Prepare CRAN release v0.0.5

.Rbuildignore

@@ -36,3 +36,4 @@
 ^cran-comments\.md$
 ^CRAN-SUBMISSION$
 ^configure\.log$
+^\.claude$

.github/workflows/check.yaml

@@ -48,7 +48,7 @@ jobs:
       - name: Install Python libraries used for testing
         continue-on-error: true
         run: |
-          reticulate::py_install(c("tbparse", "tensorflow"), pip = TRUE)
+          reticulate::py_install(c('tbparse', 'tensorflow'), pip = TRUE)
         shell: Rscript {0}
 
       - uses: r-lib/actions/check-r-package@v2

.github/workflows/pkgdown.yaml

@@ -21,6 +21,7 @@ jobs:
       group: pkgdown-${{ github.event_name != 'pull_request' || github.run_id }}
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      CHROMOTE_CHROME: google-chrome-stable
     permissions:
       contents: write
     steps:
@@ -41,7 +42,7 @@ jobs:
 
       - name: Install Python deps
         run: |
-          reticulate::py_install('tensorflow', pip = TRUE)
+          reticulate::py_install(c('tensorflow==2.10', 'numpy<2', 'setuptools<70'), pip = TRUE, python_version = '3.10')
         shell: Rscript {0}
 
       - name: Build site

.github/workflows/test-coverage.yaml

@@ -32,7 +32,7 @@ jobs:
 
       - name: Install Python libraries used for testing
         run: |
-          reticulate::py_install(c("tbparse", "tensorflow"), pip = TRUE)
+          reticulate::py_install(c('tbparse', 'tensorflow'), pip = TRUE)
         shell: Rscript {0}
 
       - name: Test coverage

DESCRIPTION

@@ -1,8 +1,9 @@
 Package: tfevents
 Title: Write Events for 'TensorBoard'
-Version: 0.0.4.9000
+Version: 0.0.5
 Authors@R: c(
-    person("Daniel", "Falbel", email = "daniel@posit.co", role = c("aut", "cre", "cph")),
+    person("Daniel", "Falbel", email = "daniel@posit.co", role = c("aut", "cph")),
+    person("Tomasz", "Kalinowski", email = "tomasz@posit.co", role = c("cre")),
     person(family = "Posit, PBC", role = c("cph")),
     person(family = "The tl::optional authors", role = c("cph"), comment = "For the vendored tl::optional code."),
     person("Mark", "Adler", role = c("cph"), comment = "For the included crc32c code.")
@@ -13,7 +14,7 @@ Description: Provides a convenient way to log scalars, images, audio, and histog
 License: MIT + file LICENSE
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.3
 LinkingTo: 
     Rcpp
 Imports: 

NAMESPACE

@@ -4,6 +4,10 @@ S3method(as_event,character)
 S3method(as_event,list)
 S3method(as_event,numeric)
 S3method(as_event,tfevents_summary_values)
+S3method(as_tensor_proto,array)
+S3method(as_tensor_proto,blob)
+S3method(as_tensor_proto,character)
+S3method(as_tensor_proto,list)
 S3method(format,tfevents_event)
 S3method(format,tfevents_summary)
 S3method(format,tfevents_summary_values)

NEWS.md

@@ -1,4 +1,6 @@
-# tfevents (development version)
+# tfevents 0.0.5
+
+* Changed maintainer to Tomasz Kalinowski.
 
 # tfevents 0.0.4
 

R/audio.R

@@ -7,7 +7,7 @@
 #' @param sample_rate The sample rate in Hz associated to the audio values.
 #' @returns An audio summary that can be logged with [log_event()].
 #' @family summary
-#' @examples
+#' @examplesIf rlang::is_installed("wav")
 #' tmp <- tempfile()
 #' with_logdir(tmp, {
 #'   summary_audio(array(runif(100), dim = c(1,100, 1)))

R/tensor.R

@@ -15,20 +15,23 @@ as_tensor_proto <- function(x, dtype = NA, ...) {
   UseMethod("as_tensor_proto")
 }
 
+#' @exportS3Method
 as_tensor_proto.blob <- function(x, dtype = NA, ...) {
   if (is.na(dtype)) dtype <- "string"
   if (!dtype %in% c("string"))
     cli::cli_abort("dtype should be string when converting a blob to tensor proto.")
   tensor_proto(list(x), shape = new_tensor_shape(dim = length(x)), dtype = dtype)
 }
 
+#' @exportS3Method
 as_tensor_proto.character <- function(x, dtype = NA, ...) {
   if (is.na(dtype)) dtype <- "string"
   if (!dtype %in% c("string"))
     cli::cli_abort("dtype should be string when converting a character to tensor proto.")
   tensor_proto(list(x), shape = new_tensor_shape(dim = length(x)), dtype = dtype)
 }
 
+#' @exportS3Method
 as_tensor_proto.array <- function(x, dtype = NA, ...) {
   dims <- dim(x)
   # proto store tensor data in C ordering, thus we need to reshape values
@@ -37,6 +40,7 @@ as_tensor_proto.array <- function(x, dtype = NA, ...) {
   tensor_proto(x, shape = new_tensor_shape(dim = list(dims)), dtype = dtype)
 }
 
+#' @exportS3Method
 as_tensor_proto.list <- function(x, dtype, ...) {
   c(x, dtype) %<-% vec_recycle_common(x, dtype)
   results <- lapply(seq_along(x), function(i) {

configure

@@ -108,10 +108,17 @@ if [ ! -d "generated" ]; then
     'protoc -I "proto" --cpp_out="generated" {}' \;
 fi
 
-# copied from protolite:
-# Suppress wanrings about pragmas in the autogenerated protobuf headers.
-# Uwe + BDR have said this is OK and there is nothing we can do about this.
+# Remove pragma diagnostic directives from autogenerated protobuf headers
+# to avoid CRAN NOTEs about pragmas suppressing diagnostics.
 find ./ -type f -name "*.pb.h" -exec sed -i.bak "s@  #pragma@/*nowarn*/#pragma@g" {} \;
+find ./ -type f -name "*.pb.h" -exec sed -i.bak '/#pragma GCC diagnostic/d' {} \;
+
+# Strip [[deprecated]] and [[nodiscard]] attributes from generated protobuf
+# code to avoid compilation warnings on CRAN.
+find ./ -type f \( -name "*.pb.h" -o -name "*.pb.cc" \) -exec sed -i.bak \
+  -e 's/\[\[deprecated\]\]//g' \
+  -e 's/\[\[nodiscard\]\]//g' \
+  -e 's/enum \(.*\) : int/enum \1 : int/' {} \;
 
 PB_SRC=$(echo $(find generated -type f -name "*.pb.cc" -print))
 CPP_SRC=$(echo $(find *.cpp -print))

src/reader.cpp

@@ -45,7 +45,7 @@ tensorboard::Event EventFileIterator::get_next () {
   file.read(&buffer[0], length);
 
   tensorboard::Event event;
-  event.ParseFromString(std::string(buffer.begin(), buffer.end()));
+  (void)event.ParseFromString(std::string(buffer.begin(), buffer.end()));
 
   file.read(reinterpret_cast<char*>(&crc), sizeof(std::uint32_t));
 

tests/testthat/helper-tbparse.R

@@ -2,6 +2,12 @@ skip_if_tbparse_not_available <- function() {
   skip_if(inherits(try(reticulate::import("tbparse"), silent = TRUE), "try-error"))
 }
 
+skip_if_no_tensorflow <- function() {
+  skip_on_cran()
+  skip_if_not_installed("tensorflow")
+  skip_if(inherits(try(reticulate::import("tensorflow"), silent = TRUE), "try-error"))
+}
+
 if (inherits(try(reticulate::import("tbparse"), silent = TRUE), "try-error")) {
   tbparse <- NULL
 } else {

tests/testthat/test-audio.R

@@ -1,4 +1,5 @@
 test_that("can write an audio file", {
+  skip_if_not_installed("wav")
   f <- wav::read_wav(test_path("resources/test-audio.wav"))
   audio <- array(t(f), dim = c(1, rev(dim(f))))
 
@@ -21,6 +22,7 @@ test_that("can write an audio file", {
 })
 
 test_that("can write multiple audio files from a array", {
+  skip_if_not_installed("wav")
   f <- wav::read_wav(test_path("resources/test-audio.wav"))
   f_t <- t(f)
   audio <- array(0, dim = c(10, rev(dim(f))))

tests/testthat/test-image.R

@@ -12,6 +12,7 @@ test_that("write image", {
 
 
   skip_if_tbparse_not_available()
+  skip_if_no_tensorflow()
   reader <- tbparse$SummaryReader(temp)
   buf <- reader$tensors$value[[1]][[3]]
   # TODO: in theory we don't need tensorflow for this, but couldnt find a way to

tests/testthat/test-read.R

@@ -81,6 +81,7 @@ test_that("can iterate over events", {
 })
 
 test_that("can extract value", {
+  skip_if_not_installed("wav")
 
   temp <- tempfile()