient registry has no entry for
Hi guys,. with the new `raw_rnn`, I was able to implement a dynamic rnn decoder (thanks to ebrevdo).
Read more >tf.RegisterGradient | TensorFlow v2.11.0
For an op with m inputs and n outputs, the gradient function is a function that takes the original Operation and n Tensor...
Read more >No gradient defined for operation 'CudnnRNN' (op type
LookupError : gradient registry has no entry for CudnnRNN. During handling of the above exception, another exception occurred:enter code here.
Read more >No gradient defined for operation 'inference/sample/FloorMod ...
So, once I have the Cartesian coordinates (for instance a multivariate ... _name, name)) LookupError: gradient registry has no entry for: ...
Read more >
Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free
Top Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
Duplicate of #94
Can you try using the TF-Hub modules with “/3” suffix? We regenerated them using TF 1.15 (see Jan 7 update in the readme).
I tried upgrading the version of Tensorflow to 1.15 and that helped me bypass the issue.