Merge pull request #1395 from rstudio/update-guides

Update guides

R/image-utils.R

@@ -1,11 +1,11 @@
 
-#' Saves an image stored as a NumPy array to a path or file object.
+#' Saves an image stored as an array to a path or file object.
 #'
 #' @param path
 #' Path or file object.
 #'
 #' @param x
-#' NumPy array.
+#' An array.
 #'
 #' @param data_format
 #' Image data format, either `"channels_first"` or

R/model-training.R

@@ -884,7 +884,7 @@ function(x,
          line_length = getOption("width"), # width - (12L * show_trainable),
          positions = NULL,
          expand_nested = FALSE,
-         show_trainable = x$built && as.logical(length(x$non_trainable_weights)),
+         show_trainable = NA,
          ...,
          # width = getOption("width"),
          # rich = TRUE, ??
@@ -898,6 +898,11 @@ function(x,
     args <- capture_args(ignore = c("x", "compact", "width"),
                           force = c("show_trainable", "line_length"))
 
+    if(is.na(args$show_trainable)) {
+      built <- as_r_value(py_get_attr(x, "built", silent = TRUE)) %||% FALSE
+      args$show_trainable <- built && as.logical(length(x$non_trainable_weights))
+    }
+
     # Do we need to check for model$built before calling summary?
     with_rich_config(
       out <- trimws(py_capture_output(do.call(x$summary, args)))

R/py-classes.R

@@ -34,7 +34,7 @@ function(classname,
          inherit = NULL,
          parent_env = parent.frame(),
          private = list(),
-         modifiers = quote(expr =),
+         # modifiers = quote(expr =),
          default_formals = function(...) {})
 {
   # force all new_py_type() args
@@ -63,10 +63,10 @@ function(classname,
   frmls$self <- NULL
 
   bdy <- bquote({
-    args <- capture_args(.(modifiers), enforce_all_dots_named = FALSE)
+    args <- capture_args(enforce_all_dots_named = FALSE) # .(modifiers),
     do.call(.(as.name(classname)), args)
   })
-  rm(modifiers, default_formals) # free memory
+  rm(default_formals) # free memory ; rm(modifiers)
 
   as.function.default(c(frmls, bdy))
 }
@@ -431,18 +431,24 @@ py_func2 <- function(fn, convert, name = deparse(substitute(fn))) {
   pass_sig <- iterate(sig$parameters$values(), function(p) {
     if(p$kind == inspect$Parameter$POSITIONAL_ONLY)
       p$name
+    else if (p$kind == inspect$Parameter$POSITIONAL_OR_KEYWORD)
+    # pass as positional, since there might be a positional args collector up ahead, and
+    # having kwargs before a positional collector is illegal
+      p$name
     else if (p$kind == inspect$Parameter$VAR_POSITIONAL)
      paste0("*", p$name)
     else if (p$kind == inspect$Parameter$VAR_KEYWORD)
      paste0("**", p$name)
-    else
+    else if(p$kind == inspect$Parameter$KEYWORD_ONLY)
      paste0(p$name, "=", p$name)
+    else
+      stop("Unrecognized function argument type: ", p$name)
   })
   pass_sig <- paste0(pass_sig, collapse = ", ")
   code <- glue::glue("
-def wrap_fn(_fn):
+def wrap_fn(r_fn):
   def {name}{py_str(sig)}:
-    return _fn({pass_sig})
+    return r_fn({pass_sig})
   return {name}
   ")
   util <- reticulate::py_run_string(code, local = TRUE, convert = convert)

R/utils.R

@@ -635,8 +635,10 @@ function(x,
                         force = c("show_layer_names"))
   args$model <- x
 
-  if(is.na(show_trainable))
-    show_trainable <- x$built && as.logical(length(x$non_trainable_weights))
+  if (is.na(show_trainable)) {
+    built <- as_r_value(py_get_attr(x, "built", silent = TRUE)) %||% FALSE
+    show_trainable <- built && as.logical(length(x$non_trainable_weights))
+  }
   args$show_trainable <- show_trainable
 
   if (is.null(to_file)) {