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I get the following error when trying to fit the model (Tensorflow 2.3.1):
```
Error in py_call_impl(callable, dots$args, dots$keywords) :
_SymbolicException: Inputs to eager execution functio…
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# Context
## Objective
In this RFC I will talk about the roadmap to enable eager mode as the default computation mode for PyTorch/XLA users and how to enable graph compilation in this mode.
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Click to expand!
### Issue Type
Bug
### Have you reproduced the bug with TF nightly?
Yes
### Source
binary
### Tensorflow Version
tf 2.11.0
### Custom Code
Yes
### OS Platform and Distri…
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| --- | --- |
| Bugzilla Link | [516652](https://bugs.eclipse.org/bugs/show_bug.cgi?id=516652) |
| Status | NEW |
| Importance | P3 normal |
| Reported | May 15, 2017 09:51 EDT |
| Modified | Jul…
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Let me show this on example:
```
from Standard.Base import all
type My_Ref
Lazy ~lazy
Eager eager
get_if_eager self = case self of
My_Ref.Eager x -> x
My_Ref.La…
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From https://github.com/pytorch/pytorch/pull/134282#issuecomment-2307157197, in the aarch64 dashboard results, if we benchmark with fp16, it is 2x~10x slower than bf16, often causing timeout in cases.…
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We currently support `+=` in both Groovy and Kotlin DSLs (and `
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When I try to scale up my model, I find that `tf.scan` uses too much memory. Probably I have to use eager execution.
How well does `HMC` and `SGMCMC` work with eager execution and tensorflow 2.0?
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I ran HuggingFace BERT model which uses tensorflow 2.13v with oneDNN support on intel machine and recorded its execution logs by setting TF_CPP_MAX_VLOG_LEVEL=2 & ONEDNN_VERBOSE=1 in file.
**Observ…
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I installed all the dependencies and ran the code , I have this error
File "/home/lnuser/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/gradients_util.py", line 504, in _GradientsHelpe…