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simple and scalable statistical modelling in R
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TF2 Errors in `test_inference.R` - bad proposals are not rejected #574

Closed njtierney closed 2 weeks ago

njtierney commented 1 year ago

See

devtools::load_all(".")
#> ℹ Loading greta
#> ℹ Initialising python and checking dependencies, this may take a moment.
#> 
#> ✔ Initialising python and checking dependencies ... done!
#> Loaded Tensorflow version 2.10.0
source(here::here("tests", "testthat", "helpers.R"))
  x <- rnorm(10000, 1e6, 1)
  z <- normal(-1e6, 1e-6)
  distribution(x) <- normal(z, 1e6)
  m <- model(z, precision = "single")

  out <- get_output(
    mcmc(m, n_samples = 10, warmup = 0, pb_update = 10)
    )
  out
#> [1] "running 4 chains simultaneously on up to 8 CPU cores\n\r  sampling                                             0/10 | eta:  ?s          \r  sampling ========================================== 10/10 | eta:  0s          \n"
  expect_match(out, "100% bad")
#> Error: `out` does not match "100% bad".
#> Actual value: "running 4 chains simultaneously on up to 8 CPU cores\\n\\r  sampling                                             0/10 \| eta:  \?s          \\r  sampling ========================================== 10/10 \| eta:  0s          \\n"

Created on 2022-12-09 with reprex v2.0.2

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This is also related to another test where bad proposals aren't being rejected, where we expect the above model to fail with this code:

expect_snapshot_error(
      draws <- mcmc(m,
                    chains = 1,
                    n_samples = 2,
                    warmup = 0,
                    verbose = FALSE,
                    initial_values = initials(z = 1e60)
      )

Which is supposed to produce this error:

The log density could not be evaluated at these initial values

Try using these initials as the values argument in `calculate()` to see what values of subsequent <greta_array>s these initial values lead to.
njtierney commented 1 year ago

This was due to improvements in TF / better precision in M1 macs - this required some tweaking of the tests to get the values beyond machine tolerance.