casact / rp-bnn-claims Goto Github PK

I'm an renv novice, so apologies if this is an obvious question. When running renv::restore, I get the message * The library is already synchronized with the lockfile.. Yet RStudio tells me that I don't have recipes, tfdatasets and two others. I know that I have recipes installed globally, but it doesn't look as though it appears in the file renv.lock.

Does the lockfile simply need to be updated?

@PirateGrunt added you as admin, not sure if that's enough to transfer ownership but worth a shot (so I don't need to obtain unnecessary permissions on the cas org)

Hello,

I'm working on individual claims reserving and your work is incredible ! Thank you so much for sharing your code.

I came across an error and I can't fix it (is the problem coming from the new version of tfprobabilty or tensorflow or something else ?)
It's related to this lines of code (model.R) :

paid_out <- out_sequence %>%
    layer_dense_variational(units = 4,
                            make_posterior_fn = posterior_mean_field,
                            make_prior_fn = prior,
                            kl_weight = 1 / n_rows,
                            activation = "linear") %>%
    layer_distribution_lambda(
      function(x) {
       

        d <- tfd_mixture(
          cat = tfd_categorical(logits = x[,,1:2]),
          components = list(
            tfd_transformed_distribution(
              tfd_log_normal(x[,,3], 1e-3 + ln_scale_bound * k_sigmoid(scale_c * x[,,4])),
              tfb_affine_scalar(shift = -1e-3)
            ),
            tfd_deterministic(loc = k_zeros_like(x[,,3]))
          )
        )
      },
      name = "paid_out_"
    )

Am getting this error :

Warning message in tfb_affine_scalar(shift = -0.001):
“tfb_affine_scalar() is deprecated, please use tfb_shift(shift)(tfb_scale(scale)) instead”
Error in py_call_impl(callable, dots$args, dots$keywords): RuntimeError: Exception encountered when calling layer "paid_out_" (type DistributionLambda).

Evaluation error: TypeError: got an unexpected keyword argument 'use_static_graph'

Detailed traceback:

File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/decorator.py", line 231, in fun
args, kw = fix(args, kw, sig)
File "/miniconda/envs/r-reticulate/lib/python3.8/site-packages/decorator.py", line 203, in fix
ba = sig.bind(*args, **kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/inspect.py", line 3037, in bind
return self._bind(args, kwargs)
File "/miniconda/envs/r-reticulate/lib/python3.8/inspect.py", line 3026, in _bind
raise TypeError(

Call arguments received:

• inputs=tf.Tensor(shape=(None, 11, 4), dtype=float32)
• args=<class 'inspect._empty'>
• kwargs={'training': 'None'}

Thank you so much !

After addressing the renv issue #14, I'm now having an issue with piggyback::download(). It worked earlier, but I'm not getting the error:

Error in df[update, ] : incorrect number of dimensions
In addition: Warning message:
In get_token() : Using default public GITHUB_TOKEN.
                     Please set your own token

Is the repo missing a .pbattributes file?

In requirements.txt, line 14: pkg-resources==0.0.0

I do not believe this to be a valid PyPI package number.

To the original author(s), please ensure that package numbers are valid in order for users to build the project.

I'll try to create a PR to correct this and any other package version issues soon.

Thank you! :D

I tried to build the repo and received an error, stating that PyPI cannot find the version of opt-einsum at 3.0.0.

could not find function "layer_distribution_lambda"
file model.R
I use keras 2.13.0
tensorflow 2.14.0.9000
trims