`thin` and `pb_update` combinations result in `tensorflow` errors

This issues is, apprently, related to #241 (also #284). I believe, the root cause of #241 is that (according to docs) when `pb_update <= thin`, `pb_update` is selected to be `thin + 1`. This is extremely poor decision, because, as human beings, users tend to select `thin` divisable by e.g. 5, 10, therefore `pb_udpate + 1` can be a prime number, and not a divisor of `n_sample` or `warmup` in the `mcmc` method.

Now, different values of `pb_update` cause `greta` to fail at the end of sampling with some `python` TensorArray-zero-size error. I ran some tests for different combinations of `pb_update` and `thin` to check, what values are causing those crashes.

The best thing is that `mcmc(verbose = FALSE)` appears to solve the problem, so `greta` crashes are actually caused by `UI` behaviour. I was unable to locate the source of the problem, but I would say it happens at the last sampling step (maybe, [here](https://github.com/greta-dev/greta/blob/master/R/inference_class.R#L512-L534)). Changes, introduced in #284, might be causing the problem.

In the following table, look at #⁠4 and #⁠7, which update by `10x + 1`. This appears to *almost always* crash, and it is exactly what happens if `pb_update <= thin`.
``` r
reticulate::use_condaenv("r-tensorflow-gpu", required = TRUE)
library(greta, warn.conflicts = FALSE)
library(purrr, warn.conflicts = FALSE)
library(dplyr, warn.conflicts = FALSE)
library(vctrs, warn.conflicts = FALSE)

run_model <- function(n_warm, n_spin, n_thin, n_pb_update) {
x <- normal(0, 1)
model <- model(x)
result <-
suppressWarnings(
suppressMessages(
mcmc(model, n_samples = n_spin, warmup = n_warm,
thin = n_thin, pb_update = n_pb_update,
chains = 4, n_cores = 8)))

summary(result)$statistics
}

wrap_call <- function(n_warm, n_spin, n_thin, n_pb_update) {
pmap(list(n_warm, n_spin, n_thin, n_pb_update),
function(n_w, n_s, n_t, n_pb) {
result <- tryCatch(run_model(n_w, n_s, n_t, n_pb),
error = function(e) return(e))
if (inherits(result, "error"))
return(list(Warmup = n_w, Spin = n_s, Thin = n_t, Pb = n_pb,
Mean = NA_real_, SD = NA_real_, Status = FALSE,
Message = result$message))
else
return(list(Warmup = n_w, Spin = n_s, Thin = n_t, Pb = n_pb,
Mean = result["Mean"], SD = result["SD"], Status = TRUE,
Message = "OK"))
}) %>% bind_rows
}

wrap_call(
n_warm = 1000L,
n_spin = 1000L,
n_thin = vec_c(1L, 25L, 30L, 50L, 10L, 10L, 10L, 10L),
n_pb_update = vec_c(50L, 50L, 50L, 50L, 20L, 23L, 31L, 99L)
) ->> temp

print(temp)
#> # A tibble: 8 x 8
#> Warmup Spin Thin Pb Mean SD Status Message
#>
#> 1 1000 1000 1 50 0.00881 1.00 TRUE OK
#> 2 1000 1000 25 50 -0.122 1.11 TRUE OK
#> 3 1000 1000 30 50 -0.245 1.05 TRUE OK
#> 4 1000 1000 50 50 NA NA FALSE "greta hit a tensorflow ~
#> 5 1000 1000 10 20 0.0183 0.987 TRUE OK
#> 6 1000 1000 10 23 -0.0226 0.971 TRUE OK
#> 7 1000 1000 10 31 NA NA FALSE "greta hit a tensorflow ~
#> 8 1000 1000 10 99 0.0791 0.942 TRUE OK
```
``` r
sessionInfo()
#> R version 3.6.1 (2019-07-05)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 18362)
#>
#> Matrix products: default
#>
#> locale:
#> [1] LC_COLLATE=English_United States.1252
#> [2] LC_CTYPE=English_United States.1252
#> [3] LC_MONETARY=English_United States.1252
#> [4] LC_NUMERIC=C
#> [5] LC_TIME=English_United States.1252
#> .....
```
``` r
reticulate::py_config()
#> python: C:\PROGRA~3\MINICO~1\envs\R-TENS~1\python.exe
#> libpython: C:/PROGRA~3/MINICO~1/envs/R-TENS~1/python37.dll
#> pythonhome: C:\PROGRA~3\MINICO~1\envs\R-TENS~1
#> version: 3.7.4 (default, Aug 9 2019, 18:34:13) [MSC v.1915 64 bit (AMD64)]
#> Architecture: 64bit
#> numpy: C:\PROGRA~3\MINICO~1\envs\R-TENS~1\lib\site-packages\numpy
#> numpy_version: 1.17.0
#>
#> python versions found:
#> C:\PROGRA~3\MINICO~1\envs\R-TENS~1\python.exe
#> C:\PROGRA~3\MINICO~1\python.exe
#> C:\ProgramData\Miniconda3\python.exe
#> C:\ProgramData\Miniconda3\envs\r-tensorflow-gpu\python.exe
```
``` r
reticulate::use_condaenv("r-tensorflow-gpu", required = TRUE)
tensorflow::tf_config()
#> TensorFlow v1.14.0 (C:\PROGRA~3\MINICO~1\envs\R-TENS~1\lib\site-packages\tensorflow\__init__.p)
#> Python v3.7 (C:\ProgramData\Miniconda3\envs\r-tensorflow-gpu\python.exe)
tensorflow::tf_gpu_configured()
#> TensorFlow built with CUDA: TRUE
#> GPU device name: /device:GPU:0
#> [1] TRUE
```
``` r
packageDescription("greta")
#> Package: greta
#> Type: Package
#> Title: Simple and Scalable Statistical Modelling in R
#> Version: 0.3.1.9004
#> Date: 2019-08-25
#> ...
#> Encoding: UTF-8
#> LazyData: true
#> Depends: R (>= 3.0)
#> Collate: 'package.R' 'utils.R' 'tf_functions.R' 'overloaded.R'
#> .....
#> Imports: R6, tensorflow (>= 1.13.0), reticulate, progress (>=
#> 1.2.0), future, coda, methods
#> Suggests: knitr, rmarkdown, DiagrammeR, bayesplot, lattice,
#> testthat, mvtnorm, MCMCpack, rmutil, extraDistr, truncdist,
#> tidyverse, fields, MASS, abind, spelling
#> VignetteBuilder: knitr
#> RoxygenNote: 6.1.1
#> Language: en-GB
#> RemoteType: github
#> RemoteHost: api.github.com
#> RemoteRepo: greta
#> RemoteUsername: greta-dev
#> RemoteRef: master
#> RemoteSha: 4d08524a7e13bc759a1c66fd1657455803c2ebf5
#> GithubRepo: greta
#> GithubUsername: greta-dev
#> GithubRef: master
#> GithubSHA1: 4d08524a7e13bc759a1c66fd1657455803c2ebf5
#> NeedsCompilation: no
#> .....
#> Built: R 3.6.1; ; 2019-09-06 12:11:50 UTC; windows

```

^{Created on 2019-09-26 by the [reprex package](https://reprex.tidyverse.org) (v0.3.0)}

```
greta hit a tensorflow error:

Error in py_call_impl(callable, dots$args, dots$keywords): UnimplementedError: 2 root error(s) found.
(0) Unimplemented: TensorArray has size zero, but element shape [?] is not fully defined. Currently only static shapes are supported when packing zero-size TensorArrays.
[[node mcmc_sample_chain/trace_scan/TensorArrayStack_2/TensorArrayGatherV3 (defined at \tensorflow_probability\python\mcmc\internal\util.py:372) ]]
[[mcmc_sample_chain/trace_scan/while/smart_for_loop/while/Exit_5/_75]]
(1) Unimplemented: TensorArray has size zero, but element shape [?] is not fully defined. Currently only static shapes are supported when packing zero-size TensorArrays.
[[node mcmc_sample_chain/trace_scan/TensorArrayStack_2/TensorArrayGatherV3 (defined at \tensorflow_probability\python\mcmc\internal\util.py:372) ]]
0 successful operations.
0 derived errors ignored.

Errors may have originated from an input operation.
Input Source operations connected to node mcmc_sample_chain/trace_scan/TensorArrayStack_2/TensorArrayGatherV3:
mcmc_sample_chain/trace_scan/while/Exit_13 (defined at \tensorflow_probability\python\mcmc\internal\util.py:370)
mcmc_sample_chain/trace_scan/TensorArray_3 (defined at \tensorflow_probability\python\mcmc\internal\util.py:355)

Input Source operations connected to node mcmc_sample_chain/trace_scan/TensorArrayStack_2/TensorArrayGatherV3:
mcmc_sample_chain/trace_scan/while/Exit_13 (defined at \tensorflow_probability\python\mcmc\internal\util.py:370)
mcmc_sample_chain/trace_scan/TensorArray_3 (defined at \tensorflow_probability\python\mcmc\internal\util.py:355)

Original stack trace for 'mcmc_sample_chain/trace_scan/TensorArrayStack_2/TensorArrayGatherV3':
File "\tensorflow_probability\python\mcmc\sample.py", line 361, in sample_chain
parallel_iterations=parallel_iterations)
File "\tensorflow_probability\python\mcmc\internal\util.py", line 372, in trace_scan
stacked_trace = tf.nest.map_structure(lambda x: x.stack(), trace_arrays)
File "\tensorflow\python\util\nest.py", line 515, in map_structure
structure[0], [func(*x) for x in entries],
File "\tensorflow\python\util\nest.py", line 515, in
structure[0], [func(*x) for x in entries],
File "\tensorflow_probability\python\mcmc\internal\util.py", line 372, in
stacked_trace = tf.nest.map_structure(lambda x: x.stack(), trace_arrays)
File "\tensorflow\python\ops\tensor_array_ops.py", line 1205, in stack
return self._implementation.stack(name=name)
File "\tensorflow\python\ops\tensor_array_ops.py", line 309, in stack
return self.gather(math_ops.range(0, self.size()), name=name)
File "\tensorflow\python\ops\tensor_array_ops.py", line 323, in gather
element_shape=element_shape)
File "\tensorflow\python\ops\gen_data_flow_ops.py", line 7167, in tensor_array_gather_v3
element_shape=element_shape, name=name)
File "\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "\tensorflow\python\util\deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "\tensorflow\python\framework\ops.py", line 3616, in create_op
op_def=op_def)
File "\tensorflow\python\framework\ops.py", line 2005, in __init__
self._traceback = tf_stack.extract_stack()

Detailed traceback:
File "C:\PROGRA~3\MINICO~1\envs\R-TENS~1\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "C:\PROGRA~3\MINICO~1\envs\R-TENS~1\lib\site-packages\tensorflow\python\client\session.py", line 1173, in _run
feed_dict_tensor, options, run_metadata)
File "C:\PROGRA~3\MINICO~1\envs\R-TENS~1\lib\site-packages\tensorflow\python\client\session.py", line 1350, in _do_run
run_metadata)
File "C:\PROGRA~3\MINICO~1\envs\R-TENS~1\lib\site-packages\tensorflow\python\client\session.py", line 1370, in _do_call
raise type(e)(node_def, op, message)
```