2025-12-11 14:12.48: New job: test ahrefs/ocannl https://github.com/ahrefs/ocannl.git#refs/heads/master (d0b9381a8df7c93e46fc958900deb7fee60d430f) (linux-x86_64:(lint-fmt))Base: ocaml/opam:debian-13-ocaml-4.08@sha256:e3cc4e8fe5c00f48c72a719e3551b1d8a51c2862349a0f7507e8aa29fdf72321ocamlformat version: version 0.28.1 (from opam)To reproduce locally:git clone --recursive "https://github.com/ahrefs/ocannl.git" -b "master" && cd "ocannl" && git reset --hard d0b9381acat > Dockerfile <<'END-OF-DOCKERFILE'FROM ocaml/opam:debian-13-ocaml-4.08@sha256:e3cc4e8fe5c00f48c72a719e3551b1d8a51c2862349a0f7507e8aa29fdf72321USER 1000:1000RUN cd ~/opam-repository && (git cat-file -e 6c1b38620288b5bf349067f089a7b1fc91185d94 || git fetch origin master) && git reset -q --hard 6c1b38620288b5bf349067f089a7b1fc91185d94 && git log --no-decorate -n1 --oneline && opam update -uRUN opam depext -i duneWORKDIR /srcRUN opam depext -i ocamlformat=0.28.1COPY --chown=1000:1000 . /src/RUN opam exec -- dune build @fmt --ignore-promoted-rules || (echo "dune build @fmt failed"; exit 2)END-OF-DOCKERFILEdocker build .END-REPRO-BLOCK2025-12-11 14:12.48: Using cache hint "ahrefs/ocannl-ocaml/opam:debian-13-ocaml-4.08@sha256:e3cc4e8fe5c00f48c72a719e3551b1d8a51c2862349a0f7507e8aa29fdf72321-debian-13-4.08_opam-2.4-ocamlformat-6c1b38620288b5bf349067f089a7b1fc91185d94"2025-12-11 14:12.48: Using OBuilder spec:((from ocaml/opam:debian-13-ocaml-4.08@sha256:e3cc4e8fe5c00f48c72a719e3551b1d8a51c2862349a0f7507e8aa29fdf72321)(user (uid 1000) (gid 1000))(run (cache (opam-archives (target /home/opam/.opam/download-cache)))(network host)(shell "cd ~/opam-repository && (git cat-file -e 6c1b38620288b5bf349067f089a7b1fc91185d94 || git fetch origin master) && git reset -q --hard 6c1b38620288b5bf349067f089a7b1fc91185d94 && git log --no-decorate -n1 --oneline && opam update -u"))(run (cache (opam-archives (target /home/opam/.opam/download-cache)))(network host)(shell "opam depext -i dune"))(workdir /src)(run (cache (opam-archives (target /home/opam/.opam/download-cache)))(network host)(shell "opam depext -i ocamlformat=0.28.1"))(copy (src .) (dst /src/))(run (shell "opam exec -- dune build @fmt --ignore-promoted-rules || (echo \"dune build @fmt failed\"; exit 2)")))2025-12-11 14:12.48: Waiting for resource in pool OCluster2025-12-11 14:12.48: Waiting for worker…2025-12-11 14:16.05: Got resource from pool OClusterBuilding on bremusa.ocamllabs.ioAll commits already cachedHEAD is now at d0b9381a Fix tropical g2 gradient: use RHS1 projection for both input and kernel(from ocaml/opam:debian-13-ocaml-4.08@sha256:e3cc4e8fe5c00f48c72a719e3551b1d8a51c2862349a0f7507e8aa29fdf72321)2025-12-11 14:16.25 ---> saved as "d458486dd7823c592e7ea9c88366c5f90e1939c3b51f3abbd6760272096f8a3e"/: (user (uid 1000) (gid 1000))/: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))(network host)(shell "cd ~/opam-repository && (git cat-file -e 6c1b38620288b5bf349067f089a7b1fc91185d94 || git fetch origin master) && git reset -q --hard 6c1b38620288b5bf349067f089a7b1fc91185d94 && git log --no-decorate -n1 --oneline && opam update -u"))6c1b386202 Merge pull request #28774 from Julow/release-ocamlformat-0.28.1<><> Updating package repositories ><><><><><><><><><><><><><><><><><><><><><><>[default] Initialiseddefault (at git+file:///home/opam/opam-repository):[INFO] opam 2.1 and 2.2 include many performance and security improvements over 2.0; please consider upgrading (https://opam.ocaml.org/doc/Install.html)Everything as up-to-date as possible (run with --verbose to show unavailable upgrades).However, you may "opam upgrade" these packages explicitly, which will ask permission to downgrade or uninstall the conflicting packages.Nothing to do.# Run eval $(opam env) to update the current shell environment2025-12-11 14:17.52 ---> saved as "a7d3c7d9f6aff7dc059c465a33e7ef3fda4b4a1ee9c79bef8645b5cd4da72b96"/: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))(network host)(shell "opam depext -i dune"))# Detecting depexts using vars: arch=x86_64, os=linux, os-distribution=debian, os-family=debian# No extra OS packages requirements found.# All required OS packages found.# Now letting opam install the packagesThe following actions will be performed:- install dune 3.20.2<><> Gathering sources ><><><><><><><><><><><><><><><><><><><><><><><><><><><><>[dune.3.20.2] found in cache<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>-> installed dune.3.20.2Done.# Run eval $(opam env) to update the current shell environment2025-12-11 14:18.48 ---> saved as "b8799a0f87a66bd49a9341889a0027044c03db80ad17a5edb3adaf72f166d8fd"/: (workdir /src)/src: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))(network host)(shell "opam depext -i ocamlformat=0.28.1"))# Detecting depexts using vars: arch=x86_64, os=linux, os-distribution=debian, os-family=debian# No extra OS packages requirements found.# All required OS packages found.# Now letting opam install the packagesThe following actions will be performed:- install sexplib0 v0.14.0 [required by base]- install ocamlbuild 0.16.1 [required by fpath, astring, uuseg]- install either 1.0.0 [required by ocamlformat-lib]- install menhirLib 20250912 [required by ocamlformat-lib]- install csexp 1.5.2 [required by ocamlformat]- install camlp-streams 5.0.1 [required by ocamlformat-lib]- install seq base [required by re]- install menhirSdk 20250912 [required by ocamlformat-lib]- install fix 20250919 [required by ocamlformat-lib]- install menhirCST 20250912 [required by menhir]- install ocamlfind 1.9.8 [required by ocp-indent, astring, fpath, uuseg]- install dune-build-info 3.20.2 [required by ocamlformat-lib]- install cmdliner 2.0.0 [required by ocamlformat]- install ocaml-version 4.0.3 [required by ocamlformat-lib]- install dune-configurator 3.20.2 [required by base]- install re 1.11.0 [required by ocamlformat]- install menhir 20250912 [required by ocamlformat-lib]- install topkg 1.1.1 [required by fpath, astring, uuseg]- install ocp-indent 1.9.0 [required by ocamlformat-lib]- install base v0.14.3 [required by ocamlformat-lib]- install uutf 1.0.4 [required by ocamlformat-lib]- install astring 0.8.5 [required by ocamlformat-lib]- install stdio v0.14.0 [required by ocamlformat-lib]- install uucp 15.0.0 [required by uuseg]- install fpath 0.7.3 [required by ocamlformat-lib]- install uuseg 15.0.0 [required by ocamlformat-lib]- install ocamlformat-lib 0.28.1 [required by ocamlformat]- install ocamlformat 0.28.1===== 28 to install =====<><> Gathering sources ><><><><><><><><><><><><><><><><><><><><><><><><><><><><>[astring.0.8.5] found in cache[base.v0.14.3] found in cache[camlp-streams.5.0.1] found in cache[cmdliner.2.0.0] found in cache[csexp.1.5.2] found in cache[dune-build-info.3.20.2] found in cache[dune-configurator.3.20.2] found in cache[either.1.0.0] found in cache[fix.20250919] found in cache[fpath.0.7.3] found in cache[menhir.20250912] found in cache[menhirCST.20250912] found in cache[menhirLib.20250912] found in cache[menhirSdk.20250912] found in cache[ocaml-version.4.0.3] found in cache[ocamlbuild.0.16.1] found in cache[ocamlfind.1.9.8] found in cache[ocamlformat.0.28.1] found in cache[ocamlformat-lib.0.28.1] found in cache[ocp-indent.1.9.0] found in cache[re.1.11.0] found in cache[sexplib0.v0.14.0] found in cache[stdio.v0.14.0] found in cache[topkg.1.1.1] found in cache[uucp.15.0.0] found in cache[uuseg.15.0.0] found in cache[uutf.1.0.4] found in cache<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>-> installed seq.base-> installed camlp-streams.5.0.1-> installed csexp.1.5.2-> installed either.1.0.0-> installed fix.20250919-> installed menhirCST.20250912-> installed menhirLib.20250912-> installed menhirSdk.20250912-> installed ocaml-version.4.0.3-> installed sexplib0.v0.14.0-> installed re.1.11.0-> installed cmdliner.2.0.0-> installed dune-build-info.3.20.2-> installed ocamlfind.1.9.8-> installed dune-configurator.3.20.2-> installed ocp-indent.1.9.0-> installed ocamlbuild.0.16.1-> installed base.v0.14.3-> installed topkg.1.1.1-> installed stdio.v0.14.0-> installed uutf.1.0.4-> installed astring.0.8.5-> installed menhir.20250912-> installed fpath.0.7.3-> installed uucp.15.0.0-> installed uuseg.15.0.0-> installed ocamlformat-lib.0.28.1-> installed ocamlformat.0.28.1Done.<><> ocp-indent.1.9.0 installed successfully ><><><><><><><><><><><><><><><><><>=> This package requires additional configuration for use in editors. Install package 'user-setup', or manually:* for Emacs, add these lines to ~/.emacs:(add-to-list 'load-path "/home/opam/.opam/4.08/share/emacs/site-lisp")(require 'ocp-indent)* for Vim, add this line to ~/.vimrc:set rtp^="/home/opam/.opam/4.08/share/ocp-indent/vim"# Run eval $(opam env) to update the current shell environment2025-12-11 14:20.30 ---> saved as "7b71439e6ac9917292b28dc59ecc075d01d03dd2ef11c372809a6cf99e594a22"/src: (copy (src .) (dst /src/))2025-12-11 14:20.31 ---> saved as "7cf2eb1bebb4cea802636c5a3de52dfb0e1db000f452a2d4313ec1691ce9e996"/src: (run (shell "opam exec -- dune build @fmt --ignore-promoted-rules || (echo \"dune build @fmt failed\"; exit 2)"))File "test/einsum/dune", line 1, characters 0-0:diff --git a/_build/default/test/einsum/dune b/_build/default/test/einsum/.formatted/duneindex 4e0d487..b6f3980 100644--- a/_build/default/test/einsum/dune+++ b/_build/default/test/einsum/.formatted/dune@@ -163,7 +163,8 @@(pps ppx_here ppx_ocannl)); Disable virtualization because tropical backprop uses input-shaped tensors; with affine indices like 2*oh+wh, which virtualization doesn't yet support.- (action (run %{test} --ocannl_virtualize_max_visits=0)))+ (action+ (run %{test} --ocannl_virtualize_max_visits=0)))(test(name test_tropical_kernel)@@ -177,4 +178,5 @@(pps ppx_here ppx_ocannl)); Disable virtualization because tropical backprop uses input-shaped tensors; with affine indices like 2*oh+wh, which virtualization doesn't yet support.- (action (run %{test} --ocannl_virtualize_max_visits=0)))+ (action+ (run %{test} --ocannl_virtualize_max_visits=0)))Warning: Invalid documentation comment:File "tensor/einsum_types.ml", line 38, characters 0-0:End of text is not allowed in '[...]' (code).File "datasets/circles.ml", line 1, characters 0-0:diff --git a/_build/default/datasets/circles.ml b/_build/default/datasets/.formatted/circles.mlindex 1c640a3..4fae3df 100644--- a/_build/default/datasets/circles.ml+++ b/_build/default/datasets/.formatted/circles.ml@@ -11,21 +11,19 @@ module Config = structseed : int option; (** Optional random seed for reproducibility *)}- let default =- { image_size = 32; max_radius = 8; min_radius = 2; max_circles = 5; seed = None }+ let default = { image_size = 32; max_radius = 8; min_radius = 2; max_circles = 5; seed = None }endmodule Random = Rand.Random_for_tests-(** Draw a filled circle on the image at (cx, cy) with radius r.- Values are clamped to [0, 1] range. *)+(** Draw a filled circle on the image at (cx, cy) with radius r. Values are clamped to [0, 1] range.+*)let draw_circle ~image_size image cx cy r =for y = 0 to image_size - 1 dofor x = 0 to image_size - 1 dolet dx = x - cx inlet dy = y - cy in- if (dx * dx) + (dy * dy) <= r * r then- Genarray.set image [| y; x; 0 |] 1.0+ if (dx * dx) + (dy * dy) <= r * r then Genarray.set image [| y; x; 0 |] 1.0donedone@@ -36,7 +34,8 @@ let draw_circle ~image_size image cx cy r =@param len Number of images to generate@returnA tuple of (images, labels) where:- - images is a bigarray of shape [len; image_size; image_size; 1] (batch, height, width, channels)+ - images is a bigarray of shape [len; image_size; image_size; 1] (batch, height, width,+ channels)- labels is a bigarray of shape [len; 1] (batch, output) containing the circle count *)let generate_with_kind kind ?(config = Config.default) ~len () =(match config.seed with Some seed -> Random.init seed | None -> ());File "datasets/rand.ml", line 1, characters 0-0:diff --git a/_build/default/datasets/rand.ml b/_build/default/datasets/.formatted/rand.mlindex 22f8f7f..84ab9a6 100644--- a/_build/default/datasets/rand.ml+++ b/_build/default/datasets/.formatted/rand.ml@@ -24,6 +24,7 @@ module Random_for_tests : Random = struct(raw /. 10000. *. (high -. low)) +. lowlet char () = Char.chr @@ Int32.(to_int @@ rem (rand_int32 ()) 256l)+let int high =(* Use abs to handle negative random values from xor-shift RNG *)Int32.(to_int @@ rem (abs (rand_int32 ())) @@ of_int high)File "tensor/einsum_types.ml", line 1, characters 0-0:diff --git a/_build/default/tensor/einsum_types.ml b/_build/default/tensor/.formatted/einsum_types.mlindex 084d9ac..e357e66 100644--- a/_build/default/tensor/einsum_types.ml+++ b/_build/default/tensor/.formatted/einsum_types.ml@@ -4,18 +4,16 @@open Base-(** Use_padding specification for convolutions. *)type use_padding_spec = [ `True | `False | `Unspecified ] [@@deriving compare, sexp]+(** Use_padding specification for convolutions. *)-(** Convolution component for affine axis specifications.- Note: [dilation] is a string because it can be an identifier at parse time,- and is resolved to an int at runtime. *)type conv_spec = { dilation : string; kernel_label : string; use_padding : use_padding_spec }[@@deriving compare, sexp]+(** Convolution component for affine axis specifications. Note: [dilation] is a string because it+ can be an identifier at parse time, and is resolved to an int at runtime. *)-(** Specification for individual axes in the einsum notation.- Note: [stride] is a string because it can be an identifier at parse time,- and is resolved to an int at runtime. *)+(** Specification for individual axes in the einsum notation. Note: [stride] is a string because it+ can be an identifier at parse time, and is resolved to an int at runtime. *)type axis_spec =| Label of string (** A variable axis label. *)| Fixed_index of int (** A fixed index, used for projection. *)@@ -25,8 +23,8 @@ type axis_spec =conv : conv_spec option; (** Optional convolution: dilation*kernel. *)stride_offset : int; (** Constant offset added after stride*over. *)}- (** Affine axis specification: stride*over + stride_offset [+ dilation*kernel].- Corresponds to [Row.Affine] in shape inference. *)+ (** Affine axis specification: stride*over + stride_offset [+ dilation*kernel]. Corresponds to+ [Row.Affine] in shape inference. *)[@@deriving compare, sexp](** An index pointing to any of a shape's axes, including the kind of the axis ([Batch, Input,@@ -75,8 +73,8 @@ type parsed_axis_labels = {(** The labels are strings assigned to [AxisKey] axes. Moreover the [bcast_] fields representwhether additional leading/middle axes are allowed (corresponding to the dot-ellipsis syntax forbroadcasting). The string can be used to identify a row variable, and defaults to ["batch"],- ["input"], ["output"] respectively when parsing ["..."]. The [given_] fields are lists of- axis specs of the corresponding kind in [labels] where [from_end=true], [given_beg_] where+ ["input"], ["output"] respectively when parsing ["..."]. The [given_] fields are lists of axis+ specs of the corresponding kind in [labels] where [from_end=true], [given_beg_] where[from_end=false]. *)let axis_labels parsed = parsed.labelsFile "tensor/shape.mli", line 1, characters 0-0:diff --git a/_build/default/tensor/shape.mli b/_build/default/tensor/.formatted/shape.mliindex d7533f0..b3e6eba 100644--- a/_build/default/tensor/shape.mli+++ b/_build/default/tensor/.formatted/shape.mli@@ -49,8 +49,9 @@Adding [<] after the output label (e.g., [stride*output<+kernel]) indicates no-padding mode,where indices must stay within the input bounds. In this mode, the input dimension must satisfy:- [(input - effective_kernel_span) mod stride = 0], where [effective_kernel_span = 1 + (kernel - 1) * dilation].- Without [<], padding is applied and there is no such divisibility constraint.+ [(input - effective_kernel_span) mod stride = 0], where+ [effective_kernel_span = 1 + (kernel - 1) * dilation]. Without [<], padding is applied and there+ is no such divisibility constraint.Note: currently, OCANNL shapes always allow broadcasting. Row variables track the broadcastedaxes -- if there is no row variable, broadcasted axes are not tracked. In the notation case@@ -242,9 +243,9 @@ val to_padding : t -> (Ir.Ops.axis_padding array * float) optionval propagate_shapes : update_step -> unitval get_projections : update_step -> Ir.Indexing.projections-(** Returns the projections for this update step, computing them if not already done.- This triggers [finish_inference] and then retrieves the projections from- [unsafe_projections]. Use this instead of [derive_projections] directly. *)+(** Returns the projections for this update step, computing them if not already done. This triggers+ [finish_inference] and then retrieves the projections from [unsafe_projections]. Use this+ instead of [derive_projections] directly. *)val of_spec : ?deduced:deduce_within_shape -> debug_name:string -> id:int -> string -> tval default_display_indices : t -> int array@@ -253,5 +254,5 @@ val to_labels : t -> string array(** Uses the matrix convention of putting the input axes last. *)val parse_n5_layout : string -> int array-(** Parse a N5_layout priority string (e.g., "0,1,2") into display indices.- Only supports integer labels (Fixed_index). *)+(** Parse a N5_layout priority string (e.g., "0,1,2") into display indices. Only supports integer+ labels (Fixed_index). *)File "lib/nn_blocks.ml", line 1, characters 0-0:diff --git a/_build/default/lib/nn_blocks.ml b/_build/default/lib/.formatted/nn_blocks.mlindex 470123e..ace55f8 100644--- a/_build/default/lib/nn_blocks.ml+++ b/_build/default/lib/.formatted/nn_blocks.ml@@ -231,8 +231,9 @@ let%op transformer_with_loss ~label:_ ~model () ~train_step ~src ~tgt_input ~tgtWhen [use_padding=true], there is no such restriction and output size is [input_size / stride].- @param out_channels Optional number of output channels. If not provided, must be inferred from- context (e.g., from a downstream operation that constrains the output shape). *)+ @param out_channels+ Optional number of output channels. If not provided, must be inferred from context (e.g., from+ a downstream operation that constrains the output shape). *)let%op conv2d ~label ?(kernel_size = 3) ?(stride = 1) ?(use_padding = true) ?out_channels () x =(* Notation: kernel height (kh), kernel width (kw), input channels (ic), output channels (oc),output height (oh), output width (ow) *)@@ -268,7 +269,8 @@ let%op depthwise_separable_conv2d ~label ?(kernel_size = 3) ?(stride = 1) ?(use_(** Max pooling for 2D spatial data - reduces spatial dimensions by taking maximum values.The input spatial dimensions must satisfy: [(input_size - window_size) mod stride = 0],- otherwise shape inference will fail. The output size is [(input_size - window_size) / stride + 1].+ otherwise shape inference will fail. The output size is+ [(input_size - window_size) / stride + 1].Note: The [<] in the einsum spec indicates no-padding mode (indices stay within bounds). *)let%op max_pool2d ?(stride = 2) ?(window_size = 2) () x =File "test/einsum/test_einsum_parser.ml", line 1, characters 0-0:diff --git a/_build/default/test/einsum/test_einsum_parser.ml b/_build/default/test/einsum/.formatted/test_einsum_parser.mlindex c305169..ac88c8a 100644--- a/_build/default/test/einsum/test_einsum_parser.ml+++ b/_build/default/test/einsum/.formatted/test_einsum_parser.ml@@ -12,8 +12,7 @@ let test_single_char () =(* Test 2: With batch and input *)let spec2 = "b|i->o" inlet labels2 = Einsum_parser.axis_labels_of_spec spec2 in- printf " 'b|i->o' -> batch:%d input:%d output:%d\n"- (List.length labels2.given_batch)+ printf " 'b|i->o' -> batch:%d input:%d output:%d\n" (List.length labels2.given_batch)(List.length labels2.given_input)(List.length labels2.given_output);@@ -21,13 +20,9 @@ let test_single_char () =let spec3 = "ij;jk=>ik" inlet l1, l2_opt, l3 = Einsum_parser.einsum_of_spec spec3 inlet l2 = Option.value_exn l2_opt in- printf " 'ij;jk=>ik' -> (%d,%d);(%d,%d)=>(%d,%d)\n"- (List.length l1.given_input)- (List.length l1.given_output)- (List.length l2.given_input)- (List.length l2.given_output)- (List.length l3.given_input)- (List.length l3.given_output);+ printf " 'ij;jk=>ik' -> (%d,%d);(%d,%d)=>(%d,%d)\n" (List.length l1.given_input)+ (List.length l1.given_output) (List.length l2.given_input) (List.length l2.given_output)+ (List.length l3.given_input) (List.length l3.given_output);printf "\n"File "test/einsum/test_conv_padding.ml", line 1, characters 0-0:diff --git a/_build/default/test/einsum/test_conv_padding.ml b/_build/default/test/einsum/.formatted/test_conv_padding.mlindex 2415a61..bbdc511 100644--- a/_build/default/test/einsum/test_conv_padding.ml+++ b/_build/default/test/einsum/.formatted/test_conv_padding.ml@@ -128,16 +128,15 @@ let test_conv2d_stride_with_padding_backprop () =(** Test conv2d with stride=2 and use_padding=false.- With stride=2 and use_padding=false, output dims are (input - kernel) / stride + 1.- IMPORTANT: For no-padding convolutions, (input - kernel) must be divisible by stride.- For 9x9 input, kernel_size=3, stride=2: (9-3)/2 + 1 = 4, so output should be 4x4. *)+ With stride=2 and use_padding=false, output dims are (input - kernel) / stride + 1. IMPORTANT:+ For no-padding convolutions, (input - kernel) must be divisible by stride. For 9x9 input,+ kernel_size=3, stride=2: (9-3)/2 + 1 = 4, so output should be 4x4. *)let test_conv2d_stride_without_padding () =printf "Testing conv2d with stride=2 and use_padding=false...\n%!";Tensor.unsafe_reinitialize ();- (* Create a 9x9 input with 1 channel - sized for stride=2, kernel=3 without padding.- For no-padding conv: (input - kernel) must be divisible by stride.- (9 - 3) = 6, 6 % 2 = 0 ✓ *)+ (* Create a 9x9 input with 1 channel - sized for stride=2, kernel=3 without padding. For+ no-padding conv: (input - kernel) must be divisible by stride. (9 - 3) = 6, 6 % 2 = 0 ✓ *)let input = TDSL.range_of_shape ~output_dims:[ 9; 9; 1 ] () in(* Apply conv2d with kernel_size=3, stride=2, use_padding=false, out_channels=4 *)@@ -164,16 +163,15 @@ let test_conv2d_stride_without_padding () =This tests that shape inference works correctly during backpropagation for strided convolutionswithout padding.- IMPORTANT: For no-padding convolutions, (input - kernel) must be divisible by stride,- otherwise shape inference will fail with "incompatible stride" error. *)+ IMPORTANT: For no-padding convolutions, (input - kernel) must be divisible by stride, otherwise+ shape inference will fail with "incompatible stride" error. *)let test_conv2d_stride_without_padding_backprop () =printf "\nTesting backprop for conv2d with stride=2 and use_padding=false...\n%!";Tensor.unsafe_reinitialize ();- (* Create a 9x9 input with 1 channel - sized for stride=2, kernel=3 without padding.- For no-padding conv: (input - kernel) must be divisible by stride.- (9 - 3) = 6, 6 % 2 = 0 ✓- Output size: (9 - 3) / 2 + 1 = 4, so 4x4 output. *)+ (* Create a 9x9 input with 1 channel - sized for stride=2, kernel=3 without padding. For+ no-padding conv: (input - kernel) must be divisible by stride. (9 - 3) = 6, 6 % 2 = 0 ✓ Output+ size: (9 - 3) / 2 + 1 = 4, so 4x4 output. *)let input = TDSL.range_of_shape ~output_dims:[ 9; 9; 1 ] () in(* Apply conv2d with kernel_size=3, stride=2, use_padding=false, out_channels=4 *)File "test/einsum/test_max_pool2d.ml", line 1, characters 0-0:diff --git a/_build/default/test/einsum/test_max_pool2d.ml b/_build/default/test/einsum/.formatted/test_max_pool2d.mlindex 2e44dd4..b4415ec 100644--- a/_build/default/test/einsum/test_max_pool2d.ml+++ b/_build/default/test/einsum/.formatted/test_max_pool2d.ml@@ -133,13 +133,11 @@ let test_max_pool2d_backprop () =printf "\nTesting backprop for max_pool2d...\n%!";Tensor.unsafe_reinitialize ();- (* Create a 4x4 input with 1 channel using a parameter (requires grad).- Design: each 2x2 window has its max in a different position:- Window positions: (row within window, col within window)- - Top-left window [0-1, 0-1]: max 9 at (0,0)- - Top-right window [0-1, 2-3]: max 8 at (1,1)- - Bottom-left window [2-3, 0-1]: max 7 at (0,1)- - Bottom-right window [2-3, 2-3]: max 6 at (1,0) *)+ (* Create a 4x4 input with 1 channel using a parameter (requires grad). Design: each 2x2 window+ has its max in a different position: Window positions: (row within window, col within window) -+ Top-left window [0-1, 0-1]: max 9 at (0,0) - Top-right window [0-1, 2-3]: max 8 at (1,1) -+ Bottom-left window [2-3, 0-1]: max 7 at (0,1) - Bottom-right window [2-3, 2-3]: max 6 at+ (1,0) *)let%op input ={x =File "test/training/circles_conv.ml", line 1, characters 0-0:diff --git a/_build/default/test/training/circles_conv.ml b/_build/default/test/training/.formatted/circles_conv.mlindex fb025c0..357625f 100644--- a/_build/default/test/training/circles_conv.ml+++ b/_build/default/test/training/.formatted/circles_conv.ml@@ -1,7 +1,7 @@(** Circle counting training test using synthetic dataset.- This test trains a model to classify images by the number of circles they contain.- Uses cross-entropy loss for classification.+ This test trains a model to classify images by the number of circles they contain. Uses+ cross-entropy loss for classification.{2 Known Issues with conv2d in Training}@@ -17,8 +17,8 @@hidden dimension(s)" errors during SGD update compilation, as the gradient tensors cannotdetermine their shapes.- 3. {b Workaround}: Use an MLP instead - OCANNL's matrix multiplication handles- multi-dimensional inputs automatically without explicit flattening.+ 3. {b Workaround}: Use an MLP instead - OCANNL's matrix multiplication handles multi-dimensional+ inputs automatically without explicit flattening.These issues suggest that [conv2d] may need:- An explicit [out_channels] parameter to constrain output shape@@ -44,7 +44,8 @@ let () =(* Configuration for circle dataset *)let image_size = 16 inlet max_circles = 3 in- let num_classes = max_circles in (* Classes: 1, 2, 3 circles -> indices 0, 1, 2 *)+ let num_classes = max_circles in+ (* Classes: 1, 2, 3 circles -> indices 0, 1, 2 *)let config =Datasets.Circles.Config.{ image_size; max_radius = 4; min_radius = 2; max_circles; seed = Some seed }@@ -83,9 +84,10 @@ let () =let%op batch_images = images @| batch_n inlet%op batch_labels = labels_one_hot @| batch_n in- (* Try lenet - this will likely fail due to conv2d shape inference issues.- Fallback to MLP if needed. *)- let use_lenet = false in (* Set to true to test lenet - currently fails *)+ (* Try lenet - this will likely fail due to conv2d shape inference issues. Fallback to MLP if+ needed. *)+ let use_lenet = false in+ (* Set to true to test lenet - currently fails *)let logits =if use_lenet then (@@ -111,7 +113,6 @@ let () =let%op sample_loss = neg (log correct_prob) inlet%op batch_loss = (sample_loss ++ "...|... => 0") /. !..batch_size in-(* Training setup *)let epochs = 10 inlet total_steps = epochs * n_batches in@@ -133,7 +134,6 @@ let () =printf "\nStarting training for %d epochs (%d steps)...\n%!" epochs total_steps;let open Operation.At in-for epoch = 1 to epochs dolet epoch_loss = ref 0. inTrain.sequential_loop (Context.bindings sgd_routine) ~f:(fun () ->File "test/einsum/test_conv_syntax.ml", line 1, characters 0-0:diff --git a/_build/default/test/einsum/test_conv_syntax.ml b/_build/default/test/einsum/.formatted/test_conv_syntax.mlindex bb97681..028dbb4 100644--- a/_build/default/test/einsum/test_conv_syntax.ml+++ b/_build/default/test/einsum/.formatted/test_conv_syntax.ml@@ -8,43 +8,50 @@ let test_conv_parsing () =let spec1 = "2*o+3*k" inlet labels1 = Einsum_parser.axis_labels_of_spec spec1 inprintf "Test 1: Parsed '%s' successfully\n%!" spec1;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels1));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels1));(* Test 2: Simple conv expression without coefficients (multichar - requires commas) *)let spec2 = "o+k" inlet labels2 = Einsum_parser.axis_labels_of_spec spec2 inprintf "Test 2: Parsed '%s' successfully\n%!" spec2;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels2));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels2));(* Test 3: Mixed spec with comma (multichar mode) *)let spec3 = "a, 2*b+c" inlet labels3 = Einsum_parser.axis_labels_of_spec spec3 inprintf "Test 3: Parsed '%s' successfully\n%!" spec3;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels3));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels3));(* Test 4: Conv expression with multiple identifiers (multichar - requires commas) *)let spec4 = "i, o+k, j" inlet labels4 = Einsum_parser.axis_labels_of_spec spec4 inprintf "Test 4: Parsed '%s' successfully (multichar mode)\n%!" spec4;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels4));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels4));(* Test 5: Conv expression with multi-char identifiers (multichar) *)let spec5 = "a+bc" inlet labels5 = Einsum_parser.axis_labels_of_spec spec5 inprintf "Test 5: Parsed '%s' successfully (multichar mode)\n%!" spec5;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels5));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels5));(* Test 6: Test in einsum notation with multichar conv *)let spec6 = "i, j -> 2*i+j" inlet labels6 = Einsum_parser.axis_labels_of_spec spec6 inprintf "Test 6: Parsed '%s' successfully\n%!" spec6;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels6));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels6));(* Test 7: Complex batch-input-output spec with conv *)let spec7 = "batch|input->3*output+1*kernel," inlet labels7 = Einsum_parser.axis_labels_of_spec spec7 inprintf "Test 7: Parsed '%s' successfully\n%!" spec7;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels7));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels7));printf "All conv syntax parsing tests passed!\n%!"@@ -55,25 +62,29 @@ let test_strided_iteration_parsing () =let spec1 = "2*output" inlet labels1 = Einsum_parser.axis_labels_of_spec spec1 inprintf "Test 1: Parsed strided iteration '%s' successfully\n%!" spec1;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels1));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels1));(* Test 2: Strided iteration with single-char identifier (multichar mode) *)let spec2 = "3*i" inlet labels2 = Einsum_parser.axis_labels_of_spec spec2 inprintf "Test 2: Parsed strided iteration '%s' successfully\n%!" spec2;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels2));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels2));(* Test 3: Strided iteration in einsum context (multichar due to multiplication) *)let spec3 = "input -> 2*output" inlet labels3 = Einsum_parser.axis_labels_of_spec spec3 inprintf "Test 3: Parsed einsum with strided iteration '%s' successfully\n%!" spec3;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels3));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels3));(* Test 4: Mixed regular labels and strided iteration (multichar due to comma) *)let spec4 = "regular, 3*strided" inlet labels4 = Einsum_parser.axis_labels_of_spec spec4 inprintf "Test 4: Parsed mixed labels with strided iteration '%s' successfully\n%!" spec4;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels4));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels4));printf "\nAll strided iteration parsing tests completed!\n%!"@@ -138,37 +149,43 @@ let test_use_padding_syntax () =let spec1 = "o=+k" inlet labels1 = Einsum_parser.axis_labels_of_spec spec1 inprintf "Test 1: Parsed '%s' (use_padding=true)\n%!" spec1;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels1));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels1));(* Test 2: use_padding=false with < syntax *)let spec2 = "o<+k" inlet labels2 = Einsum_parser.axis_labels_of_spec spec2 inprintf "Test 2: Parsed '%s' (use_padding=false)\n%!" spec2;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels2));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels2));(* Test 3: use_padding with stride *)let spec3 = "2*o=+k" inlet labels3 = Einsum_parser.axis_labels_of_spec spec3 inprintf "Test 3: Parsed '%s' (stride with use_padding=true)\n%!" spec3;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels3));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels3));(* Test 4: use_padding with dilation *)let spec4 = "o<+3*k" inlet labels4 = Einsum_parser.axis_labels_of_spec spec4 inprintf "Test 4: Parsed '%s' (dilation with use_padding=false)\n%!" spec4;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels4));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels4));(* Test 5: use_padding with stride and dilation *)let spec5 = "2*o=+3*k" inlet labels5 = Einsum_parser.axis_labels_of_spec spec5 inprintf "Test 5: Parsed '%s' (stride, dilation, use_padding=true)\n%!" spec5;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels5));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels5));(* Test 6: unspecified use_padding (legacy syntax) *)let spec6 = "o+k" inlet labels6 = Einsum_parser.axis_labels_of_spec spec6 inprintf "Test 6: Parsed '%s' (unspecified use_padding)\n%!" spec6;- printf " Structure: %s\n\n%!" (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels6));+ printf " Structure: %s\n\n%!"+ (Sexp.to_string_hum (Einsum_parser.sexp_of_parsed_axis_labels labels6));printf "All use_padding syntax tests completed!\n%!"File "arrayjit/lib/assignments.ml", line 1, characters 0-0:diff --git a/_build/default/arrayjit/lib/assignments.ml b/_build/default/arrayjit/lib/.formatted/assignments.mlindex 069170f..a198727 100644--- a/_build/default/arrayjit/lib/assignments.ml+++ b/_build/default/arrayjit/lib/.formatted/assignments.ml@@ -153,9 +153,9 @@ let sequence l =let%track4_sexp to_low_level code =let open Indexing in- (* Apply left padding offsets to convert from semantic to buffer indices.- Semantic indices can be negative (e.g., -1 for convolution padding), but buffer- indices must be non-negative. Adding left_padding converts semantic to buffer space. *)+ (* Apply left padding offsets to convert from semantic to buffer indices. Semantic indices can be+ negative (e.g., -1 for convolution padding), but buffer indices must be non-negative. Adding+ left_padding converts semantic to buffer space. *)let apply_padding_offset (tn : Tn.t) (idcs : Indexing.axis_index array) :Indexing.axis_index array =match Tn.get_padding tn with@@ -214,10 +214,10 @@ let%track4_sexp to_low_level code ==let projections : Indexing.projections = Lazy.force projections inlet basecase rev_iters =- (* Create a substitution from product iterators to loop iterators.- Fresh loop symbols are needed because product_iterators may be shared across- different operations/tensors, but each lowered operation needs private loop symbols- to avoid conflicts in low_level.ml's symbol-to-tensor tracking. *)+ (* Create a substitution from product iterators to loop iterators. Fresh loop symbols are+ needed because product_iterators may be shared across different operations/tensors, but+ each lowered operation needs private loop symbols to avoid conflicts in low_level.ml's+ symbol-to-tensor tracking. *)let subst_map =let loop_iters = Array.of_list_rev rev_iters inArray.mapi projections.product_iterators ~f:(fun i prod_iter ->File "tensor/operation.ml", line 1, characters 0-0:diff --git a/_build/default/tensor/operation.ml b/_build/default/tensor/.formatted/operation.mlindex aa8ddae..cd89772 100644--- a/_build/default/tensor/operation.ml+++ b/_build/default/tensor/.formatted/operation.ml@@ -430,10 +430,10 @@ let einmax1 ?(capture_dims = []) spec =(** This generalizes the tropical matrix multiplication to arbitrary indices combinations.- LIMITATION: Backpropagation is only correct when the RHS1 (t1) index space includes- the RHS2 (t2) index space. This is the case for convolution-like operations where- the kernel indices are contracted with strided input indices. For general tropical- operations where RHS2 has independent indices, the g2 gradient will be incorrect. *)+ LIMITATION: Backpropagation is only correct when the RHS1 (t1) index space includes the RHS2+ (t2) index space. This is the case for convolution-like operations where the kernel indices are+ contracted with strided input indices. For general tropical operations where RHS2 has+ independent indices, the g2 gradient will be incorrect. *)let tropical ?(capture_dims = []) spec =let module NTDSL = structinclude Initial_NTDSL@@ -441,8 +441,8 @@ let tropical ?(capture_dims = []) spec =end inlet%cd op_asn ~t ~t1 ~t2 ~projections = v =:@^ v1 + v2 inlet%cd grad_asn ~t ~g ~t1 ~t2 ~projections =- (* Use _rhs1 suffix for both: gives input shape (ih,iw) = (oh,ow) x (wh,ww) outer product.- This correctly tracks which (input position, kernel position) pair achieved argmax. *)+ (* Use _rhs1 suffix for both: gives input shape (ih,iw) = (oh,ow) x (wh,ww) outer product. This+ correctly tracks which (input position, kernel position) pair achieved argmax. *){ sum_rhs1 } =:@^ add (t1, t2);{ cond_rhs1 } =: eq (t, sum_rhs1);g1 =+ where cond_rhs1 g 0;File "test/einsum/test_tropical_kernel.ml", line 1, characters 0-0:diff --git a/_build/default/test/einsum/test_tropical_kernel.ml b/_build/default/test/einsum/.formatted/test_tropical_kernel.mlindex 08991bf..32bad19 100644--- a/_build/default/test/einsum/test_tropical_kernel.ml+++ b/_build/default/test/einsum/.formatted/test_tropical_kernel.ml@@ -5,20 +5,21 @@ open Stdio(** Test tropical semiring (max-plus) operations with a learnable kernel.- This tests backpropagation for tropical operations with both input (t1/rhs1)- and kernel (t2/rhs2) gradients.+ This tests backpropagation for tropical operations with both input (t1/rhs1) and kernel+ (t2/rhs2) gradients.- The implementation uses `_rhs1` suffix for both input and kernel gradient paths.- This gives condition tensors input shape (ih,iw) which is effectively the "outer- product" of output (oh,ow) and kernel (wh,ww) dimensions. This correctly tracks- which (input position, kernel position) pair achieved the argmax for each output. *)+ The implementation uses `_rhs1` suffix for both input and kernel gradient paths. This gives+ condition tensors input shape (ih,iw) which is effectively the "outer product" of output (oh,ow)+ and kernel (wh,ww) dimensions. This correctly tracks which (input position, kernel position)+ pair achieved the argmax for each output. *)(** Create a tropical convolution-like operation with a learnable kernel.- This is similar to max_pool2d but with a non-zero learnable kernel, allowing us to- verify that g2 (kernel) gradients are computed correctly.+ This is similar to max_pool2d but with a non-zero learnable kernel, allowing us to verify that+ g2 (kernel) gradients are computed correctly.- The tropical operation computes: output[oh,ow] = max over (wh,ww) of (input[2*oh+wh, 2*ow+ww] + kernel[wh,ww])+ The tropical operation computes: output[oh,ow] = max over (wh,ww) of (input[2*oh+wh, 2*ow+ww] ++ kernel[wh,ww])For backprop:- g1 (input grad): gradient flows to input positions that achieved the argmax@@ -27,8 +28,9 @@ let tropical_conv2d ?(stride = 2) ?(window_size = 2) () =let%op op x kernel =Shape.set_dim wh window_size;Shape.set_dim ww window_size;- x @^+ "... | stride*oh< + wh, stride*ow< + ww, ..c..; wh, ww => ... | oh, ow, ..c.." [ "wh"; "ww" ]- kernel+ x+ @^+ "... | stride*oh< + wh, stride*ow< + ww, ..c..; wh, ww => ... | oh, ow, ..c.."+ [ "wh"; "ww" ] kernelinop@@ -73,19 +75,10 @@ let test_tropical_kernel_forward () =This is the key test: verifies that gradients flow correctly to both input and kernel.- Input pattern (4x4, values designed so argmax varies):- ```- [[9, 0, 0, 0],- [0, 0, 0, 8],- [0, 7, 0, 0],- [0, 0, 6, 0]]- ```+ Input pattern (4x4, values designed so argmax varies): ```+ [[9, 0, 0, 0], [0, 0, 0, 8], [0, 7, 0, 0], [0, 0, 6, 0]] ```- Kernel (2x2, small values so input determines argmax):- ```- [[0, 0],- [0, 0]]- ```+ Kernel (2x2, small values so input determines argmax): ``` [[0, 0], [0, 0]] ```With zero kernel, this is like max_pool2d - argmax is at input max positions.- Window [0,0]: max at (0,0)=9, argmax kernel position (0,0)@@ -93,8 +86,8 @@ let test_tropical_kernel_forward () =- Window [1,0]: max at (2,1)=7, argmax kernel position (0,1)- Window [1,1]: max at (3,2)=6, argmax kernel position (1,0)- Expected input gradients: 1 at positions (0,0), (1,3), (2,1), (3,2); 0 elsewhere.- Expected kernel gradients: 1 at each position (each is argmax for exactly one output). *)+ Expected input gradients: 1 at positions (0,0), (1,3), (2,1), (3,2); 0 elsewhere. Expected+ kernel gradients: 1 at each position (each is argmax for exactly one output). *)let test_tropical_kernel_backprop_zero_kernel () =printf "Testing tropical conv backprop with zero kernel...\n%!";Tensor.unsafe_reinitialize ();@@ -140,27 +133,18 @@ let test_tropical_kernel_backprop_zero_kernel () =(** Test tropical conv backprop with non-zero kernel that affects argmax.- Input (4x4, uniform low values):- ```- [[1, 1, 1, 1],- [1, 1, 1, 1],- [1, 1, 1, 1],- [1, 1, 1, 1]]+ Input (4x4, uniform low values): ``` [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]]```- Kernel (2x2, large value at position (1,1)):- ```- [[0, 0],- [0, 10]]- ```+ Kernel (2x2, large value at position (1,1)): ``` [[0, 0], [0, 10]] ```- With this kernel, the argmax for every window is at kernel position (1,1)- because 1+10=11 > 1+0=1 for all other positions.+ With this kernel, the argmax for every window is at kernel position (1,1) because 1+10=11 >+ 1+0=1 for all other positions.- Expected output: all 11 (value 1 + kernel 10 at position (1,1) of each window)- Expected input gradients: 1 at positions (1,1), (1,3), (3,1), (3,3); 0 elsewhere- (these are the input positions corresponding to kernel (1,1) in each window)- Expected kernel gradients: [[0,0],[0,4]] - only (1,1) was argmax, used 4 times *)+ Expected output: all 11 (value 1 + kernel 10 at position (1,1) of each window) Expected input+ gradients: 1 at positions (1,1), (1,3), (3,1), (3,3); 0 elsewhere (these are the input positions+ corresponding to kernel (1,1) in each window) Expected kernel gradients: [[0,0],[0,4]] - only+ (1,1) was argmax, used 4 times *)let test_tropical_kernel_backprop_nonzero_kernel () =printf "Testing tropical conv backprop with non-zero kernel...\n%!";Tensor.unsafe_reinitialize ();File "arrayjit/lib/indexing.ml", line 1, characters 0-0:diff --git a/_build/default/arrayjit/lib/indexing.ml b/_build/default/arrayjit/lib/.formatted/indexing.mlindex 018c9e9..0d03161 100644--- a/_build/default/arrayjit/lib/indexing.ml+++ b/_build/default/arrayjit/lib/.formatted/indexing.ml@@ -139,8 +139,8 @@ type projections = {*)product_iterators : symbol array;(** The product space iterators (concatentation of the relevant batch, output, input axes) for- iterating over the [product_space] axes, where same axes are at same array indices.- These may be shared; lowering creates fresh symbols for loop indices. *)+ iterating over the [product_space] axes, where same axes are at same array indices. These+ may be shared; lowering creates fresh symbols for loop indices. *)project_lhs : axis_index array;(** A projection that takes an [product_space]-bound index and produces an index into theresult of an operation. *)File "tensor/ppx_shared.ml", line 1, characters 0-0:diff --git a/_build/default/tensor/ppx_shared.ml b/_build/default/tensor/.formatted/ppx_shared.mlindex bee7b1b..7225cf0 100644--- a/_build/default/tensor/ppx_shared.ml+++ b/_build/default/tensor/.formatted/ppx_shared.ml@@ -115,12 +115,12 @@ let ndarray_constant expr =(** Convert an einsum spec string to an OCaml expression that constructs the runtime string.- This function parses the einsum spec using the Einsum_parser, then reconstructs a runtime- string expression, handling:- - stride and dilation values: if they look like integer literals, emit them directly;- otherwise emit [Int.to_string identifier] to convert at runtime- - use_padding: if unspecified (legacy syntax), emit [if use_padding then "=" else "<"]- to read the value from [Row.use_padding] at runtime+ This function parses the einsum spec using the Einsum_parser, then reconstructs a runtime string+ expression, handling:+ - stride and dilation values: if they look like integer literals, emit them directly; otherwise+ emit [Int.to_string identifier] to convert at runtime+ - use_padding: if unspecified (legacy syntax), emit [if use_padding then "=" else "<"] to read+ the value from [Row.use_padding] at runtimeExample: ["stride*x=+k; y => z"] where [stride] is a variable, generates an expression thatevaluates to e.g. ["2*x=+k; y => z"] if [stride = 2]. *)@@ -216,11 +216,12 @@ let substitute_identifiers_in_einsum_spec ~loc str_input =let output_segments =row_to_segments ~kind:"output" parsed.bcast_output parsed.given_beg_output parsed.given_outputin- let has_batch = not (List.is_empty batch_segments) || Option.is_some parsed.bcast_batch in- let has_input = not (List.is_empty input_segments) || Option.is_some parsed.bcast_input in+ let has_batch = (not (List.is_empty batch_segments)) || Option.is_some parsed.bcast_batch in+ let has_input = (not (List.is_empty input_segments)) || Option.is_some parsed.bcast_input inlet segments =if has_batch then- batch_segments @ [ estring ~loc "|" ]+ batch_segments+ @ [ estring ~loc "|" ]@ (if has_input then input_segments @ [ estring ~loc "->" ] else [])@ output_segmentselse if has_input then input_segments @ [ estring ~loc "->" ] @ output_segments@@ -248,33 +249,34 @@ let substitute_identifiers_in_einsum_spec ~loc str_input =let combined =String.concat(List.filter_map all_segments ~f:(fun e ->- match e.pexp_desc with Pexp_constant (Pconst_string (s, _, _)) -> Some s | _ -> None))+ match e.pexp_desc with+ | Pexp_constant (Pconst_string (s, _, _)) -> Some s+ | _ -> None))inestring ~loc combinedelse [%expr String.concat ~sep:"" [%e elist ~loc all_segments]]- with Parse_error _ ->+ with Parse_error _ -> ((* If parsing fails, try as axis_labels_spec *)- (try- let parsed = axis_labels_of_spec str_input in- let segments = parsed_to_segments parsed in- let all_literals =- List.for_all segments ~f:(fun e ->- match e.pexp_desc with Pexp_constant (Pconst_string _) -> true | _ -> false)- in- if all_literals then- let combined =- String.concat- (List.filter_map segments ~f:(fun e ->- match e.pexp_desc with- | Pexp_constant (Pconst_string (s, _, _)) -> Some s- | _ -> None))- in- estring ~loc combined- else [%expr String.concat ~sep:"" [%e elist ~loc segments]]- with Parse_error msg ->- (* Fall back to returning the original string with an error note *)- pexp_extension ~loc- @@ Location.error_extensionf ~loc "Failed to parse einsum spec: %s" msg)+ try+ let parsed = axis_labels_of_spec str_input in+ let segments = parsed_to_segments parsed in+ let all_literals =+ List.for_all segments ~f:(fun e ->+ match e.pexp_desc with Pexp_constant (Pconst_string _) -> true | _ -> false)+ in+ if all_literals then+ let combined =+ String.concat+ (List.filter_map segments ~f:(fun e ->+ match e.pexp_desc with+ | Pexp_constant (Pconst_string (s, _, _)) -> Some s+ | _ -> None))+ in+ estring ~loc combined+ else [%expr String.concat ~sep:"" [%e elist ~loc segments]]+ with Parse_error msg ->+ (* Fall back to returning the original string with an error note *)+ pexp_extension ~loc @@ Location.error_extensionf ~loc "Failed to parse einsum spec: %s" msg)let string_expr ~loc s = Ast_helper.Exp.constant @@ Pconst_string (s, loc, None)@@ -546,11 +548,7 @@ let let_opt ~loc vbs expr =(* Check for duplicates and create nested let bindings preserving definition order *)let seen = Hashtbl.create (module String) inList.fold_right vbs ~init:expr ~f:(fun vb acc ->- let name =- match vb.pvb_pat.ppat_desc with- | Ppat_var { txt; _ } -> txt- | _ -> "_"- in+ let name = match vb.pvb_pat.ppat_desc with Ppat_var { txt; _ } -> txt | _ -> "_" inmatch Hashtbl.add seen ~key:name ~data:() with| `Ok -> Ast_helper.Exp.let_ ~loc Nonrecursive [ vb ] acc| `Duplicate ->@@ -565,7 +563,6 @@ let let_opt ~loc vbs expr =Ast_helper.Exp.let_ ~loc Nonrecursive [ { vb with pvb_expr = error_expr } ] acc)let no_vbs = []-let reduce_vbss vbss = List.concat vbsslet expr_expander_with_punning translate ~loc ~path:_ payload =File "tensor/tensor.ml", line 1, characters 0-0:diff --git a/_build/default/tensor/tensor.ml b/_build/default/tensor/.formatted/tensor.mlindex 0376308..a9f685c 100644--- a/_build/default/tensor/tensor.ml+++ b/_build/default/tensor/.formatted/tensor.ml@@ -299,7 +299,8 @@ let%track7_sexp op ~(label : string list) ?(ternary_op = Shape.Pointwise_tern)let v =match terminal_op with| Some (Shape.Data (Asgns.Reshape data)) ->- Tn.create_with_reshape ~id ~label ~unpadded_dims ~padding ~from_padded:false ~base_ndarray:data ()+ Tn.create_with_reshape ~id ~label ~unpadded_dims ~padding ~from_padded:false+ ~base_ndarray:data ()| Some (Shape.Data (Asgns.Keep_shape_no_padding data)) ->Tn.create_from_padded ~id ~label ~ndarray:data ~padding:None ()| Some (Shape.Data (Asgns.Padded { data; padding = padding_spec; padded_value })) ->@@ -329,8 +330,8 @@ let%track7_sexp op ~(label : string list) ?(ternary_op = Shape.Pointwise_tern)assert falseinlet local_shape_updates =- List.map- ~f:(fun logic -> Shape.{ shape; logic; id = get_update_id (); unsafe_projections = None })+ List.map ~f:(fun logic ->+ Shape.{ shape; logic; id = get_update_id (); unsafe_projections = None })@@ shape_logics orig_tsinList.iter ~f:Shape.propagate_shapes local_shape_updates;File "arrayjit/lib/tnode.ml", line 1, characters 0-0:diff --git a/_build/default/arrayjit/lib/tnode.ml b/_build/default/arrayjit/lib/.formatted/tnode.mlindex 5ce96c8..4ffc148 100644--- a/_build/default/arrayjit/lib/tnode.ml+++ b/_build/default/arrayjit/lib/.formatted/tnode.ml@@ -710,8 +710,8 @@ let create_with_reshape ~id ~label ~base_ndarray ~unpadded_dims ~padding ~from_pinSome (Nd.apply_with_prec { f = f_reshape_with_prec } base_ndarray)| Some _, false ->- (* Create new bigarray with padding and copy source into non-padding parts.- semantic_dims are the data area dimensions (without padding). *)+ (* Create new bigarray with padding and copy source into non-padding parts. semantic_dims+ are the data area dimensions (without padding). *)let target = Nd.create_array ~debug prec_val ~dims:padded_dims ~padding:target_padding inlet source_dims = Nd.dims base_ndarray in(* Check total elements match, allowing shape differences *)dune build @fmt failed"/usr/bin/env" "bash" "-c" "opam exec -- dune build @fmt --ignore-promoted-rules || (echo "dune build @fmt failed"; exit 2)" failed with exit status 22025-12-11 14:20.35: Job failed: Failed: Build failed