module 'tensorflow' has no attribute 'contrib'

[njtierney]

First reported here https://forum.greta-stats.org/t/odes-and-config-attribute-in-tensorflow/366

This appears to be an issue with using the contrib slot in tensorflow, specifically in greta.dynamics, probably here:

greta.dynamics/R/ode_solve.R

Line 179 in 5defd19

tf_int <- tf$contrib$integrate

It is likely just an API change, but here is the reprex:

library(greta.dynamics)
#> Loading required package: greta
#> 
#> Attaching package: 'greta'
#> The following objects are masked from 'package:stats':
#> 
#>     binomial, cov2cor, poisson
#> The following objects are masked from 'package:base':
#> 
#>     %*%, apply, backsolve, beta, chol2inv, colMeans, colSums, diag,
#>     eigen, forwardsolve, gamma, identity, rowMeans, rowSums, sweep,
#>     tapply
greta_sitrep()
#> ℹ checking if python available
#> ✔ python (v3.10) available
#> 
#> ℹ checking if TensorFlow available
#> ✔ TensorFlow (v2.15.0) available
#> 
#> ℹ checking if TensorFlow Probability available
#> ✔ TensorFlow Probability (v0.23.0) available
#> 
#> ℹ checking if greta conda environment available
#> ✔ greta conda environment available
#> 
#> ℹ Initialising python and checking dependencies, this may take a moment.
#> ✔ Initialising python and checking dependencies ... done!
#> 
#> ℹ greta is ready to use!
# replicate the Lotka-Volterra example from deSolve
library(deSolve)
LVmod <- function(Time, State, Pars) {
  with(as.list(c(State, Pars)), {
    Ingestion <- rIng * Prey * Predator
    GrowthPrey <- rGrow * Prey * (1 - Prey / K)
    MortPredator <- rMort * Predator
    
    dPrey <- GrowthPrey - Ingestion
    dPredator <- Ingestion * assEff - MortPredator
    
    return(list(c(dPrey, dPredator)))
  })
}

pars <- c(
  rIng = 0.2, # /day, rate of ingestion
  rGrow = 1.0, # /day, growth rate of prey
  rMort = 0.2, # /day, mortality rate of predator
  assEff = 0.5, # -, assimilation efficiency
  K = 10
) # mmol/m3, carrying capacity

yini <- c(Prey = 1, Predator = 2)
times <- seq(0, 30, by = 1)
out <- ode(yini, times, LVmod, pars)

# simulate observations
jitter <- rnorm(2 * length(times), 0, 0.1)
y_obs <- out[, -1] + matrix(jitter, ncol = 2)

# fit a greta model to infer the parameters from this simulated data

# greta version of the function
lotka_volterra <- function(y, t, rIng, rGrow, rMort, assEff, K) {
  Prey <- y[1, 1]
  Predator <- y[1, 2]
  
  Ingestion <- rIng * Prey * Predator
  GrowthPrey <- rGrow * Prey * (1 - Prey / K)
  MortPredator <- rMort * Predator
  
  dPrey <- GrowthPrey - Ingestion
  dPredator <- Ingestion * assEff - MortPredator
  
  cbind(dPrey, dPredator)
}

# priors for the parameters
rIng <- uniform(0, 2) # /day, rate of ingestion
rGrow <- uniform(0, 3) # /day, growth rate of prey
rMort <- uniform(0, 1) # /day, mortality rate of predator
assEff <- uniform(0, 1) # -, assimilation efficiency
K <- uniform(0, 30) # mmol/m3, carrying capacity

# initial values and observation error
y0 <- uniform(0, 5, dim = c(1, 2))
obs_sd <- uniform(0, 1)

# solution to the ODE
y <- ode_solve(lotka_volterra, y0, times, rIng, rGrow, rMort, assEff, K)

# sampling statement/observation model
distribution(y_obs) <- normal(y, obs_sd)

# we can use greta to solve directly, for a fixed set of parameters (the true
# ones in this case)
values <- c(
  list(y0 = t(1:2)),
  as.list(pars)
)
vals <- calculate(y, values = values)[[1]]
#> module 'tensorflow' has no attribute 'contrib'

^{Created on 2024-11-06 with reprex v2.1.1}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.4.1 Patched (2024-07-08 r86915)
#>  os       macOS Sonoma 14.5
#>  system   aarch64, darwin20
#>  ui       X11
#>  language (EN)
#>  collate  en_US.UTF-8
#>  ctype    en_US.UTF-8
#>  tz       Australia/Hobart
#>  date     2024-11-06
#>  pandoc   3.2 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/aarch64/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package        * version  date (UTC) lib source
#>  abind            1.4-5    2016-07-21 [1] CRAN (R 4.4.0)
#>  backports        1.5.0    2024-05-23 [1] CRAN (R 4.4.0)
#>  base64enc        0.1-3    2015-07-28 [1] CRAN (R 4.4.0)
#>  callr            3.7.6    2024-03-25 [1] CRAN (R 4.4.0)
#>  cli              3.6.3    2024-06-21 [1] CRAN (R 4.4.0)
#>  coda             0.19-4.1 2024-01-31 [1] CRAN (R 4.4.0)
#>  codetools        0.2-20   2024-03-31 [2] CRAN (R 4.4.1)
#>  crayon           1.5.3    2024-06-20 [1] CRAN (R 4.4.0)
#>  deSolve        * 1.40     2023-11-27 [1] CRAN (R 4.4.0)
#>  digest           0.6.37   2024-08-19 [1] CRAN (R 4.4.1)
#>  evaluate         1.0.1    2024-10-10 [1] CRAN (R 4.4.1)
#>  fansi            1.0.6    2023-12-08 [1] CRAN (R 4.4.0)
#>  fastmap          1.2.0    2024-05-15 [1] CRAN (R 4.4.0)
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#>  glue             1.8.0    2024-09-30 [1] CRAN (R 4.4.1)
#>  greta          * 0.5.0    2024-11-06 [1] local
#>  greta.dynamics * 0.2.1    2024-10-15 [1] https://greta-dev.r-universe.dev (R 4.4.1)
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#>  [2] /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library
#> 
#> ─ Python configuration ───────────────────────────────────────────────────────
#>  python:         /Users/nick/Library/r-miniconda-arm64/envs/greta-env-tf2/bin/python
#>  libpython:      /Users/nick/Library/r-miniconda-arm64/envs/greta-env-tf2/lib/libpython3.10.dylib
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#> 
#> ──────────────────────────────────────────────────────────────────────────────

And the output of reticulate::py_last_error()

> reticulate::py_last_error()

── Python Exception Message ─────────────────────────────────────────────────────────────────────────
AttributeError: module 'tensorflow' has no attribute 'contrib'

── R Traceback ──────────────────────────────────────────────────────────────────────────────────────
     ▆
  1. └─greta::calculate(y, values = values)
  2.   ├─base::with(...) at greta/R/calculate.R:163:3
  3.   ├─reticulate:::with.python.builtin.object(...)
  4.   │ ├─base::tryCatch(...)
  5.   │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
  6.   │ └─base::force(expr)
  7.   └─greta:::calculate_list(...) at greta/R/calculate.R:252:7
  8.     └─greta:::calculate_target_tensor_list(...) at greta/R/calculate.R:428:3
  9.       └─dag$define_tf(target_nodes = target_nodes) at greta/R/calculate.R:499:3
 10.         └─self$define_tf_body(target_nodes = target_nodes) at greta/R/dag_class.R:374:7
 11.           └─base::lapply(...) at greta/R/dag_class.R:349:7
 12.             └─greta (local) FUN(X[[i]], ...)
 13.               └─x$define_tf(self) at greta/R/dag_class.R:351:9
 14.                 └─self$tf(dag) at greta/R/node_class.R:211:9
 15.                   ├─base::do.call(operation, tf_args) at greta/R/node_types.R:192:9
 16.                   └─greta.dynamics (local) `<fn>`(...)
 17.                     ├─tf$contrib
 18.                     └─reticulate:::`$.python.builtin.module`(tf, "contrib")
 19.                       └─reticulate::py_get_attr(x, name, FALSE)
See `reticulate::py_last_error()$r_trace$full_call` for more details.

[goldingn]

Just flagging that there's a greta_2 branch of greta.dynamics. That might be the solution if this error is due to the main greta.dynamics (which I think is for TF1 greta) being run with TF2 greta.

[njtierney]

Thanks, Nick! I'll make sure to branch changes off from that TF2 branch.

Currently the issue seems to be

greta.dynamics/R/ode_solve.R

Line 179 in 5defd19

tf_int <- tf$contrib$integrate

Just trying to track down if they've left some backwards compatibility in there somewhere - so far the best I've come up with is the ODE solver in TFP: https://www.tensorflow.org/probability/api_docs/python/tfp/math/ode/Solver

But nothing that is just a drop-in

[njtierney]

Resolved in #33