2025-05-22 12:20.03: New job: test ahrefs/ocannl https://github.com/ahrefs/ocannl.git#refs/heads/master (9afb61d245b2724d2132450805c8b080ac7e0c9a) (linux-x86_64:fedora-41-5.3_opam-2.3) Base: ocaml/opam:fedora-41-ocaml-5.3@sha256:abc80c782e7acbd09ffd49defcb056c2fc402593e57bcb537add09330e2c3992 Opam project build To reproduce locally: git clone --recursive "https://github.com/ahrefs/ocannl.git" -b "master" && cd "ocannl" && git reset --hard 9afb61d2 cat > Dockerfile <<'END-OF-DOCKERFILE' FROM ocaml/opam:fedora-41-ocaml-5.3@sha256:abc80c782e7acbd09ffd49defcb056c2fc402593e57bcb537add09330e2c3992 # fedora-41-5.3_opam-2.3 USER 1000:1000 ENV CLICOLOR_FORCE="1" ENV OPAMCOLOR="always" WORKDIR /src RUN sudo dnf install -y findutils RUN sudo ln -f /usr/bin/opam-2.3 /usr/bin/opam RUN opam init --reinit -ni RUN uname -rs && opam exec -- ocaml -version && opam --version WORKDIR /src RUN sudo chown opam /src RUN cd ~/opam-repository && (git cat-file -e c7d6d1d2aa1bf00c8e6ec9dff2030cd39d493e47 || git fetch origin master) && git reset -q --hard c7d6d1d2aa1bf00c8e6ec9dff2030cd39d493e47 && git log --no-decorate -n1 --oneline && opam update -u COPY --chown=1000:1000 neural_nets_lib.opam arrayjit.opam ./ RUN opam pin add -yn neural_nets_lib.dev './' && \ opam pin add -yn arrayjit.dev './' RUN echo '(lang dune 3.0)' > './dune-project' ENV DEPS="angstrom.0.16.1 astring.0.8.5 backoff.0.1.1 base.v0.17.2 base-bigarray.base base-domains.base base-effects.base base-nnp.base base-threads.base base-unix.base bigarray-compat.1.1.0 bigstringaf.0.10.0 camlp-streams.5.0.1 cmdliner.1.3.0 conf-libffi.2.0.0 conf-pkg-config.4 cppo.1.8.0 csexp.1.5.2 ctypes.0.23.0 ctypes-foreign.0.23.0 dune.3.18.2 dune-configurator.3.18.2 fieldslib.v0.17.0 fmt.0.10.0 integers.0.7.0 jane-street-headers.v0.17.0 jst-config.v0.17.0 logs.0.8.0 mdx.2.5.0 mtime.2.1.0 multicore-magic.2.3.1 num.1.5-1 ocaml.5.3.0 ocaml-base-compiler.5.3.0 ocaml-compiler.5.3.0 ocaml-compiler-libs.v0.17.0 ocaml-config.3 ocaml-options-vanilla.1 ocaml-syntax-shims.1.0.0 ocaml-version.4.0.0 ocaml_intrinsics_kernel.v0.17.1 ocamlbuild.0.16.1 ocamlfind.1.9.8 parsexp.v0.17.0 pprint.20230830 ppx_assert.v0.17.0 ppx_base.v0.17.0 ppx_cold.v0.17.0 ppx_compare.v0.17.0 ppx_derivers.1.2.1 ppx_deriving.6.0.3 ppx_enumerate.v0.17.0 ppx_expect.v0.17.2 ppx_fields_conv.v0.17.0 ppx_globalize.v0.17.0 ppx_hash.v0.17.0 ppx_here.v0.17.0 ppx_inline_test.v0.17.0 ppx_minidebug.2.2.0 ppx_optcomp.v0.17.0 ppx_sexp_conv.v0.17.0 ppx_string.v0.17.0 ppx_variants_conv.v0.17.0 ppxlib.0.35.0 ppxlib_jane.v0.17.2 printbox.0.12 printbox-ext-plot.0.12 printbox-html.0.12 printbox-md.0.12 printbox-text.0.12 ptime.1.2.0 re.1.12.0 result.1.5 saturn_lockfree.0.5.0 seq.base sexplib.v0.17.0 sexplib0.v0.17.0 stdio.v0.17.0 stdlib-shims.0.3.0 thread-local-storage.0.2 time_now.v0.17.0 topkg.1.0.8 tyxml.4.6.0 uucp.16.0.0 uutf.1.0.4 variantslib.v0.17.0" ENV CI="true" ENV OCAMLCI="true" RUN opam update --depexts && opam install --cli=2.3 --depext-only -y neural_nets_lib.dev arrayjit.dev $DEPS RUN opam install $DEPS COPY --chown=1000:1000 . /src RUN opam exec -- dune build @install @check @runtest && rm -rf _build END-OF-DOCKERFILE docker build . END-REPRO-BLOCK 2025-05-22 12:20.03: Using cache hint "ahrefs/ocannl-ocaml/opam:fedora-41-ocaml-5.3@sha256:abc80c782e7acbd09ffd49defcb056c2fc402593e57bcb537add09330e2c3992-fedora-41-5.3_opam-2.3-cdc9572ad54e4d4bf194acfcdfaa690c" 2025-05-22 12:20.03: Using OBuilder spec: ((from ocaml/opam:fedora-41-ocaml-5.3@sha256:abc80c782e7acbd09ffd49defcb056c2fc402593e57bcb537add09330e2c3992) (comment fedora-41-5.3_opam-2.3) (user (uid 1000) (gid 1000)) (env CLICOLOR_FORCE 1) (env OPAMCOLOR always) (workdir /src) (run (network host) (shell "sudo dnf install -y findutils")) (run (shell "sudo ln -f /usr/bin/opam-2.3 /usr/bin/opam")) (run (shell "opam init --reinit -ni")) (run (shell "uname -rs && opam exec -- ocaml -version && opam --version")) (workdir /src) (run (shell "sudo chown opam /src")) (run (cache (opam-archives (target /home/opam/.opam/download-cache))) (network host) (shell "cd ~/opam-repository && (git cat-file -e c7d6d1d2aa1bf00c8e6ec9dff2030cd39d493e47 || git fetch origin master) && git reset -q --hard c7d6d1d2aa1bf00c8e6ec9dff2030cd39d493e47 && git log --no-decorate -n1 --oneline && opam update -u")) (copy (src neural_nets_lib.opam arrayjit.opam) (dst ./)) (run (network host) (shell "opam pin add -yn neural_nets_lib.dev './' && \ \nopam pin add -yn arrayjit.dev './'")) (run (network host) (shell "echo '(lang dune 3.0)' > './dune-project'")) (env DEPS "angstrom.0.16.1 astring.0.8.5 backoff.0.1.1 base.v0.17.2 base-bigarray.base base-domains.base base-effects.base base-nnp.base base-threads.base base-unix.base bigarray-compat.1.1.0 bigstringaf.0.10.0 camlp-streams.5.0.1 cmdliner.1.3.0 conf-libffi.2.0.0 conf-pkg-config.4 cppo.1.8.0 csexp.1.5.2 ctypes.0.23.0 ctypes-foreign.0.23.0 dune.3.18.2 dune-configurator.3.18.2 fieldslib.v0.17.0 fmt.0.10.0 integers.0.7.0 jane-street-headers.v0.17.0 jst-config.v0.17.0 logs.0.8.0 mdx.2.5.0 mtime.2.1.0 multicore-magic.2.3.1 num.1.5-1 ocaml.5.3.0 ocaml-base-compiler.5.3.0 ocaml-compiler.5.3.0 ocaml-compiler-libs.v0.17.0 ocaml-config.3 ocaml-options-vanilla.1 ocaml-syntax-shims.1.0.0 ocaml-version.4.0.0 ocaml_intrinsics_kernel.v0.17.1 ocamlbuild.0.16.1 ocamlfind.1.9.8 parsexp.v0.17.0 pprint.20230830 ppx_assert.v0.17.0 ppx_base.v0.17.0 ppx_cold.v0.17.0 ppx_compare.v0.17.0 ppx_derivers.1.2.1 ppx_deriving.6.0.3 ppx_enumerate.v0.17.0 ppx_expect.v0.17.2 ppx_fields_conv.v0.17.0 ppx_globalize.v0.17.0 ppx_hash.v0.17.0 ppx_here.v0.17.0 ppx_inline_test.v0.17.0 ppx_minidebug.2.2.0 ppx_optcomp.v0.17.0 ppx_sexp_conv.v0.17.0 ppx_string.v0.17.0 ppx_variants_conv.v0.17.0 ppxlib.0.35.0 ppxlib_jane.v0.17.2 printbox.0.12 printbox-ext-plot.0.12 printbox-html.0.12 printbox-md.0.12 printbox-text.0.12 ptime.1.2.0 re.1.12.0 result.1.5 saturn_lockfree.0.5.0 seq.base sexplib.v0.17.0 sexplib0.v0.17.0 stdio.v0.17.0 stdlib-shims.0.3.0 thread-local-storage.0.2 time_now.v0.17.0 topkg.1.0.8 tyxml.4.6.0 uucp.16.0.0 uutf.1.0.4 variantslib.v0.17.0") (env CI true) (env OCAMLCI true) (run (cache (opam-archives (target /home/opam/.opam/download-cache))) (network host) (shell "opam update --depexts && opam install --cli=2.3 --depext-only -y neural_nets_lib.dev arrayjit.dev $DEPS")) (run (cache (opam-archives (target /home/opam/.opam/download-cache))) (network host) (shell "opam install $DEPS")) (copy (src .) (dst /src)) (run (shell "opam exec -- dune build @install @check @runtest && rm -rf _build")) ) 2025-05-22 12:20.03: Waiting for resource in pool OCluster 2025-05-22 12:20.03: Waiting for worker… 2025-05-22 12:20.03: Got resource from pool OCluster Building on laodoke.caelum.ci.dev All commits already cached HEAD is now at 9afb61d2 In progress / broken: Format -> PPrint migration first pass by Claude (from ocaml/opam:fedora-41-ocaml-5.3@sha256:abc80c782e7acbd09ffd49defcb056c2fc402593e57bcb537add09330e2c3992) 2025-05-22 12:20.04 ---> using "da0437edefc3074e740b2380711421a58ad6af000252c27345a9c063faf0cc10" from cache /: (comment fedora-41-5.3_opam-2.3) /: (user (uid 1000) (gid 1000)) /: (env CLICOLOR_FORCE 1) /: (env OPAMCOLOR always) /: (workdir /src) /src: (run (network host) (shell "sudo dnf install -y findutils")) Updating and loading repositories: Fedora 41 openh264 (From Cisco) - x86_ 100% | 9.7 KiB/s | 989.0 B | 00m00s Fedora 41 - x86_64 100% | 196.2 KiB/s | 25.7 KiB | 00m00s Fedora 41 - x86_64 - Updates 100% | 183.7 KiB/s | 23.5 KiB | 00m00s Fedora 41 - x86_64 - Updates 100% | 8.3 MiB/s | 9.6 MiB | 00m01s Repositories loaded. Package "findutils-1:4.10.0-4.fc41.x86_64" is already installed. Nothing to do. 2025-05-22 12:20.04 ---> using "cda621b93ea4e5bc7b2f3a44f5472568fa9069c819fc4f9ee4dba7021db6599e" from cache /src: (run (shell "sudo ln -f /usr/bin/opam-2.3 /usr/bin/opam")) 2025-05-22 12:20.04 ---> using "00fdc0066ab5f68afc204c28620b3ce62c27dda0ac3863d3d421d30b1e5a7121" from cache /src: (run (shell "opam init --reinit -ni")) Configuring from /home/opam/.opamrc and then from built-in defaults. Checking for available remotes: rsync and local, git. - you won't be able to use mercurial repositories unless you install the hg command on your system. - you won't be able to use darcs repositories unless you install the darcs command on your system. This development version of opam requires an update to the layout of /home/opam/.opam from version 2.0 to version 2.2, which can't be reverted. You may want to back it up before going further. Continue? [y/n] y [NOTE] The 'jobs' option was reset, its value was 255 and its new value will vary according to the current number of cores on your machine. You can restore the fixed value using: opam option jobs=255 --global Format upgrade done. <><> Updating repositories ><><><><><><><><><><><><><><><><><><><><><><><><><><> [default] Initialised 2025-05-22 12:20.04 ---> using "e4c6ec45de15317b19a5e44e28bcb7589e585c58ff662e7c78b23377170afeeb" from cache /src: (run (shell "uname -rs && opam exec -- ocaml -version && opam --version")) Linux 5.15.0-139-generic The OCaml toplevel, version 5.3.0 2.3.0 2025-05-22 12:20.04 ---> using "21404f6f0f15670f1371a8655b67d83eca7d3eb1d65bed293fe562e27fca1e04" from cache /src: (workdir /src) /src: (run (shell "sudo chown opam /src")) 2025-05-22 12:20.04 ---> using "e6db08cef467f22bc6d82a42d4d4c7d0ba62091bad93cb74af70b44a2974850b" from cache /src: (run (cache (opam-archives (target /home/opam/.opam/download-cache))) (network host) (shell "cd ~/opam-repository && (git cat-file -e c7d6d1d2aa1bf00c8e6ec9dff2030cd39d493e47 || git fetch origin master) && git reset -q --hard c7d6d1d2aa1bf00c8e6ec9dff2030cd39d493e47 && git log --no-decorate -n1 --oneline && opam update -u")) From https://github.com/ocaml/opam-repository * branch master -> FETCH_HEAD 35eb2f107a..27f5ac67c2 master -> origin/master c7d6d1d2aa Merge pull request #27880 from MisterDA/os-family-fedora <><> Updating package repositories ><><><><><><><><><><><><><><><><><><><><><><> [default] synchronised from git+file:///home/opam/opam-repository 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. # To update the current shell environment, run: eval $(opam env) 2025-05-22 12:20.04 ---> using "47e222691df9f48e96b82354930e643d109158150dc7c77fac9953e2867a0de2" from cache /src: (copy (src neural_nets_lib.opam arrayjit.opam) (dst ./)) 2025-05-22 12:20.04 ---> using "e7730057529b4754024c66acc0d1018233e8d2f2daf11327df013acb81dd02d8" from cache /src: (run (network host) (shell "opam pin add -yn neural_nets_lib.dev './' && \ \nopam pin add -yn arrayjit.dev './'")) [neural_nets_lib.dev] synchronised (file:///src) neural_nets_lib is now pinned to file:///src (version dev) [arrayjit.dev] synchronised (file:///src) arrayjit is now pinned to file:///src (version dev) 2025-05-22 12:20.04 ---> using "063b3fe81118ec0277acdaec22f1eecc2dd6a81fe61f9d9f1889e8d0cbd0aebf" from cache /src: (run (network host) (shell "echo '(lang dune 3.0)' > './dune-project'")) 2025-05-22 12:20.04 ---> using "33e409d72e19a2f51ac75adada9ccd6f1a25cd1f594ac1fdee973b79ca82e452" from cache /src: (env DEPS "angstrom.0.16.1 astring.0.8.5 backoff.0.1.1 base.v0.17.2 base-bigarray.base base-domains.base base-effects.base base-nnp.base base-threads.base base-unix.base bigarray-compat.1.1.0 bigstringaf.0.10.0 camlp-streams.5.0.1 cmdliner.1.3.0 conf-libffi.2.0.0 conf-pkg-config.4 cppo.1.8.0 csexp.1.5.2 ctypes.0.23.0 ctypes-foreign.0.23.0 dune.3.18.2 dune-configurator.3.18.2 fieldslib.v0.17.0 fmt.0.10.0 integers.0.7.0 jane-street-headers.v0.17.0 jst-config.v0.17.0 logs.0.8.0 mdx.2.5.0 mtime.2.1.0 multicore-magic.2.3.1 num.1.5-1 ocaml.5.3.0 ocaml-base-compiler.5.3.0 ocaml-compiler.5.3.0 ocaml-compiler-libs.v0.17.0 ocaml-config.3 ocaml-options-vanilla.1 ocaml-syntax-shims.1.0.0 ocaml-version.4.0.0 ocaml_intrinsics_kernel.v0.17.1 ocamlbuild.0.16.1 ocamlfind.1.9.8 parsexp.v0.17.0 pprint.20230830 ppx_assert.v0.17.0 ppx_base.v0.17.0 ppx_cold.v0.17.0 ppx_compare.v0.17.0 ppx_derivers.1.2.1 ppx_deriving.6.0.3 ppx_enumerate.v0.17.0 ppx_expect.v0.17.2 ppx_fields_conv.v0.17.0 ppx_globalize.v0.17.0 ppx_hash.v0.17.0 ppx_here.v0.17.0 ppx_inline_test.v0.17.0 ppx_minidebug.2.2.0 ppx_optcomp.v0.17.0 ppx_sexp_conv.v0.17.0 ppx_string.v0.17.0 ppx_variants_conv.v0.17.0 ppxlib.0.35.0 ppxlib_jane.v0.17.2 printbox.0.12 printbox-ext-plot.0.12 printbox-html.0.12 printbox-md.0.12 printbox-text.0.12 ptime.1.2.0 re.1.12.0 result.1.5 saturn_lockfree.0.5.0 seq.base sexplib.v0.17.0 sexplib0.v0.17.0 stdio.v0.17.0 stdlib-shims.0.3.0 thread-local-storage.0.2 time_now.v0.17.0 topkg.1.0.8 tyxml.4.6.0 uucp.16.0.0 uutf.1.0.4 variantslib.v0.17.0") /src: (env CI true) /src: (env OCAMLCI true) /src: (run (cache (opam-archives (target /home/opam/.opam/download-cache))) (network host) (shell "opam update --depexts && opam install --cli=2.3 --depext-only -y neural_nets_lib.dev arrayjit.dev $DEPS")) + /usr/bin/sudo "yum" "makecache" - Updating and loading repositories: - Repositories loaded. - Metadata cache created. <><> Synchronising pinned packages ><><><><><><><><><><><><><><><><><><><><><><> [arrayjit.dev] synchronised (file:///src) [neural_nets_lib.dev] synchronised (file:///src) [NOTE] Package ocaml-options-vanilla is already installed (current version is 1). [NOTE] Package ocaml-config is already installed (current version is 3). [NOTE] Package ocaml-compiler is already installed (current version is 5.3.0). [NOTE] Package ocaml-base-compiler is already installed (current version is 5.3.0). [NOTE] Package ocaml is already installed (current version is 5.3.0). [NOTE] Package base-unix is already installed (current version is base). [NOTE] Package base-threads is already installed (current version is base). [NOTE] Package base-nnp is already installed (current version is base). [NOTE] Package base-effects is already installed (current version is base). [NOTE] Package base-domains is already installed (current version is base). [NOTE] Package base-bigarray is already installed (current version is base). The following system packages will first need to be installed: libffi-devel <><> Handling external dependencies <><><><><><><><><><><><><><><><><><><><><><> + /usr/bin/sudo "yum" "install" "-y" "libffi-devel" - Updating and loading repositories: - Repositories loaded. - Package Arch Version Repository Size - Installing: - libffi-devel x86_64 3.4.6-3.fc41 fedora 33.1 KiB - - Transaction Summary: - Installing: 1 package - - Total size of inbound packages is 29 KiB. Need to download 29 KiB. - After this operation, 33 KiB extra will be used (install 33 KiB, remove 0 B). - [1/1] libffi-devel-0:3.4.6-3.fc41.x86_6 100% | 368.8 KiB/s | 28.8 KiB | 00m00s - -------------------------------------------------------------------------------- - [1/1] Total 100% | 109.4 KiB/s | 28.8 KiB | 00m00s - Running transaction - [1/3] Verify package files 100% | 0.0 B/s | 1.0 B | 00m00s - [2/3] Prepare transaction 100% | 38.0 B/s | 1.0 B | 00m00s - [3/3] Installing libffi-devel-0:3.4.6-3 100% | 669.1 KiB/s | 34.8 KiB | 00m00s - Complete! + /usr/bin/rpm "-q" "--whatprovides" "libffi-devel" - libffi-devel-3.4.6-3.fc41.x86_64 2025-05-22 12:20.04 ---> using "56f1fb25cdf08ccfa843e8cf68715585265b4862dc78f3ea7237d6f2aabdd617" from cache /src: (run (cache (opam-archives (target /home/opam/.opam/download-cache))) (network host) (shell "opam install $DEPS")) [NOTE] Package ocaml-options-vanilla is already installed (current version is 1). [NOTE] Package ocaml-config is already installed (current version is 3). [NOTE] Package ocaml-compiler is already installed (current version is 5.3.0). [NOTE] Package ocaml-base-compiler is already installed (current version is 5.3.0). [NOTE] Package ocaml is already installed (current version is 5.3.0). [NOTE] Package base-unix is already installed (current version is base). [NOTE] Package base-threads is already installed (current version is base). [NOTE] Package base-nnp is already installed (current version is base). [NOTE] Package base-effects is already installed (current version is base). [NOTE] Package base-domains is already installed (current version is base). [NOTE] Package base-bigarray is already installed (current version is base). The following actions will be performed: === install 75 packages - install angstrom 0.16.1 - install astring 0.8.5 - install backoff 0.1.1 - install base v0.17.2 - install bigarray-compat 1.1.0 - install bigstringaf 0.10.0 - install camlp-streams 5.0.1 - install cmdliner 1.3.0 - install conf-libffi 2.0.0 - install conf-pkg-config 4 - install cppo 1.8.0 - install csexp 1.5.2 - install ctypes 0.23.0 - install ctypes-foreign 0.23.0 - install dune 3.18.2 - install dune-configurator 3.18.2 - install fieldslib v0.17.0 - install fmt 0.10.0 - install integers 0.7.0 - install jane-street-headers v0.17.0 - install jst-config v0.17.0 - install logs 0.8.0 - install mdx 2.5.0 - install mtime 2.1.0 - install multicore-magic 2.3.1 - install num 1.5-1 - install ocaml-compiler-libs v0.17.0 - install ocaml-syntax-shims 1.0.0 - install ocaml-version 4.0.0 - install ocaml_intrinsics_kernel v0.17.1 - install ocamlbuild 0.16.1 - install ocamlfind 1.9.8 - install parsexp v0.17.0 - install pprint 20230830 - install ppx_assert v0.17.0 - install ppx_base v0.17.0 - install ppx_cold v0.17.0 - install ppx_compare v0.17.0 - install ppx_derivers 1.2.1 - install ppx_deriving 6.0.3 - install ppx_enumerate v0.17.0 - install ppx_expect v0.17.2 - install ppx_fields_conv v0.17.0 - install ppx_globalize v0.17.0 - install ppx_hash v0.17.0 - install ppx_here v0.17.0 - install ppx_inline_test v0.17.0 - install ppx_minidebug 2.2.0 - install ppx_optcomp v0.17.0 - install ppx_sexp_conv v0.17.0 - install ppx_string v0.17.0 - install ppx_variants_conv v0.17.0 - install ppxlib 0.35.0 - install ppxlib_jane v0.17.2 - install printbox 0.12 - install printbox-ext-plot 0.12 - install printbox-html 0.12 - install printbox-md 0.12 - install printbox-text 0.12 - install ptime 1.2.0 - install re 1.12.0 - install result 1.5 - install saturn_lockfree 0.5.0 - install seq base - install sexplib v0.17.0 - install sexplib0 v0.17.0 - install stdio v0.17.0 - install stdlib-shims 0.3.0 - install thread-local-storage 0.2 - install time_now v0.17.0 - install topkg 1.0.8 - install tyxml 4.6.0 - install uucp 16.0.0 - install uutf 1.0.4 - install variantslib v0.17.0 <><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><> -> retrieved backoff.0.1.1 (cached) -> retrieved astring.0.8.5 (cached) -> retrieved angstrom.0.16.1 (cached) -> retrieved base.v0.17.2 (cached) -> retrieved bigarray-compat.1.1.0 (cached) -> retrieved bigstringaf.0.10.0 (cached) -> retrieved camlp-streams.5.0.1 (cached) -> retrieved cppo.1.8.0 (cached) -> retrieved cmdliner.1.3.0 (cached) -> installed conf-pkg-config.4 -> retrieved csexp.1.5.2 (cached) -> retrieved ctypes.0.23.0, ctypes-foreign.0.23.0 (cached) -> installed conf-libffi.2.0.0 -> retrieved fieldslib.v0.17.0 (cached) -> retrieved integers.0.7.0 (cached) -> retrieved fmt.0.10.0 (cached) -> retrieved jane-street-headers.v0.17.0 (cached) -> retrieved jst-config.v0.17.0 (cached) -> retrieved logs.0.8.0 (cached) -> retrieved mtime.2.1.0 (cached) -> retrieved mdx.2.5.0 (cached) -> retrieved multicore-magic.2.3.1 (cached) -> retrieved num.1.5-1 (cached) -> retrieved ocaml-compiler-libs.v0.17.0 (cached) -> retrieved ocaml-syntax-shims.1.0.0 (cached) -> retrieved ocaml-version.4.0.0 (cached) -> retrieved ocaml_intrinsics_kernel.v0.17.1 (cached) -> retrieved ocamlbuild.0.16.1 (cached) -> retrieved ocamlfind.1.9.8 (cached) -> retrieved dune.3.18.2, dune-configurator.3.18.2 (cached) -> retrieved parsexp.v0.17.0 (cached) -> retrieved pprint.20230830 (cached) -> retrieved ppx_assert.v0.17.0 (cached) -> retrieved ppx_base.v0.17.0 (cached) -> retrieved ppx_cold.v0.17.0 (cached) -> retrieved ppx_compare.v0.17.0 (cached) -> retrieved ppx_derivers.1.2.1 (cached) -> retrieved ppx_deriving.6.0.3 (cached) -> retrieved ppx_enumerate.v0.17.0 (cached) -> retrieved ppx_expect.v0.17.2 (cached) -> installed cmdliner.1.3.0 -> installed num.1.5-1 -> retrieved ppx_fields_conv.v0.17.0 (cached) -> retrieved ppx_globalize.v0.17.0 (cached) -> retrieved ppx_hash.v0.17.0 (cached) -> retrieved ppx_here.v0.17.0 (cached) -> retrieved ppx_inline_test.v0.17.0 (cached) -> retrieved ppx_optcomp.v0.17.0 (cached) -> retrieved ppx_sexp_conv.v0.17.0 (cached) -> retrieved ppx_string.v0.17.0 (cached) -> retrieved ppx_variants_conv.v0.17.0 (cached) -> retrieved ppx_minidebug.2.2.0 (cached) -> retrieved ppxlib_jane.v0.17.2 (cached) -> retrieved ptime.1.2.0 (cached) -> retrieved re.1.12.0 (cached) -> retrieved result.1.5 (cached) -> retrieved saturn_lockfree.0.5.0 (cached) -> retrieved seq.base (cached) -> installed seq.base -> retrieved sexplib.v0.17.0 (cached) -> retrieved ppxlib.0.35.0 (cached) -> retrieved sexplib0.v0.17.0 (cached) -> retrieved stdio.v0.17.0 (cached) -> retrieved stdlib-shims.0.3.0 (cached) -> retrieved thread-local-storage.0.2 (cached) -> retrieved time_now.v0.17.0 (cached) -> retrieved printbox.0.12, printbox-ext-plot.0.12, printbox-html.0.12, printbox-md.0.12, printbox-text.0.12 (cached) -> retrieved topkg.1.0.8 (cached) -> retrieved tyxml.4.6.0 (cached) -> retrieved uutf.1.0.4 (cached) -> retrieved variantslib.v0.17.0 (cached) -> retrieved uucp.16.0.0 (cached) -> installed ocamlfind.1.9.8 -> installed ocamlbuild.0.16.1 -> installed topkg.1.0.8 -> installed uutf.1.0.4 -> installed mtime.2.1.0 -> installed fmt.0.10.0 -> installed ptime.1.2.0 -> installed astring.0.8.5 -> installed logs.0.8.0 -> installed dune.3.18.2 -> installed jane-street-headers.v0.17.0 -> installed ppx_derivers.1.2.1 -> installed csexp.1.5.2 -> installed backoff.0.1.1 -> installed bigarray-compat.1.1.0 -> installed camlp-streams.5.0.1 -> installed multicore-magic.2.3.1 -> installed ocaml-version.4.0.0 -> installed ocaml_intrinsics_kernel.v0.17.1 -> installed ocaml-syntax-shims.1.0.0 -> installed ocaml-compiler-libs.v0.17.0 -> installed pprint.20230830 -> installed printbox.0.12 -> installed cppo.1.8.0 -> installed re.1.12.0 -> installed result.1.5 -> installed sexplib0.v0.17.0 -> installed stdlib-shims.0.3.0 -> installed thread-local-storage.0.2 -> installed saturn_lockfree.0.5.0 -> installed integers.0.7.0 -> installed parsexp.v0.17.0 -> installed dune-configurator.3.18.2 -> installed bigstringaf.0.10.0 -> installed mdx.2.5.0 -> installed sexplib.v0.17.0 -> installed angstrom.0.16.1 -> installed tyxml.4.6.0 -> installed printbox-html.0.12 -> installed ctypes.0.23.0 -> installed base.v0.17.2 -> installed variantslib.v0.17.0 -> installed fieldslib.v0.17.0 -> installed stdio.v0.17.0 -> installed ctypes-foreign.0.23.0 -> installed uucp.16.0.0 -> installed printbox-text.0.12 -> installed printbox-md.0.12 -> installed printbox-ext-plot.0.12 -> installed ppxlib.0.35.0 -> installed ppxlib_jane.v0.17.2 -> installed ppx_optcomp.v0.17.0 -> installed ppx_cold.v0.17.0 -> installed ppx_here.v0.17.0 -> installed ppx_variants_conv.v0.17.0 -> installed ppx_fields_conv.v0.17.0 -> installed ppx_enumerate.v0.17.0 -> installed ppx_globalize.v0.17.0 -> installed ppx_deriving.6.0.3 -> installed ppx_compare.v0.17.0 -> installed ppx_sexp_conv.v0.17.0 -> installed ppx_hash.v0.17.0 -> installed ppx_assert.v0.17.0 -> installed ppx_base.v0.17.0 -> installed ppx_minidebug.2.2.0 -> installed jst-config.v0.17.0 -> installed ppx_string.v0.17.0 -> installed time_now.v0.17.0 -> installed ppx_inline_test.v0.17.0 -> installed ppx_expect.v0.17.2 Done. # To update the current shell environment, run: eval $(opam env) 2025-05-22 12:20.04 ---> using "1de4cf5d4fa2045ccadabf4d63be5b5e21a9617c39609bd14197216061357a4d" from cache /src: (copy (src .) (dst /src)) 2025-05-22 12:20.05 ---> saved as "f86f420bad9bc9c324a54f6156859de659d804cdb879d96055dff0b9612c63b2" /src: (run (shell "opam exec -- dune build @install @check @runtest && rm -rf _build")) (cd _build/default/test/config && ../../arrayjit/bin/read_config.exe --read=backend) Welcome to OCANNL! Reading configuration defaults from /src/_build/default/test/config/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file Wrote value of 'backend' to ocannl_backend.txt (cd _build/default/test_ppx && ./test_ppx_op_expected.exe) Welcome to OCANNL! Reading configuration defaults from /src/_build/default/test_ppx/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/default/test_ppx && ./test_ppx_op.exe) Welcome to OCANNL! Reading configuration defaults from /src/_build/default/test_ppx/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition 'Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/77c478fbfbf5b5f79f37815041cf490a/default/test/ocannl_config.' -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition 'Retrieving commandline, environment, or config file variable ocannl_log_level' -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition '' -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition 'Found 0, in the config file' -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file File "test/dune", lines 30-40, characters 0-281: 30 | (rule 31 | (alias runtest) 32 | (target 33 | (dir log_files)) 34 | (action 35 | (run 36 | %{dep:micrograd_demo_logging.exe} 37 | "--ocannl_debug_backend=text" 38 | "--ocannl_log_file_stem=micrograd_demo_logging" 39 | "--ocannl_log_main_domain_to_stdout=false" 40 | "--ocannl_debug_log_to_stream_files=true"))) (cd _build/default/test && ./micrograd_demo_logging.exe --ocannl_debug_backend=text --ocannl_log_file_stem=micrograd_demo_logging --ocannl_log_main_domain_to_stdout=false --ocannl_debug_log_to_stream_files=true) Welcome to OCANNL! Reading configuration defaults from /src/_build/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file Retrieving commandline, environment, or config file variable ocannl_backend Found multicore_cc, in the config file Retrieving commandline, environment, or config file variable ocannl_cd_ident_style Not found, using default heuristic Retrieving commandline, environment, or config file variable ocannl_ll_ident_style Not found, using default heuristic Retrieving commandline, environment, or config file variable ocannl_prefer_backend_uniformity Found true, in the config file Retrieving commandline, environment, or config file variable ocannl_debug_log_to_stream_files Found true, commandline --ocannl_debug_log_to_stream_files=true Retrieving commandline, environment, or config file variable ocannl_cc_backend_optimization_level Not found, using default 3 Retrieving commandline, environment, or config file variable ocannl_cc_backend_compiler_command Not found, using default gcc Fatal error: exception File "src/printbox-text/PrintBox_text.ml", line 212, characters 6-12: Assertion failed Raised at PrintBox_text.Output.Make_out.to_buf_aux_ in file "src/printbox-text/PrintBox_text.ml", line 212, characters 6-50 Called from Stdlib__Map.Make.fold in file "map.ml", line 329, characters 19-42 Called from Stdlib__Map.Make.fold in file "map.ml", line 329, characters 26-41 Called from Stdlib__Map.Make.fold in file "map.ml", line 329, characters 26-41 Called from Stdlib__Map.Make.fold in file "map.ml", line 329, characters 26-41 Called from PrintBox_text.Output.Make_out.render in file "src/printbox-text/PrintBox_text.ml", line 242, characters 14-64 Called from PrintBox_text.output in file "src/printbox-text/PrintBox_text.ml", line 851, characters 2-31 Called from Minidebug_runtime.PrintBox.output_box in file "minidebug_runtime.ml", line 1527, characters 19-59 Called from Minidebug_runtime.PrintBox.close_log_impl.close_tree in file "minidebug_runtime.ml", line 1572, characters 6-38 Called from Backends.Add_buffer_retrieval_and_syncing.sync_routine in file "arrayjit/lib/backends.ml", lines 144-172, characters 31-82 Called from Backends.Raise_backend.link in file "arrayjit/lib/backends.ml", lines 454-455, characters 4-92 Re-raised at Backends.Raise_backend.link in file "arrayjit/lib/backends.ml", lines 441-455, characters 23-92 Called from Dune__exe__Micrograd_demo_logging in file "test/micrograd_demo_logging.ml", line 34, characters 13-77 (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition primitive_ops.ml -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition zero2hero_1of7.ml -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition hello_world_op.ml -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition einsum_trivia.ml -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition micrograd_demo.ml -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file (cd _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition moons_demo_parallel.ml -source-tree-root .. -diff-cmd -) Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file File "test/micrograd_demo.ml", line 1, characters 0-0: /usr/bin/git --no-pager diff --no-index --color=always -u _build/default/test/micrograd_demo.ml _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/micrograd_demo.ml.corrected diff --git a/_build/default/test/micrograd_demo.ml b/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/micrograd_demo.ml.corrected index 77e46c6..3cb470c 100644 --- a/_build/default/test/micrograd_demo.ml +++ b/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/micrograd_demo.ml.corrected @@ -52,15 +52,14 @@ let%expect_test "Micrograd README basic example" = │├┼───────┤ │ │││ -4.00 │ │ │└┴───────┘ │ - └─────────────────┘ - ┌────────────────────────┐ - │[0]: a shape 0:1 grad_a│ - │┌┬─────────┐ │ - │││axis 0 │ │ - │├┼─────────┤ │ - │││ 1.38e+2 │ │ - │└┴─────────┘ │ - └────────────────────────┘ + └─────────────────┘┌────────────────────────┐ + │[0]: a shape 0:1 grad_a│ + │┌┬─────────┐ │ + │││axis 0 │ │ + │├┼─────────┤ │ + │││ 1.38e+2 │ │ + │└┴─────────┘ │ + └────────────────────────┘ |}]; Tensor.print ~with_code:false ~with_grad:true `Default b; [%expect @@ -72,15 +71,14 @@ let%expect_test "Micrograd README basic example" = │├┼──────┤ │ │││ 2.00 │ │ │└┴──────┘ │ - └─────────────────┘ - ┌────────────────────────┐ - │[2]: b shape 0:1 grad_b│ - │┌┬─────────┐ │ - │││axis 0 │ │ - │├┼─────────┤ │ - │││ 6.45e+2 │ │ - │└┴─────────┘ │ - └────────────────────────┘ + └─────────────────┘┌────────────────────────┐ + │[2]: b shape 0:1 grad_b│ + │┌┬─────────┐ │ + │││axis 0 │ │ + │├┼─────────┤ │ + │││ 6.45e+2 │ │ + │└┴─────────┘ │ + └────────────────────────┘ |}] let%expect_test "Micrograd half-moons example" = File "test/hello_world_op.ml", line 1, characters 0-0: /usr/bin/git --no-pager diff --no-index --color=always -u _build/default/test/hello_world_op.ml _build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/hello_world_op.ml.corrected diff --git a/_build/default/test/hello_world_op.ml b/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/hello_world_op.ml.corrected index ba9d7ef..6b90c44 100644 --- a/_build/default/test/hello_world_op.ml +++ b/_build/.sandbox/55a5b0641fd7c10700572f19d8669cf5/default/test/hello_world_op.ml.corrected @@ -102,36 +102,39 @@ let%expect_test "Print constant tensor" = let%op hey = [ (1, 2, 3); (4, 5, 6) ] in Train.forward_and_forget backend ctx hey; Tensor.print ~with_code:false ~with_grad:false `Inline @@ hey; - [%expect {| [1.00, 2.00, 3.00; 4.00, 5.00, 6.00] |}]; + [%expect {| [ 1.00 , 2.00 , 3.00 ; 4.00 , 5.00 , 6.00 ][0]: c2x3_hey shape 1:3->0:2 |}]; Tensor.print ~with_code:false ~with_grad:false `Default @@ hey; [%expect {| - ┌─────────────────────────────────────────────────────────────┐ - │[0]: [1.00, 2.00, 3.00; 4.00, 5.00, 6.00]_hey shape 1:3->0:2 │ - │┌──────┬──────────────────┐ │ - ││ │axis 1 │ │ - │├──────┼──────────────────┤ │ - ││axis 0│ 1.00 2.00 3.00 │ │ - ││ │ 4.00 5.00 6.00 │ │ - │└──────┴──────────────────┘ │ - └─────────────────────────────────────────────────────────────┘ + ┌─────────────────────────────┐ + │[0]: c2x3_hey shape 1:3->0:2 │ + │┌──────┬──────────────────┐ │ + ││ │axis 1 │ │ + │├──────┼──────────────────┤ │ + ││axis 0│ 1.00 2.00 3.00 │ │ + ││ │ 4.00 5.00 6.00 │ │ + │└──────┴──────────────────┘ │ + └─────────────────────────────┘ |}]; let%op hoo = [| [ 1; 2; 3 ]; [ 4; 5; 6 ] |] in Train.forward_and_forget backend ctx hoo; Tensor.print ~with_code:false ~with_grad:false `Inline @@ hoo; - [%expect {| [|[1.00; 2.00; 3.00]; [4.00; 5.00; 6.00]|] |}]; + [%expect {| + [| [ 1.00 ; 2.00 ; 3.00 ] ; [ 4.00 ; 5.00 ; 6.00 ] |][1]: c2x3_hoo shape + 0:2|1:3 + |}]; Tensor.print ~with_code:false ~with_grad:false `Default @@ hoo; [%expect {| - ┌──────────────────────────────────────────────────────────────────┐ - │[1]: [|[1.00; 2.00; 3.00]; [4.00; 5.00; 6.00]|]_hoo shape 0:2|1:3 │ - │┌──────┬──────────────────┐ │ - ││ │axis 1 │ │ - │├──────┼──────────────────┤ │ - ││axis 0│ 1.00 2.00 3.00 │ │ - ││ │ 4.00 5.00 6.00 │ │ - │└──────┴──────────────────┘ │ - └──────────────────────────────────────────────────────────────────┘ + ┌────────────────────────────┐ + │[1]: c2x3_hoo shape 0:2|1:3 │ + │┌──────┬──────────────────┐ │ + ││ │axis 1 │ │ + │├──────┼──────────────────┤ │ + ││axis 0│ 1.00 2.00 3.00 │ │ + ││ │ 4.00 5.00 6.00 │ │ + │└──────┴──────────────────┘ │ + └────────────────────────────┘ |}]; let%op hey2 = [ @@ -145,10 +148,12 @@ let%expect_test "Print constant tensor" = Tensor.print ~with_code:false ~with_grad:false `Inline @@ hey2; [%expect {| - [(1.00, 2.00, 3.00), (4.00, 5.00, 6.00); - (7.00, 8.00, 9.00), (10.00, 11.00, 12.00); - (13.00, 14.00, 15.00), (16.00, 17.00, 18.00); - (19.00, 20.00, 21.00), (22.00, 23.00, 24.00)] + [ + ( 1.00 , 2.00 , 3.00 ) , ( 4.00 , 5.00 , 6.00 ) + ; ( 7.00 , 8.00 , 9.00 ) , ( 10.00 , 11.00 , 12.00 ) + ; ( 13.00 , 14.00 , 15.00 ) , ( 16.00 , 17.00 , 18.00 ) + ; ( 19.00 , 20.00 , 21.00 ) , ( 22.00 , 23.00 , 24.00 ) + ][2]: c4x2x3_hey2 shape 1:2,2:3->0:4 |}]; Tensor.print ~with_code:false ~with_grad:false `Default @@ hey2; [%expect @@ -178,10 +183,12 @@ let%expect_test "Print constant tensor" = Tensor.print ~with_code:false ~with_grad:false `Inline @@ hoo2; [%expect {| - [|[[1.00; 2.00; 3.00]; [4.00; 5.00; 6.00]]; - [[7.00; 8.00; 9.00]; [10.00; 11.00; 12.00]]; - [[13.00; 14.00; 15.00]; [16.00; 17.00; 18.00]]; - [[19.00; 20.00; 21.00]; [22.00; 23.00; 24.00]]|] + [| + [ [ 1.00 ; 2.00 ; 3.00 ] ; [ 4.00 ; 5.00 ; 6.00 ] ] + ; [ [ 7.00 ; 8.00 ; 9.00 ] ; [ 10.00 ; 11.00 ; 12.00 ] ] + ; [ [ 13.00 ; 14.00 ; 15.00 ] ; [ 16.00 ; 17.00 ; 18.00 ] ] + ; [ [ 19.00 ; 20.00 ; 21.00 ] ; [ 22.00 ; 23.00 ; 24.00 ] ] + |][3]: c4x2x3_hoo2 shape 0:4|1:2,2:3 |}]; Tensor.print ~with_code:false ~with_grad:false `Default @@ hoo2; [%expect @@ -209,10 +216,12 @@ let%expect_test "Print constant tensor" = Tensor.print ~with_code:false ~with_grad:false `Inline @@ heyhoo; [%expect {| - [|[|[1.00; 2.00; 3.00]; [4.00; 5.00; 6.00]|]; - [|[7.00; 8.00; 9.00]; [10.00; 11.00; 12.00]|]; - [|[13.00; 14.00; 15.00]; [16.00; 17.00; 18.00]|]; - [|[19.00; 20.00; 21.00]; [22.00; 23.00; 24.00]|]|] + [| + [| [ 1.00 ; 2.00 ; 3.00 ] ; [ 4.00 ; 5.00 ; 6.00 ] |] + ; [| [ 7.00 ; 8.00 ; 9.00 ] ; [ 10.00 ; 11.00 ; 12.00 ] |] + ; [| [ 13.00 ; 14.00 ; 15.00 ] ; [ 16.00 ; 17.00 ; 18.00 ] |] + ; [| [ 19.00 ; 20.00 ; 21.00 ] ; [ 22.00 ; 23.00 ; 24.00 ] |] + |][4]: c4x2x3_heyhoo shape 0:4,1:2|2:3 |}]; Tensor.print ~with_code:false ~with_grad:false `Default @@ heyhoo; [%expect @@ -241,14 +250,23 @@ let%expect_test "Print constant tensor" = [%expect {| [| - [|[[1.00; 31.00]; [2.00; 32.00]; [3.00; 33.00]]; - [[4.00; 34.00]; [5.00; 35.00]; [6.00; 36.00]]|]; - [|[[7.00; 37.00]; [8.00; 38.00]; [9.00; 39.00]]; - [[10.00; 40.00]; [11.00; 41.00]; [12.00; 42.00]]|]; - [|[[13.00; 43.00]; [14.00; 44.00]; [15.00; 45.00]]; - [[16.00; 46.00]; [17.00; 47.00]; [18.00; 48.00]]|]; - [|[[19.00; 49.00]; [20.00; 50.00]; [21.00; 51.00]]; - [[22.00; 52.00]; [23.00; 53.00]; [24.00; 54.00]]|]|] + [| + [ [ 1.00 ; 31.00 ] ; [ 2.00 ; 32.00 ] ; [ 3.00 ; 33.00 ] ] + ; [ [ 4.00 ; 34.00 ] ; [ 5.00 ; 35.00 ] ; [ 6.00 ; 36.00 ] ] + |] + ; [| + [ [ 7.00 ; 37.00 ] ; [ 8.00 ; 38.00 ] ; [ 9.00 ; 39.00 ] ] + ; [ [ 10.00 ; 40.00 ] ; [ 11.00 ; 41.00 ] ; [ 12.00 ; 42.00 ] ] + |] + ; [| + [ [ 13.00 ; 43.00 ] ; [ 14.00 ; 44.00 ] ; [ 15.00 ; 45.00 ] ] + ; [ [ 16.00 ; 46.00 ] ; [ 17.00 ; 47.00 ] ; [ 18.00 ; 48.00 ] ] + |] + ; [| + [ [ 19.00 ; 49.00 ] ; [ 20.00 ; 50.00 ] ; [ 21.00 ; 51.00 ] ] + ; [ [ 22.00 ; 52.00 ] ; [ 23.00 ; 53.00 ] ; [ 24.00 ; 54.00 ] ] + |] + |][5]: c4x2x3x2_heyhoo2 shape 0:4,1:2|2:3,3:2 |}]; Tensor.print ~with_code:false ~with_grad:false `Default @@ heyhoo2; [%expect @@ -295,15 +313,26 @@ let%expect_test "Print constant tensor" = {| [| [| - [[[1.00; 31.00]; [2.00; 32.00]; [3.00; 33.00]]; - [[4.00; 34.00]; [5.00; 35.00]; [6.00; 36.00]]]; - [[[7.00; 37.00]; [8.00; 38.00]; [9.00; 39.00]]; - [[10.00; 40.00]; [11.00; 41.00]; [12.00; 42.00]]]|]; - [| - [[[13.00; 43.00]; [14.00; 44.00]; [15.00; 45.00]]; - [[16.00; 46.00]; [17.00; 47.00]; [18.00; 48.00]]]; - [[[19.00; 49.00]; [20.00; 50.00]; [21.00; 51.00]]; - [[22.00; 52.00]; [23.00; 53.00]; [24.00; 54.00]]]|]|] + [ + [ [ 1.00 ; 31.00 ] ; [ 2.00 ; 32.00 ] ; [ 3.00 ; 33.00 ] ] + ; [ [ 4.00 ; 34.00 ] ; [ 5.00 ; 35.00 ] ; [ 6.00 ; 36.00 ] ] + ] + ; [ + [ [ 7.00 ; 37.00 ] ; [ 8.00 ; 38.00 ] ; [ 9.00 ; 39.00 ] ] + ; [ [ 10.00 ; 40.00 ] ; [ 11.00 ; 41.00 ] ; [ 12.00 ; 42.00 ] ] + ] + |] + ; [| + [ + [ [ 13.00 ; 43.00 ] ; [ 14.00 ; 44.00 ] ; [ 15.00 ; 45.00 ] ] + ; [ [ 16.00 ; 46.00 ] ; [ 17.00 ; 47.00 ] ; [ 18.00 ; 48.00 ] ] + ] + ; [ + [ [ 19.00 ; 49.00 ] ; [ 20.00 ; 50.00 ] ; [ 21.00 ; 51.00 ] ] + ; [ [ 22.00 ; 52.00 ] ; [ 23.00 ; 53.00 ] ; [ 24.00 ; 54.00 ] ] + ] + |] + |][6]: c2x2x2x3x2_heyhoo3 shape 0:2,1:2|2:2,3:3,4:2 |}]; Tensor.print ~with_code:false ~with_grad:false `Default @@ heyhoo3; [%expect @@ -355,15 +384,26 @@ let%expect_test "Print constant tensor" = {| [| [ - [[1.00, 31.00; 2.00, 32.00; 3.00, 33.00]; - [4.00, 34.00; 5.00, 35.00; 6.00, 36.00]]; - [[7.00, 37.00; 8.00, 38.00; 9.00, 39.00]; - [10.00, 40.00; 11.00, 41.00; 12.00, 42.00]]]; - [ - [[13.00, 43.00; 14.00, 44.00; 15.00, 45.00]; - [16.00, 46.00; 17.00, 47.00; 18.00, 48.00]]; - [[19.00, 49.00; 20.00, 50.00; 21.00, 51.00]; - [22.00, 52.00; 23.00, 53.00; 24.00, 54.00]]]|] + [ + [ 1.00 , 31.00 ; 2.00 , 32.00 ; 3.00 , 33.00 ] + ; [ 4.00 , 34.00 ; 5.00 , 35.00 ; 6.00 , 36.00 ] + ] + ; [ + [ 7.00 , 37.00 ; 8.00 , 38.00 ; 9.00 , 39.00 ] + ; [ 10.00 , 40.00 ; 11.00 , 41.00 ; 12.00 , 42.00 ] + ] + ] + ; [ + [ + [ 13.00 , 43.00 ; 14.00 , 44.00 ; 15.00 , 45.00 ] + ; [ 16.00 , 46.00 ; 17.00 , 47.00 ; 18.00 , 48.00 ] + ] + ; [ + [ 19.00 , 49.00 ; 20.00 , 50.00 ; 21.00 , 51.00 ] + ; [ 22.00 , 52.00 ; 23.00 , 53.00 ; 24.00 , 54.00 ] + ] + ] + |][7]: c2x2x2x3x2_heyhoo4 shape 0:2|4:2->1:2,2:2,3:3 |}]; Tensor.print ~with_code:false ~with_grad:false `Default @@ heyhoo4; [%expect @@ -462,8 +502,29 @@ let%expect_test "Big matrix" = Tensor.print ~with_code:false ~with_grad:false `Inline zero_to_twenty; [%expect {| - [0.00; 1.00; 2.00; 3.00; 4.00; 5.00; 6.00; 7.00; 8.00; 9.00; 10.00; 11.00; - 12.00; 13.00; 14.00; 15.00; 16.00; 17.00; 18.00; 19.00; 20.00] + [ + 0.00 + ; 1.00 + ; 2.00 + ; 3.00 + ; 4.00 + ; 5.00 + ; 6.00 + ; 7.00 + ; 8.00 + ; 9.00 + ; 10.00 + ; 11.00 + ; 12.00 + ; 13.00 + ; 14.00 + ; 15.00 + ; 16.00 + ; 17.00 + ; 18.00 + ; 19.00 + ; 20.00 + ][2]: 0...20 shape 0:21 |}]; Tensor.print ~with_code:false ~with_grad:false `Default zero_to_twenty; [%expect (cd _build/default/test && ./moons_demo_parallel_run.exe) Welcome to OCANNL! Reading configuration defaults from /src/_build/default/test/ocannl_config. Retrieving commandline, environment, or config file variable ocannl_log_level Found 0, in the config file ("Set log_level to" 1) └─{orphaned from #2} Retrieving commandline, environment, or config file variable ocannl_backend Found multicore_cc, in the config file Properties of devices: (multicore_devices (device ((device_name CPU) (device_ordinal 0) (num_domains 72)))) @!Retrieving commandline, environment, or config file variable ocannl_prefer_backend_uniformity Found true, in the config file Retrieving commandline, environment, or config file variable ocannl_debug_log_to_stream_files Not found, using default false Retrieving commandline, environment, or config file variable ocannl_ll_ident_style Not found, using default heuristic Retrieving commandline, environment, or config file variable ocannl_cc_backend_optimization_level Not found, using default 3 Retrieving commandline, environment, or config file variable ocannl_cc_backend_compiler_command Not found, using default gcc Retrieving commandline, environment, or config file variable ocannl_never_capture_stdout Not found, using default false Batch=59, step=60, lr=0.200000, batch loss=23.609453, epoch loss=23.609453 Batch=119, step=120, lr=0.199750, batch loss=8.539634, epoch loss=32.149087 Batch=179, step=180, lr=0.199500, batch loss=2.626295, epoch loss=34.775382 Batch=239, step=240, lr=0.199250, batch loss=0.849657, epoch loss=35.625039 Batch=299, step=300, lr=0.199000, batch loss=1.447177, epoch loss=37.072216 Batch=359, step=360, lr=0.198750, batch loss=1.329296, epoch loss=38.401512 Batch=419, step=420, lr=0.198500, batch loss=0.618569, epoch loss=39.020081 Batch=479, step=480, lr=0.198250, batch loss=0.822060, epoch loss=39.842141 Batch=539, step=540, lr=0.198000, batch loss=0.690244, epoch loss=40.532385 Batch=599, step=600, lr=0.197750, batch loss=1.063878, epoch loss=41.596263 Batch=659, step=660, lr=0.197500, batch loss=0.483340, epoch loss=42.079603 Batch=719, step=720, lr=0.197250, batch loss=0.411299, epoch loss=42.490902 Batch=779, step=780, lr=0.197000, batch loss=0.470123, epoch loss=42.961024 Batch=839, step=840, lr=0.196750, batch loss=0.446661, epoch loss=43.407685 Batch=899, step=900, lr=0.196500, batch loss=0.382721, epoch loss=43.790407 Batch=959, step=960, lr=0.196250, batch loss=0.245136, epoch loss=44.035543 Batch=1019, step=1020, lr=0.196000, batch loss=0.466506, epoch loss=44.502049 Batch=1079, step=1080, lr=0.195750, batch loss=0.248781, epoch loss=44.750829 Batch=1139, step=1140, lr=0.195500, batch loss=0.317440, epoch loss=45.068269 Batch=1199, step=1200, lr=0.195250, batch loss=0.263683, epoch loss=45.331952 Epoch=0, step=1200, lr=0.195250, epoch loss=45.331952 Batch=59, step=1260, lr=0.195000, batch loss=0.262138, epoch loss=0.262138 Batch=119, step=1320, lr=0.194750, batch loss=0.205243, epoch loss=0.467381 Batch=179, step=1380, lr=0.194500, batch loss=0.243644, epoch loss=0.711025 Batch=239, step=1440, lr=0.194250, batch loss=0.347897, epoch loss=1.058921 Batch=299, step=1500, lr=0.194000, batch loss=0.247348, epoch loss=1.306269 Batch=359, step=1560, lr=0.193750, batch loss=0.316559, epoch loss=1.622828 Batch=419, step=1620, lr=0.193500, batch loss=0.312735, epoch loss=1.935563 Batch=479, step=1680, lr=0.193250, batch loss=0.276268, epoch loss=2.211831 Batch=539, step=1740, lr=0.193000, batch loss=0.209826, epoch loss=2.421657 Batch=599, step=1800, lr=0.192750, batch loss=0.250384, epoch loss=2.672042 Batch=659, step=1860, lr=0.192500, batch loss=0.367201, epoch loss=3.039243 Batch=719, step=1920, lr=0.192250, batch loss=0.354917, epoch loss=3.394160 Batch=779, step=1980, lr=0.192000, batch loss=0.381382, epoch loss=3.775542 Batch=839, step=2040, lr=0.191750, batch loss=0.339637, epoch loss=4.115179 Batch=899, step=2100, lr=0.191500, batch loss=0.295234, epoch loss=4.410413 Batch=959, step=2160, lr=0.191250, batch loss=0.214033, epoch loss=4.624446 Batch=1019, step=2220, lr=0.191000, batch loss=0.330972, epoch loss=4.955419 Batch=1079, step=2280, lr=0.190750, batch loss=0.208236, epoch loss=5.163654 Batch=1139, step=2340, lr=0.190500, batch loss=0.278374, epoch loss=5.442028 Batch=1199, step=2400, lr=0.190250, batch loss=0.220793, epoch loss=5.662821 Epoch=1, step=2400, lr=0.190250, epoch loss=5.662821 Batch=59, step=2460, lr=0.190000, batch loss=0.230363, epoch loss=0.230363 Batch=119, step=2520, lr=0.189750, batch loss=0.195962, epoch loss=0.426325 Batch=179, step=2580, lr=0.189500, batch loss=0.221156, epoch loss=0.647481 Batch=239, step=2640, lr=0.189250, batch loss=0.328098, epoch loss=0.975578 Batch=299, step=2700, lr=0.189000, batch loss=0.202947, epoch loss=1.178525 Batch=359, step=2760, lr=0.188750, batch loss=0.289890, epoch loss=1.468415 Batch=419, step=2820, lr=0.188500, batch loss=0.281744, epoch loss=1.750160 Batch=479, step=2880, lr=0.188250, batch loss=0.264844, epoch loss=2.015004 Batch=539, step=2940, lr=0.188000, batch loss=0.203798, epoch loss=2.218802 Batch=599, step=3000, lr=0.187750, batch loss=0.248079, epoch loss=2.466881 Batch=659, step=3060, lr=0.187500, batch loss=0.345056, epoch loss=2.811937 Batch=719, step=3120, lr=0.187250, batch loss=0.343542, epoch loss=3.155479 Batch=779, step=3180, lr=0.187000, batch loss=0.366989, epoch loss=3.522468 Batch=839, step=3240, lr=0.186750, batch loss=0.321779, epoch loss=3.844248 Batch=899, step=3300, lr=0.186500, batch loss=0.283865, epoch loss=4.128112 Batch=959, step=3360, lr=0.186250, batch loss=0.214411, epoch loss=4.342523 Batch=1019, step=3420, lr=0.186000, batch loss=0.306400, epoch loss=4.648923 Batch=1079, step=3480, lr=0.185750, batch loss=0.177313, epoch loss=4.826236 Batch=1139, step=3540, lr=0.185500, batch loss=0.235576, epoch loss=5.061812 Batch=1199, step=3600, lr=0.185250, batch loss=0.197911, epoch loss=5.259723 Epoch=2, step=3600, lr=0.185250, epoch loss=5.259723 Batch=59, step=3660, lr=0.185000, batch loss=0.226539, epoch loss=0.226539 Batch=119, step=3720, lr=0.184750, batch loss=0.191802, epoch loss=0.418341 Batch=179, step=3780, lr=0.184500, batch loss=0.210712, epoch loss=0.629053 Batch=239, step=3840, lr=0.184250, batch loss=0.314104, epoch loss=0.943157 Batch=299, step=3900, lr=0.184000, batch loss=0.206011, epoch loss=1.149168 Batch=359, step=3960, lr=0.183750, batch loss=0.291253, epoch loss=1.440420 Batch=419, step=4020, lr=0.183500, batch loss=0.297434, epoch loss=1.737854 Batch=479, step=4080, lr=0.183250, batch loss=0.260511, epoch loss=1.998365 Batch=539, step=4140, lr=0.183000, batch loss=0.195229, epoch loss=2.193593 Batch=599, step=4200, lr=0.182750, batch loss=0.230395, epoch loss=2.423989 Batch=659, step=4260, lr=0.182500, batch loss=0.337132, epoch loss=2.761121 Batch=719, step=4320, lr=0.182250, batch loss=0.347122, epoch loss=3.108243 Batch=779, step=4380, lr=0.181750, batch loss=0.346320, epoch loss=3.454563 Batch=839, step=4440, lr=0.181750, batch loss=0.317728, epoch loss=3.772291 Batch=899, step=4500, lr=0.181500, batch loss=0.283974, epoch loss=4.056265 Batch=959, step=4560, lr=0.181250, batch loss=0.238280, epoch loss=4.294546 Batch=1019, step=4620, lr=0.181000, batch loss=0.337006, epoch loss=4.631552 Batch=1079, step=4680, lr=0.180750, batch loss=0.208471, epoch loss=4.840023 Batch=1139, step=4740, lr=0.180500, batch loss=0.249282, epoch loss=5.089305 Batch=1199, step=4800, lr=0.180250, batch loss=0.191768, epoch loss=5.281073 Epoch=3, step=4800, lr=0.180250, epoch loss=5.281073 Batch=59, step=4860, lr=0.180000, batch loss=0.228017, epoch loss=0.228017 Batch=119, step=4920, lr=0.179750, batch loss=0.190270, epoch loss=0.418287 Batch=179, step=4980, lr=0.179500, batch loss=0.205910, epoch loss=0.624197 Batch=239, step=5040, lr=0.179250, batch loss=0.309041, epoch loss=0.933238 Batch=299, step=5100, lr=0.179000, batch loss=0.204646, epoch loss=1.137884 Batch=359, step=5160, lr=0.178750, batch loss=0.271107, epoch loss=1.408991 Batch=419, step=5220, lr=0.178500, batch loss=0.264065, epoch loss=1.673057 Batch=479, step=5280, lr=0.178250, batch loss=0.239668, epoch loss=1.912725 Batch=539, step=5340, lr=0.178000, batch loss=0.189489, epoch loss=2.102215 Batch=599, step=5400, lr=0.177750, batch loss=0.230954, epoch loss=2.333169 Batch=659, step=5460, lr=0.177500, batch loss=0.323638, epoch loss=2.656807 Batch=719, step=5520, lr=0.177250, batch loss=0.325823, epoch loss=2.982630 Batch=779, step=5580, lr=0.177000, batch loss=0.343232, epoch loss=3.325862 Batch=839, step=5640, lr=0.176750, batch loss=0.309310, epoch loss=3.635172 Batch=899, step=5700, lr=0.176500, batch loss=0.273221, epoch loss=3.908392 Batch=959, step=5760, lr=0.176250, batch loss=0.214833, epoch loss=4.123225 Batch=1019, step=5820, lr=0.176000, batch loss=0.339281, epoch loss=4.462506 Batch=1079, step=5880, lr=0.175750, batch loss=0.207743, epoch loss=4.670249 Batch=1139, step=5940, lr=0.175500, batch loss=0.240048, epoch loss=4.910297 Batch=1199, step=6000, lr=0.175250, batch loss=0.186869, epoch loss=5.097166 Epoch=4, step=6000, lr=0.175250, epoch loss=5.097166 Batch=59, step=6060, lr=0.175000, batch loss=0.230518, epoch loss=0.230518 Batch=119, step=6120, lr=0.174750, batch loss=0.194310, epoch loss=0.424828 Batch=179, step=6180, lr=0.174500, batch loss=0.201550, epoch loss=0.626378 Batch=239, step=6240, lr=0.174250, batch loss=0.302377, epoch loss=0.928754 Batch=299, step=6300, lr=0.174000, batch loss=0.203945, epoch loss=1.132699 Batch=359, step=6360, lr=0.173750, batch loss=0.266100, epoch loss=1.398799 Batch=419, step=6420, lr=0.173500, batch loss=0.265299, epoch loss=1.664098 Batch=479, step=6480, lr=0.173250, batch loss=0.243310, epoch loss=1.907409 Batch=539, step=6540, lr=0.173000, batch loss=0.192980, epoch loss=2.100389 Batch=599, step=6600, lr=0.172750, batch loss=0.234488, epoch loss=2.334876 Batch=659, step=6660, lr=0.172500, batch loss=0.312120, epoch loss=2.646996 Batch=719, step=6720, lr=0.172250, batch loss=0.314230, epoch loss=2.961227 Batch=779, step=6780, lr=0.172000, batch loss=0.333233, epoch loss=3.294459 Batch=839, step=6840, lr=0.171750, batch loss=0.303759, epoch loss=3.598218 Batch=899, step=6900, lr=0.171500, batch loss=0.268478, epoch loss=3.866696 Batch=959, step=6960, lr=0.171250, batch loss=0.211032, epoch loss=4.077728 Batch=1019, step=7020, lr=0.171000, batch loss=0.330458, epoch loss=4.408187 Batch=1079, step=7080, lr=0.170750, batch loss=0.180851, epoch loss=4.589037 Batch=1139, step=7140, lr=0.170500, batch loss=0.216318, epoch loss=4.805355 Batch=1199, step=7200, lr=0.170250, batch loss=0.181918, epoch loss=4.987273 Epoch=5, step=7200, lr=0.170250, epoch loss=4.987273 Batch=59, step=7260, lr=0.170000, batch loss=0.232875, epoch loss=0.232875 Batch=119, step=7320, lr=0.169750, batch loss=0.184461, epoch loss=0.417336 Batch=179, step=7380, lr=0.169500, batch loss=0.196302, epoch loss=0.613638 Batch=239, step=7440, lr=0.169250, batch loss=0.290845, epoch loss=0.904483 Batch=299, step=7500, lr=0.169000, batch loss=0.200805, epoch loss=1.105288 Batch=359, step=7560, lr=0.168750, batch loss=0.258458, epoch loss=1.363747 Batch=419, step=7620, lr=0.168500, batch loss=0.256789, epoch loss=1.620536 Batch=479, step=7680, lr=0.168250, batch loss=0.236038, epoch loss=1.856573 Batch=539, step=7740, lr=0.168000, batch loss=0.187862, epoch loss=2.044435 Batch=599, step=7800, lr=0.167750, batch loss=0.223971, epoch loss=2.268406 Batch=659, step=7860, lr=0.167500, batch loss=0.305889, epoch loss=2.574295 Batch=719, step=7920, lr=0.167250, batch loss=0.309334, epoch loss=2.883629 Batch=779, step=7980, lr=0.166750, batch loss=0.329980, epoch loss=3.213609 Batch=839, step=8040, lr=0.166750, batch loss=0.292374, epoch loss=3.505983 Batch=899, step=8100, lr=0.166500, batch loss=0.261850, epoch loss=3.767833 Batch=959, step=8160, lr=0.166250, batch loss=0.193183, epoch loss=3.961016 Batch=1019, step=8220, lr=0.166000, batch loss=0.301075, epoch loss=4.262091 Batch=1079, step=8280, lr=0.165750, batch loss=0.183495, epoch loss=4.445586 Batch=1139, step=8340, lr=0.165250, batch loss=0.215283, epoch loss=4.660869 Batch=1199, step=8400, lr=0.165250, batch loss=0.172443, epoch loss=4.833312 Epoch=6, step=8400, lr=0.165250, epoch loss=4.833312 Batch=59, step=8460, lr=0.165000, batch loss=0.213083, epoch loss=0.213083 Batch=119, step=8520, lr=0.164750, batch loss=0.177617, epoch loss=0.390701 Batch=179, step=8580, lr=0.164500, batch loss=0.188843, epoch loss=0.579543 Batch=239, step=8640, lr=0.164250, batch loss=0.279680, epoch loss=0.859224 Batch=299, step=8700, lr=0.164000, batch loss=0.191912, epoch loss=1.051136 Batch=359, step=8760, lr=0.163750, batch loss=0.248286, epoch loss=1.299422 Batch=419, step=8820, lr=0.163500, batch loss=0.244511, epoch loss=1.543933 Batch=479, step=8880, lr=0.163250, batch loss=0.229612, epoch loss=1.773545 Batch=539, step=8940, lr=0.163000, batch loss=0.176868, epoch loss=1.950414 Batch=599, step=9000, lr=0.162750, batch loss=0.218401, epoch loss=2.168814 Batch=659, step=9060, lr=0.162500, batch loss=0.294772, epoch loss=2.463587 Batch=719, step=9120, lr=0.162250, batch loss=0.299183, epoch loss=2.762770 Batch=779, step=9180, lr=0.162000, batch loss=0.315969, epoch loss=3.078739 Batch=839, step=9240, lr=0.161750, batch loss=0.281910, epoch loss=3.360649 Batch=899, step=9300, lr=0.161500, batch loss=0.252928, epoch loss=3.613577 Batch=959, step=9360, lr=0.161250, batch loss=0.210650, epoch loss=3.824227 Batch=1019, step=9420, lr=0.161000, batch loss=0.298332, epoch loss=4.122559 Batch=1079, step=9480, lr=0.160750, batch loss=0.177888, epoch loss=4.300447 Batch=1139, step=9540, lr=0.160500, batch loss=0.206021, epoch loss=4.506468 Batch=1199, step=9600, lr=0.160250, batch loss=0.164503, epoch loss=4.670970 Epoch=7, step=9600, lr=0.160250, epoch loss=4.670970 Batch=59, step=9660, lr=0.160000, batch loss=0.191391, epoch loss=0.191391 Batch=119, step=9720, lr=0.159750, batch loss=0.162918, epoch loss=0.354309 Batch=179, step=9780, lr=0.159500, batch loss=0.178846, epoch loss=0.533155 Batch=239, step=9840, lr=0.159250, batch loss=0.261184, epoch loss=0.794339 Batch=299, step=9900, lr=0.159000, batch loss=0.183823, epoch loss=0.978162 Batch=359, step=9960, lr=0.158750, batch loss=0.245289, epoch loss=1.223452 Batch=419, step=10020, lr=0.158500, batch loss=0.243661, epoch loss=1.467112 Batch=479, step=10080, lr=0.158250, batch loss=0.222567, epoch loss=1.689679 Batch=539, step=10140, lr=0.158000, batch loss=0.164829, epoch loss=1.854508 Batch=599, step=10200, lr=0.157750, batch loss=0.197303, epoch loss=2.051811 Batch=659, step=10260, lr=0.157500, batch loss=0.282838, epoch loss=2.334648 Batch=719, step=10320, lr=0.157250, batch loss=0.278044, epoch loss=2.612693 Batch=779, step=10380, lr=0.157000, batch loss=0.295767, epoch loss=2.908460 Batch=839, step=10440, lr=0.156750, batch loss=0.269780, epoch loss=3.178240 Batch=899, step=10500, lr=0.156500, batch loss=0.237353, epoch loss=3.415593 Batch=959, step=10560, lr=0.156250, batch loss=0.176188, epoch loss=3.591781 Batch=1019, step=10620, lr=0.156000, batch loss=0.298612, epoch loss=3.890393 Batch=1079, step=10680, lr=0.155750, batch loss=0.179117, epoch loss=4.069510 Batch=1139, step=10740, lr=0.155500, batch loss=0.200034, epoch loss=4.269544 Batch=1199, step=10800, lr=0.155250, batch loss=0.155235, epoch loss=4.424779 Epoch=8, step=10800, lr=0.155250, epoch loss=4.424779 Batch=59, step=10860, lr=0.155000, batch loss=0.177595, epoch loss=0.177595 Batch=119, step=10920, lr=0.154750, batch loss=0.152798, epoch loss=0.330394 Batch=179, step=10980, lr=0.154500, batch loss=0.166502, epoch loss=0.496896 Batch=239, step=11040, lr=0.154250, batch loss=0.245783, epoch loss=0.742678 Batch=299, step=11100, lr=0.154000, batch loss=0.161161, epoch loss=0.903839 Batch=359, step=11160, lr=0.153750, batch loss=0.224733, epoch loss=1.128573 Batch=419, step=11220, lr=0.153500, batch loss=0.234405, epoch loss=1.362978 Batch=479, step=11280, lr=0.153250, batch loss=0.197961, epoch loss=1.560939 Batch=539, step=11340, lr=0.153000, batch loss=0.157921, epoch loss=1.718860 Batch=599, step=11400, lr=0.152750, batch loss=0.179983, epoch loss=1.898842 Batch=659, step=11460, lr=0.152500, batch loss=0.263029, epoch loss=2.161872 Batch=719, step=11520, lr=0.152250, batch loss=0.257562, epoch loss=2.419434 Batch=779, step=11580, lr=0.152000, batch loss=0.269217, epoch loss=2.688651 Batch=839, step=11640, lr=0.151750, batch loss=0.250690, epoch loss=2.939341 Batch=899, step=11700, lr=0.151500, batch loss=0.216362, epoch loss=3.155703 Batch=959, step=11760, lr=0.151250, batch loss=0.173815, epoch loss=3.329518 Batch=1019, step=11820, lr=0.151000, batch loss=0.260681, epoch loss=3.590199 Batch=1079, step=11880, lr=0.150750, batch loss=0.139080, epoch loss=3.729279 Batch=1139, step=11940, lr=0.150250, batch loss=0.173830, epoch loss=3.903109 Batch=1199, step=12000, lr=0.150250, batch loss=0.138370, epoch loss=4.041479 Epoch=9, step=12000, lr=0.150250, epoch loss=4.041479 Batch=59, step=12060, lr=0.150000, batch loss=0.162565, epoch loss=0.162565 Batch=119, step=12120, lr=0.149750, batch loss=0.135469, epoch loss=0.298035 Batch=179, step=12180, lr=0.149500, batch loss=0.149796, epoch loss=0.447830 Batch=239, step=12240, lr=0.149250, batch loss=0.218263, epoch loss=0.666094 Batch=299, step=12300, lr=0.149000, batch loss=0.141623, epoch loss=0.807717 Batch=359, step=12360, lr=0.148750, batch loss=0.197263, epoch loss=1.004979 Batch=419, step=12420, lr=0.148500, batch loss=0.204632, epoch loss=1.209611 Batch=479, step=12480, lr=0.148250, batch loss=0.179521, epoch loss=1.389133 Batch=539, step=12540, lr=0.148000, batch loss=0.141305, epoch loss=1.530437 Batch=599, step=12600, lr=0.147750, batch loss=0.149812, epoch loss=1.680249 Batch=659, step=12660, lr=0.147500, batch loss=0.224474, epoch loss=1.904723 Batch=719, step=12720, lr=0.147250, batch loss=0.235616, epoch loss=2.140339 Batch=779, step=12780, lr=0.147000, batch loss=0.263020, epoch loss=2.403359 Batch=839, step=12840, lr=0.146750, batch loss=0.235134, epoch loss=2.638492 Batch=899, step=12900, lr=0.146500, batch loss=0.229787, epoch loss=2.868280 Batch=959, step=12960, lr=0.146250, batch loss=0.139509, epoch loss=3.007789 Batch=1019, step=13020, lr=0.146000, batch loss=0.210324, epoch loss=3.218114 Batch=1079, step=13080, lr=0.145750, batch loss=0.118595, epoch loss=3.336708 Batch=1139, step=13140, lr=0.145500, batch loss=0.158064, epoch loss=3.494772 Batch=1199, step=13200, lr=0.145250, batch loss=0.116643, epoch loss=3.611416 Epoch=10, step=13200, lr=0.145250, epoch loss=3.611416 Batch=59, step=13260, lr=0.145000, batch loss=0.135540, epoch loss=0.135540 Batch=119, step=13320, lr=0.144750, batch loss=0.118161, epoch loss=0.253701 Batch=179, step=13380, lr=0.144500, batch loss=0.126243, epoch loss=0.379944 Batch=239, step=13440, lr=0.144250, batch loss=0.181355, epoch loss=0.561299 Batch=299, step=13500, lr=0.144000, batch loss=0.115306, epoch loss=0.676605 Batch=359, step=13560, lr=0.143750, batch loss=0.159266, epoch loss=0.835871 Batch=419, step=13620, lr=0.143500, batch loss=0.160712, epoch loss=0.996583 Batch=479, step=13680, lr=0.143250, batch loss=0.145111, epoch loss=1.141694 Batch=539, step=13740, lr=0.143000, batch loss=0.118429, epoch loss=1.260123 Batch=599, step=13800, lr=0.142750, batch loss=0.119740, epoch loss=1.379863 Batch=659, step=13860, lr=0.142500, batch loss=0.173772, epoch loss=1.553635 Batch=719, step=13920, lr=0.142000, batch loss=0.175736, epoch loss=1.729372 Batch=779, step=13980, lr=0.142000, batch loss=0.195238, epoch loss=1.924610 Batch=839, step=14040, lr=0.141750, batch loss=0.189123, epoch loss=2.113733 Batch=899, step=14100, lr=0.141500, batch loss=0.188336, epoch loss=2.302070 Batch=959, step=14160, lr=0.141250, batch loss=0.124872, epoch loss=2.426942 Batch=1019, step=14220, lr=0.141000, batch loss=0.238971, epoch loss=2.665912 Batch=1079, step=14280, lr=0.140750, batch loss=0.078813, epoch loss=2.744725 Batch=1139, step=14340, lr=0.140500, batch loss=0.126640, epoch loss=2.871365 Batch=1199, step=14400, lr=0.140250, batch loss=0.086870, epoch loss=2.958235 Epoch=11, step=14400, lr=0.140250, epoch loss=2.958235 Batch=59, step=14460, lr=0.140000, batch loss=0.101548, epoch loss=0.101548 Batch=119, step=14520, lr=0.139750, batch loss=0.099423, epoch loss=0.200971 Batch=179, step=14580, lr=0.139500, batch loss=0.100477, epoch loss=0.301448 Batch=239, step=14640, lr=0.139250, batch loss=0.139681, epoch loss=0.441129 Batch=299, step=14700, lr=0.139000, batch loss=0.076984, epoch loss=0.518112 Batch=359, step=14760, lr=0.138750, batch loss=0.118619, epoch loss=0.636732 Batch=419, step=14820, lr=0.138500, batch loss=0.130945, epoch loss=0.767676 Batch=479, step=14880, lr=0.138250, batch loss=0.098944, epoch loss=0.866621 Batch=539, step=14940, lr=0.138000, batch loss=0.110388, epoch loss=0.977009 Batch=599, step=15000, lr=0.137750, batch loss=0.083173, epoch loss=1.060182 Batch=659, step=15060, lr=0.137500, batch loss=0.126660, epoch loss=1.186842 Batch=719, step=15120, lr=0.137250, batch loss=0.127669, epoch loss=1.314511 Batch=779, step=15180, lr=0.137000, batch loss=0.169174, epoch loss=1.483686 Batch=839, step=15240, lr=0.136750, batch loss=0.169623, epoch loss=1.653309 Batch=899, step=15300, lr=0.136500, batch loss=0.301952, epoch loss=1.955261 Batch=959, step=15360, lr=0.136250, batch loss=0.061375, epoch loss=2.016636 Batch=1019, step=15420, lr=0.136000, batch loss=0.134478, epoch loss=2.151114 Batch=1079, step=15480, lr=0.135500, batch loss=0.042379, epoch loss=2.193493 Batch=1139, step=15540, lr=0.135500, batch loss=0.096354, epoch loss=2.289847 Batch=1199, step=15600, lr=0.135250, batch loss=0.060039, epoch loss=2.349886 Epoch=12, step=15600, lr=0.135250, epoch loss=2.349886 Batch=59, step=15660, lr=0.135000, batch loss=0.069804, epoch loss=0.069804 Batch=119, step=15720, lr=0.134750, batch loss=0.087158, epoch loss=0.156962 Batch=179, step=15780, lr=0.134500, batch loss=0.079254, epoch loss=0.236216 Batch=239, step=15840, lr=0.134250, batch loss=0.090016, epoch loss=0.326232 Batch=299, step=15900, lr=0.134000, batch loss=0.042144, epoch loss=0.368376 Batch=359, step=15960, lr=0.133750, batch loss=0.080553, epoch loss=0.448930 Batch=419, step=16020, lr=0.133500, batch loss=0.112973, epoch loss=0.561903 Batch=479, step=16080, lr=0.133250, batch loss=0.047282, epoch loss=0.609185 Batch=539, step=16140, lr=0.133000, batch loss=0.044959, epoch loss=0.654145 Batch=599, step=16200, lr=0.132750, batch loss=0.052082, epoch loss=0.706226 Batch=659, step=16260, lr=0.132500, batch loss=0.074907, epoch loss=0.781133 Batch=719, step=16320, lr=0.132250, batch loss=0.074010, epoch loss=0.855143 Batch=779, step=16380, lr=0.132000, batch loss=0.087998, epoch loss=0.943142 Batch=839, step=16440, lr=0.131750, batch loss=0.149718, epoch loss=1.092860 Batch=899, step=16500, lr=0.131500, batch loss=0.085499, epoch loss=1.178359 Batch=959, step=16560, lr=0.131250, batch loss=0.062488, epoch loss=1.240847 Batch=1019, step=16620, lr=0.131000, batch loss=0.068323, epoch loss=1.309170 Batch=1079, step=16680, lr=0.130750, batch loss=0.050406, epoch loss=1.359575 Batch=1139, step=16740, lr=0.130500, batch loss=0.089603, epoch loss=1.449178 Batch=1199, step=16800, lr=0.130250, batch loss=0.039345, epoch loss=1.488523 Epoch=13, step=16800, lr=0.130250, epoch loss=1.488523 Batch=59, step=16860, lr=0.130000, batch loss=0.031523, epoch loss=0.031523 Batch=119, step=16920, lr=0.129750, batch loss=0.034344, epoch loss=0.065867 Batch=179, step=16980, lr=0.129500, batch loss=0.040621, epoch loss=0.106487 Batch=239, step=17040, lr=0.129250, batch loss=0.057066, epoch loss=0.163553 Batch=299, step=17100, lr=0.129000, batch loss=0.029574, epoch loss=0.193127 Batch=359, step=17160, lr=0.128750, batch loss=0.046326, epoch loss=0.239453 Batch=419, step=17220, lr=0.128500, batch loss=0.078789, epoch loss=0.318242 Batch=479, step=17280, lr=0.128250, batch loss=0.021215, epoch loss=0.339457 Batch=539, step=17340, lr=0.128000, batch loss=0.026120, epoch loss=0.365577 Batch=599, step=17400, lr=0.127750, batch loss=0.034526, epoch loss=0.400103 Batch=659, step=17460, lr=0.127500, batch loss=0.045417, epoch loss=0.445520 Batch=719, step=17520, lr=0.127250, batch loss=0.043286, epoch loss=0.488805 Batch=779, step=17580, lr=0.127000, batch loss=0.078919, epoch loss=0.567724 Batch=839, step=17640, lr=0.126750, batch loss=0.175140, epoch loss=0.742864 Batch=899, step=17700, lr=0.126500, batch loss=0.059166, epoch loss=0.802030 Batch=959, step=17760, lr=0.126250, batch loss=0.020466, epoch loss=0.822496 Batch=1019, step=17820, lr=0.126000, batch loss=0.030844, epoch loss=0.853340 Batch=1079, step=17880, lr=0.125750, batch loss=0.012263, epoch loss=0.865603 Batch=1139, step=17940, lr=0.125500, batch loss=0.035815, epoch loss=0.901419 Batch=1199, step=18000, lr=0.125250, batch loss=0.015428, epoch loss=0.916847 Epoch=14, step=18000, lr=0.125250, epoch loss=0.916847 Batch=59, step=18060, lr=0.125000, batch loss=0.013196, epoch loss=0.013196 Batch=119, step=18120, lr=0.124750, batch loss=0.034364, epoch loss=0.047561 Batch=179, step=18180, lr=0.124500, batch loss=0.090773, epoch loss=0.138333 Batch=239, step=18240, lr=0.124250, batch loss=0.043862, epoch loss=0.182196 Batch=299, step=18300, lr=0.124000, batch loss=0.011338, epoch loss=0.193534 Batch=359, step=18360, lr=0.123750, batch loss=0.024800, epoch loss=0.218335 Batch=419, step=18420, lr=0.123500, batch loss=0.026162, epoch loss=0.244496 Batch=479, step=18480, lr=0.123250, batch loss=0.010511, epoch loss=0.255007 Batch=539, step=18540, lr=0.123000, batch loss=0.029193, epoch loss=0.284200 Batch=599, step=18600, lr=0.122750, batch loss=0.040581, epoch loss=0.324781 Batch=659, step=18660, lr=0.122500, batch loss=0.025921, epoch loss=0.350702 Batch=719, step=18720, lr=0.122250, batch loss=0.066913, epoch loss=0.417615 Batch=779, step=18780, lr=0.122000, batch loss=0.093350, epoch loss=0.510965 Batch=839, step=18840, lr=0.121750, batch loss=0.053714, epoch loss=0.564679 Batch=899, step=18900, lr=0.121500, batch loss=0.053090, epoch loss=0.617769 Batch=959, step=18960, lr=0.121250, batch loss=0.013491, epoch loss=0.631260 Batch=1019, step=19020, lr=0.121000, batch loss=0.025802, epoch loss=0.657062 Batch=1079, step=19080, lr=0.120750, batch loss=0.010615, epoch loss=0.667677 Batch=1139, step=19140, lr=0.120500, batch loss=0.022964, epoch loss=0.690641 Batch=1199, step=19200, lr=0.120250, batch loss=0.009276, epoch loss=0.699917 Epoch=15, step=19200, lr=0.120250, epoch loss=0.699917 Batch=59, step=19260, lr=0.120000, batch loss=0.004701, epoch loss=0.004701 Batch=119, step=19320, lr=0.119750, batch loss=0.011317, epoch loss=0.016019 Batch=179, step=19380, lr=0.119500, batch loss=0.020342, epoch loss=0.036360 Batch=239, step=19440, lr=0.119250, batch loss=0.022663, epoch loss=0.059023 Batch=299, step=19500, lr=0.119000, batch loss=0.018292, epoch loss=0.077315 Batch=359, step=19560, lr=0.118750, batch loss=0.032406, epoch loss=0.109721 Batch=419, step=19620, lr=0.118500, batch loss=0.019803, epoch loss=0.129525 Batch=479, step=19680, lr=0.118250, batch loss=0.008109, epoch loss=0.137633 Batch=539, step=19740, lr=0.118000, batch loss=0.017338, epoch loss=0.154972 Batch=599, step=19800, lr=0.117750, batch loss=0.024076, epoch loss=0.179048 Batch=659, step=19860, lr=0.117500, batch loss=0.019396, epoch loss=0.198443 Batch=719, step=19920, lr=0.117250, batch loss=0.043825, epoch loss=0.242268 Batch=779, step=19980, lr=0.117000, batch loss=0.081109, epoch loss=0.323378 Batch=839, step=20040, lr=0.116750, batch loss=0.030978, epoch loss=0.354356 Batch=899, step=20100, lr=0.116500, batch loss=0.032240, epoch loss=0.386596 Batch=959, step=20160, lr=0.116250, batch loss=0.011562, epoch loss=0.398158 Batch=1019, step=20220, lr=0.116000, batch loss=0.014790, epoch loss=0.412948 Batch=1079, step=20280, lr=0.115750, batch loss=0.002063, epoch loss=0.415011 Batch=1139, step=20340, lr=0.115500, batch loss=0.014919, epoch loss=0.429930 Batch=1199, step=20400, lr=0.115250, batch loss=0.006977, epoch loss=0.436908 Epoch=16, step=20400, lr=0.115250, epoch loss=0.436908 Batch=59, step=20460, lr=0.115000, batch loss=0.003335, epoch loss=0.003335 Batch=119, step=20520, lr=0.114750, batch loss=0.008879, epoch loss=0.012214 Batch=179, step=20580, lr=0.114500, batch loss=0.017292, epoch loss=0.029507 Batch=239, step=20640, lr=0.114250, batch loss=0.022579, epoch loss=0.052086 Batch=299, step=20700, lr=0.114000, batch loss=0.010154, epoch loss=0.062240 Batch=359, step=20760, lr=0.113750, batch loss=0.013797, epoch loss=0.076037 Batch=419, step=20820, lr=0.113500, batch loss=0.014207, epoch loss=0.090243 Batch=479, step=20880, lr=0.113250, batch loss=0.005118, epoch loss=0.095361 Batch=539, step=20940, lr=0.113000, batch loss=0.015733, epoch loss=0.111094 Batch=599, step=21000, lr=0.112750, batch loss=0.017772, epoch loss=0.128866 Batch=659, step=21060, lr=0.112500, batch loss=0.014466, epoch loss=0.143332 Batch=719, step=21120, lr=0.112250, batch loss=0.044693, epoch loss=0.188025 Batch=779, step=21180, lr=0.112000, batch loss=0.070993, epoch loss=0.259018 Batch=839, step=21240, lr=0.111750, batch loss=0.025914, epoch loss=0.284932 Batch=899, step=21300, lr=0.111500, batch loss=0.028553, epoch loss=0.313485 Batch=959, step=21360, lr=0.111250, batch loss=0.009872, epoch loss=0.323358 Batch=1019, step=21420, lr=0.111000, batch loss=0.011036, epoch loss=0.334393 Batch=1079, step=21480, lr=0.110750, batch loss=0.000972, epoch loss=0.335365 Batch=1139, step=21540, lr=0.110500, batch loss=0.013037, epoch loss=0.348402 Batch=1199, step=21600, lr=0.110250, batch loss=0.005142, epoch loss=0.353544 Epoch=17, step=21600, lr=0.110250, epoch loss=0.353544 Batch=59, step=21660, lr=0.110000, batch loss=0.002373, epoch loss=0.002373 Batch=119, step=21720, lr=0.109750, batch loss=0.006531, epoch loss=0.008905 Batch=179, step=21780, lr=0.109500, batch loss=0.012882, epoch loss=0.021786 Batch=239, step=21840, lr=0.109250, batch loss=0.009840, epoch loss=0.031626 Batch=299, step=21900, lr=0.109000, batch loss=0.013856, epoch loss=0.045482 Batch=359, step=21960, lr=0.108750, batch loss=0.012619, epoch loss=0.058101 Batch=419, step=22020, lr=0.108500, batch loss=0.012429, epoch loss=0.070530 Batch=479, step=22080, lr=0.108250, batch loss=0.003757, epoch loss=0.074287 Batch=539, step=22140, lr=0.108000, batch loss=0.014968, epoch loss=0.089255 Batch=599, step=22200, lr=0.107750, batch loss=0.015674, epoch loss=0.104928 Batch=659, step=22260, lr=0.107500, batch loss=0.015118, epoch loss=0.120046 Batch=719, step=22320, lr=0.107250, batch loss=0.028317, epoch loss=0.148363 Batch=779, step=22380, lr=0.107000, batch loss=0.039181, epoch loss=0.187544 Batch=839, step=22440, lr=0.106750, batch loss=0.021568, epoch loss=0.209113 Batch=899, step=22500, lr=0.106500, batch loss=0.024459, epoch loss=0.233572 Batch=959, step=22560, lr=0.106250, batch loss=0.009959, epoch loss=0.243531 Batch=1019, step=22620, lr=0.106000, batch loss=0.009816, epoch loss=0.253348 Batch=1079, step=22680, lr=0.105750, batch loss=0.000858, epoch loss=0.254206 Batch=1139, step=22740, lr=0.105500, batch loss=0.010060, epoch loss=0.264266 Batch=1199, step=22800, lr=0.105250, batch loss=0.004706, epoch loss=0.268972 Epoch=18, step=22800, lr=0.105250, epoch loss=0.268972 Batch=59, step=22860, lr=0.105000, batch loss=0.001895, epoch loss=0.001895 Batch=119, step=22920, lr=0.104750, batch loss=0.005382, epoch loss=0.007277 Batch=179, step=22980, lr=0.104500, batch loss=0.011039, epoch loss=0.018316 Batch=239, step=23040, lr=0.104250, batch loss=0.008472, epoch loss=0.026788 Batch=299, step=23100, lr=0.104000, batch loss=0.006777, epoch loss=0.033565 Batch=359, step=23160, lr=0.103750, batch loss=0.012795, epoch loss=0.046360 Batch=419, step=23220, lr=0.103500, batch loss=0.011221, epoch loss=0.057580 Batch=479, step=23280, lr=0.103250, batch loss=0.003192, epoch loss=0.060773 Batch=539, step=23340, lr=0.103000, batch loss=0.016520, epoch loss=0.077292 Batch=599, step=23400, lr=0.102750, batch loss=0.013484, epoch loss=0.090776 Batch=659, step=23460, lr=0.102500, batch loss=0.011814, epoch loss=0.102590 Batch=719, step=23520, lr=0.102250, batch loss=0.010517, epoch loss=0.113107 Batch=779, step=23580, lr=0.102000, batch loss=0.018017, epoch loss=0.131124 Batch=839, step=23640, lr=0.101750, batch loss=0.029114, epoch loss=0.160238 Batch=899, step=23700, lr=0.101500, batch loss=0.019253, epoch loss=0.179491 Batch=959, step=23760, lr=0.101250, batch loss=0.009268, epoch loss=0.188759 Batch=1019, step=23820, lr=0.101000, batch loss=0.007564, epoch loss=0.196323 Batch=1079, step=23880, lr=0.100750, batch loss=0.001364, epoch loss=0.197686 Batch=1139, step=23940, lr=0.100500, batch loss=0.008324, epoch loss=0.206010 Batch=1199, step=24000, lr=0.100250, batch loss=0.004503, epoch loss=0.210513 Epoch=19, step=24000, lr=0.100250, epoch loss=0.210513 Half-moons scatterplot and decision boundary: ┌────────────────────────────────────────────────────────────────────────────────────────────────────┐ │********************************#*******************************************************************│ │**********************#*#*#######*###*#####*********************************************************│ │**********************#########################*****************************************************│ │*****************#**########*######*###########*###*************************************************│ │***************#################*###################************************************************│ │************######*#################*#################**********************************************│ │**********#*#####*########*#**************##*#########*#********************************************│ │***********########*##*#******************#*****##########******************************************│ │***********###########*************************############***************************************..│ │********######*####*********************************###*###*#***********************************....│ │*******######**##*************....*****************#*######*#********************************.......│ │*******##*##**##**********...........***************########*##***************************..........│ │*****#######***********........%...%%...***************#########*************************.........%.│ │******######**********..........%.........**************##*#####************************......%.%.%.│ │***#########**********.........%%%.%%......*************#*#######*********************.......%.%%%%.│ │****#######**********..........%%%%.........************#########********************........%%.%%.%│ │**#######************..........%%%%%%%........*************###*###******************.........%%%%%%.│ │*##*####************...........%%%%%%%.........***********########*****************..........%%%%%%.│ │*#######***********............%%%%%%%..........************#######**************............%%%%%%.│ │*##*####***********............%%.%%%%%...........***********####***************............%%%%%%%.│ │*#####*#**********..............%%%%%%%............**********##*###************..............%%%%%..│ │#######***********.............%.%%%%%%.............*********#######*********..............%%%%.%%..│ │#####*#**********...............%%%%%%%...............*******#######********...............%%%%%%%%.│ │###*#*#**********...............%%%%%%%%%..............*******######*******................%%%%%%...│ │#######*********.................%%%%%%%%................****###*###******................%%%%%%....│ │######**********.................%%%%%%%%%................***#*###******................%%%%%%%%%...│ │*#*##*#********...................%%%%%%%%%%...............***######***..................%%%%%%.....│ │#****##********....................%%%%%%%%%.................**###*#**................%.%%%%%%%.....│ │**************.....................%.%%%%%%...................*******..................%.%%.%%......│ │**************.......................%..%%%%%%%................****...............%.%%%%%%%%%.......│ │*************.........................%.%%%.%%%%.................*................%%%%%%%.%.%.......│ │************............................%..%%%%..%................................%%%%%%%%..........│ │************.............................%%%%%%%%%%%........................%%..%%%%%%%%.%..........│ │***********..............................%%.%%%%%%%%..%....................%..%%%.%%%%%%%...........│ │***********.................................%%%%.%%%%%%%%...............%.%%%%%%%%%%%%.%............│ │**********...................................%%%%%%%%%%%%%%%%%%%%%%.%%%%.%%%%%%%%%%%%%..............│ │**********....................................%%.%%%%%%%%%%%%%%%%%%%%%%.%%%%%%%%%%%.................│ │*********.........................................%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%...................│ │*********............................................%%%.%%%%%%%%%%%%%%%%%%%%%......................│ │********................................................%...%%%%.%%.%%%%..%.........................│ └────────────────────────────────────────────────────────────────────────────────────────────────────┘ "/usr/bin/env" "bash" "-c" "opam exec -- dune build @install @check @runtest && rm -rf _build" failed with exit status 1 2025-05-22 12:20.32: Job failed: Failed: Build failed