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Commitd728d31

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authored
Merge pull request#1527 from rstudio/fixes
Fixes for JAX updates
2 parents0f4a4fa +616740f commitd728d31

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11 files changed

+69
-15
lines changed

11 files changed

+69
-15
lines changed

‎NAMESPACE‎

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@@ -12,6 +12,7 @@ S3method("[[",python.builtin.super)
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S3method("[[",python_builtin_super_getter)
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S3method(Arg,keras.src.backend.Tensor)
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S3method(Arg,keras.src.backend.common.keras_tensor.KerasTensor)
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S3method(Ops,jax._src.export.shape_poly._DimExpr)
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S3method(Summary,keras_shape)
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S3method(all,equal.numpy.ndarray)
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S3method(as.array,jax.Array)
@@ -40,6 +41,7 @@ S3method(as.numeric,keras.src.backend.common.variables.KerasVariable)
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S3method(base::all.equal,keras.src.backend.Tensor)
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S3method(base::all.equal,keras.src.backend.common.keras_tensor.KerasTensor)
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S3method(base::all.equal,keras.src.backend.common.variables.KerasVariable)
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S3method(base::as.array,PIL.Image.Image)
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S3method(compile,keras.src.models.model.Model)
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S3method(destructure,keras_shape)
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S3method(evaluate,keras.src.models.model.Model)

‎NEWS.md‎

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@@ -23,6 +23,8 @@
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- Added elastic deformation utilities for images:`layer_random_elastic_transform()`
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and the lower-level`op_image_elastic_transform()`.
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- Added`as.array()` support for`PIL.Image.Image` objects.
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- Transposed convolution utilities now follow the latest Keras API:
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`op_conv_transpose()` defaults`strides = 1` and the`layer_conv_*_transpose()`
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layers expose`output_padding` for precise shape control.
@@ -38,6 +40,11 @@
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-`layer_layer_normalization()` removes the`rms_scaling` argument.
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- Merging layers now capture`...` with tidy dots (fixes#1525).
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- Fixed Ops on JAX`_DimExpr` so symbolic shapes survive arithmetic with R
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double scalars.
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-`layer_reshape()` can now accept`-1` as a sentinel for an automatically calculated axis size.
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-`layer_torch_module_wrapper()` gains an`output_shape` argument to help Keras

‎R/jax-methods.R‎

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Original file line numberDiff line numberDiff line change
@@ -94,3 +94,20 @@ type_sum.keras.src.backend.jax.core.JaxVariable <- type_sum.keras.src.backend.ja
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# "keras.src.backend.Variable" too?
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# "keras.src.backend.common.variables.Variable" too?
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#' @exportS3Method Ops jax._src.export.shape_poly._DimExpr
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Ops.jax._src.export.shape_poly._DimExpr<-function(e1,e2) {
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if (missing(e2)) {
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return(e1)
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}
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conv<-function(x) {
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if (is.double(x)&& isTRUE(all(x== suppressWarnings(as.integer(x))))) {
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storage.mode(x)<-"integer"
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}
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x
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}
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e1<- conv(e1)
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e2<- conv(e2)
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NextMethod()
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}
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‎R/layers-merging.R‎

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Original file line numberDiff line numberDiff line change
@@ -52,7 +52,7 @@ function (inputs, ...)
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args<- capture_args(list(input_shape=normalize_shape,
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batch_size=as_integer,batch_input_shape=normalize_shape),
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ignore= c("...","inputs"))
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dots<- split_dots_named_unnamed(list(...))
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dots<- split_dots_named_unnamed(list2(...))
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if (missing(inputs))
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inputs<-NULL
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elseif (!is.null(inputs)&&!is.list(inputs))
@@ -116,7 +116,7 @@ function (inputs, ...)
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args<- capture_args(list(input_shape=normalize_shape,
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batch_size=as_integer,batch_input_shape=normalize_shape),
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ignore= c("...","inputs"))
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dots<- split_dots_named_unnamed(list(...))
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dots<- split_dots_named_unnamed(list2(...))
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if (missing(inputs))
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inputs<-NULL
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elseif (!is.null(inputs)&&!is.list(inputs))
@@ -177,7 +177,7 @@ function (inputs, ..., axis = -1L)
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args<- capture_args(list(axis=as_axis,input_shape=normalize_shape,
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batch_size=as_integer,batch_input_shape=normalize_shape),
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ignore= c("...","inputs"))
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dots<- split_dots_named_unnamed(list(...))
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dots<- split_dots_named_unnamed(list2(...))
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if (missing(inputs))
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inputs<-NULL
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elseif (!is.null(inputs)&&!is.list(inputs))
@@ -260,7 +260,7 @@ function (inputs, ..., axes, normalize = FALSE)
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args<- capture_args(list(axes=as_axis,input_shape=normalize_shape,
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batch_size=as_integer,batch_input_shape=normalize_shape),
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ignore= c("...","inputs"))
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dots<- split_dots_named_unnamed(list(...))
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dots<- split_dots_named_unnamed(list2(...))
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if (missing(inputs))
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inputs<-NULL
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elseif (!is.null(inputs)&&!is.list(inputs))
@@ -322,7 +322,7 @@ function (inputs, ...)
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args<- capture_args(list(input_shape=normalize_shape,
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batch_size=as_integer,batch_input_shape=normalize_shape),
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ignore= c("...","inputs"))
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dots<- split_dots_named_unnamed(list(...))
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dots<- split_dots_named_unnamed(list2(...))
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if (missing(inputs))
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inputs<-NULL
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elseif (!is.null(inputs)&&!is.list(inputs))
@@ -384,7 +384,7 @@ function (inputs, ...)
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args<- capture_args(list(input_shape=normalize_shape,
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batch_size=as_integer,batch_input_shape=normalize_shape),
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ignore= c("...","inputs"))
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dots<- split_dots_named_unnamed(list(...))
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dots<- split_dots_named_unnamed(list2(...))
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if (missing(inputs))
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inputs<-NULL
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elseif (!is.null(inputs)&&!is.list(inputs))
@@ -446,7 +446,7 @@ function (inputs, ...)
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args<- capture_args(list(input_shape=normalize_shape,
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batch_size=as_integer,batch_input_shape=normalize_shape),
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ignore= c("...","inputs"))
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dots<- split_dots_named_unnamed(list(...))
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dots<- split_dots_named_unnamed(list2(...))
450450
if (missing(inputs))
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inputs<-NULL
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elseif (!is.null(inputs)&&!is.list(inputs))
@@ -509,7 +509,7 @@ function (inputs, ...)
509509
args<- capture_args(list(input_shape=normalize_shape,
510510
batch_size=as_integer,batch_input_shape=normalize_shape),
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ignore= c("...","inputs"))
512-
dots<- split_dots_named_unnamed(list(...))
512+
dots<- split_dots_named_unnamed(list2(...))
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if (missing(inputs))
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inputs<-NULL
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elseif (!is.null(inputs)&&!is.list(inputs))

‎R/r-utils.R‎

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@@ -27,7 +27,9 @@ split_dots_named_unnamed <- function(dots) {
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if (is.null(nms))
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return(list(unnamed=dots,named=list()))
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named<- nzchar(nms)
30-
list(unnamed=dots[!named],named=dots[named])
30+
unnamed<-dots[!named]
31+
names(unnamed)<-NULL
32+
list(unnamed=unnamed,named=dots[named])
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}
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drop_nulls<-function(x,i=NULL) {

‎R/s3-methods.R‎

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@@ -110,3 +110,7 @@ py_to_r__keras.src.utils.tracking.TrackedSet <- function(x) import("builtins")$l
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# }
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# rm(list = c("generic", "cls"))
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113+
#' @exportS3Method base::as.array
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as.array.PIL.Image.Image<-function(x,...) {
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as.array(image_to_array(x,...))
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}

‎man/layer_discretization.Rd‎

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‎man/layer_tfsm.Rd‎

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‎man/op_angle.Rd‎

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test_that("DimExpr Ops keeps symbolic dims when R uses double scalars", {
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skip_if_not(reticulate::py_module_available("jax"))
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export<-reticulate::import("jax.export",convert=FALSE)
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dim<-export$symbolic_shape("n")[[1]]
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expr<-dim-1# 1 is a double in R; Ops method should coerce to int
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expect_s3_class(expr,"jax._src.export.shape_poly._DimExpr")
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expect_match(reticulate::py_str(expr),"n - 1")
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expect_false(any(grepl("Array", class(expr))))
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})

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