Error in py_call_impl(callable, dots$args, dots$keywords): RuntimeError: in user code:
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/keras/engine/training.py", line 878, in train_function
return step_function(self, iterator)
File "/usr/local/lib/R/site-library/reticulate/python/rpytools/call.py", line 21, in python_function
raise RuntimeError(res[kErrorKey])
RuntimeError: Evaluation error: TypeError: bad operand type for unary -: 'NoneType'
Detailed traceback:
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/distributions/distribution.py", line 1316, in log_prob
return self._call_log_prob(value, name, kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/distributions/distribution.py", line 1298, in _call_log_prob
return self._log_prob(value, kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/distributions/mixture.py", line 279, in _log_prob
distribution_log_probs = [d.log_prob(x) for d in self.components]
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/distributions/mixture.py", line 279, in
distribution_log_probs = [d.log_prob(x) for d in self.components]
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/distributions/distribution.py", line 1316, in log_prob
return self._call_log_prob(value, name, kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/distributions/distribution.py", line 1298, in _call_log_prob
return self._log_prob(value, kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/distributions/transformed_distribution.py", line 367, in _log_prob
ildj = self.bijector.inverse_log_det_jacobian(
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/bijectors/bijector.py", line 1561, in inverse_log_det_jacobian
return self._call_inverse_log_det_jacobian(y, event_ndims, name, kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/bijectors/composition.py", line 539, in _call_inverse_log_det_jacobian
return self._inverse_log_det_jacobian(y, event_ndims, kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/bijectors/composition.py", line 552, in _inverse_log_det_jacobian
bm.bijector.inverse_log_det_jacobian(bm.x, bm.x_event_ndims,
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/bijectors/bijector.py", line 1561, in inverse_log_det_jacobian
return self._call_inverse_log_det_jacobian(y, event_ndims, name, kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/tensorflow_probability/python/bijectors/bijector.py", line 1492, in _call_inverse_log_det_jacobian
ildj = attrs['ildj'] = -self._forward_log_det_jacobian(x, kwargs)
I was wondring if it's related to _tf_probability since I see directories that refears to tensorflow_probability_ and if you have an idea how to fix it !
Suggest you file an issue with the authors of the code since what you have posted is a fragment of the code and it's unlikely that anyone will download, run, and debug the full code.
Suggest that you try to boil the error down to a minimum working example (smallest replicable example). That will allow people to dig into it. Else, option 1 is your best bet IMO. In what you have posted its not clear what train_data_keras etc. is. For example, why are you doing dim(train_data_keras$x[[1]])[[1]] this and then sending train_data_keras$x to Keras. That looks wrong but I can't tell because I don't know what each object is.
Hello, I hope you're all fine ^^
I'm trying to reproduce the code of this project : rp-bnn-claims
I'm having a weird error when I've tried to run this lines :
The error :
I was wondring if it's related to _tf_probability since I see directories that refears to tensorflow_probability_ and if you have an idea how to fix it !
Kindly yours,