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Organisationsahrefsocannl397418 ()opensuse-15.6-5.3_opam-2.3

opensuse-15.6-5.3_opam-2.3

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2025-05-22 20:00.59: New job: test ahrefs/ocannl https://github.com/ahrefs/ocannl.git#refs/heads/master (39741884b740497ac10065d5e464e6c70f9151f4) (linux-x86_64:opensuse-15.6-5.3_opam-2.3)
Base: ocaml/opam:opensuse-15.6-ocaml-5.3@sha256:36e05b425c0b04d4045c63087d07e299e176b878207d788e9abdc92f67fa4600
Opam project build


To reproduce locally:


git clone --recursive "https://github.com/ahrefs/ocannl.git" -b "master" && cd "ocannl" && git reset --hard 39741884
cat > Dockerfile <<'END-OF-DOCKERFILE'
FROM ocaml/opam:opensuse-15.6-ocaml-5.3@sha256:36e05b425c0b04d4045c63087d07e299e176b878207d788e9abdc92f67fa4600
# opensuse-15.6-5.3_opam-2.3
USER 1000:1000
ENV CLICOLOR_FORCE="1"
ENV OPAMCOLOR="always"
WORKDIR /src
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 2df846cb67d6f96ae4fced111519ff4ae27d19ae || git fetch origin master) && git reset -q --hard 2df846cb67d6f96ae4fced111519ff4ae27d19ae && 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.3.19.0 dune-configurator.3.19.0 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 20:00.59: Using cache hint "ahrefs/ocannl-ocaml/opam:opensuse-15.6-ocaml-5.3@sha256:36e05b425c0b04d4045c63087d07e299e176b878207d788e9abdc92f67fa4600-opensuse-15.6-5.3_opam-2.3-63d0fa7caba437c680f3f62d33f451da"
2025-05-22 20:00.59: Using OBuilder spec:
((from ocaml/opam:opensuse-15.6-ocaml-5.3@sha256:36e05b425c0b04d4045c63087d07e299e176b878207d788e9abdc92f67fa4600)
(comment opensuse-15.6-5.3_opam-2.3)
(user (uid 1000) (gid 1000))
(env CLICOLOR_FORCE 1)
(env OPAMCOLOR always)
(workdir /src)
(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 2df846cb67d6f96ae4fced111519ff4ae27d19ae || git fetch origin master) && git reset -q --hard 2df846cb67d6f96ae4fced111519ff4ae27d19ae && 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.3.19.0 dune-configurator.3.19.0 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 20:00.59: Waiting for resource in pool OCluster
2025-05-22 20:00.59: Waiting for worker…
2025-05-22 20:01.08: Got resource from pool OCluster
Building on bremusa.ocamllabs.io
All commits already cached
HEAD is now at 39741884 Untested: convert remaining uses of Format except where printing Sexp values


(from ocaml/opam:opensuse-15.6-ocaml-5.3@sha256:36e05b425c0b04d4045c63087d07e299e176b878207d788e9abdc92f67fa4600)
2025-05-22 20:01.16 ---> using "e2985c4688e78c185fe5effed79d132da1434e7bdd40f94bb99436d3b96690ce" from cache


/: (comment opensuse-15.6-5.3_opam-2.3)


/: (user (uid 1000) (gid 1000))


/: (env CLICOLOR_FORCE 1)


/: (env OPAMCOLOR always)


/: (workdir /src)


/src: (run (shell "sudo ln -f /usr/bin/opam-2.3 /usr/bin/opam"))
2025-05-22 20:01.16 ---> using "50434b1af48c812e5b8b97b6a092abb9dd6da5001ea1c138b231ba3655932e87" 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
Format upgrade done.


<><> Updating repositories ><><><><><><><><><><><><><><><><><><><><><><><><><><>
[default] Initialised
2025-05-22 20:01.16 ---> using "7cefc43bb115418c0e97b1444415cc019594bb8990b6e1f2ed0a436414564ab1" from cache


/src: (run (shell "uname -rs && opam exec -- ocaml -version && opam --version"))
Linux 6.8.0-59-generic
The OCaml toplevel, version 5.3.0
2.3.0
2025-05-22 20:01.16 ---> using "bbea99c20ed515ef2fe261fc823d093d079ef495d3a45cfaf2f85630d6f346ad" from cache


/src: (workdir /src)


/src: (run (shell "sudo chown opam /src"))
2025-05-22 20:01.16 ---> using "42f82abd2853d50c6163e98a7ac94c7848ae533331533f1aa6d2fbe1dddc149c" from cache


/src: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
(network host)
(shell "cd ~/opam-repository && (git cat-file -e 2df846cb67d6f96ae4fced111519ff4ae27d19ae || git fetch origin master) && git reset -q --hard 2df846cb67d6f96ae4fced111519ff4ae27d19ae && git log --no-decorate -n1 --oneline && opam update -u"))
From https://github.com/ocaml/opam-repository
* branch                  master     -> FETCH_HEAD
35eb2f107a..2df846cb67  master     -> origin/master
2df846cb67 Merge pull request #27910 from maiste/release-dune-3.19.0


<><> 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 20:01.16 ---> using "830de3684b2303473878f5698d61ec87cb7fe814b217f5708a2c7f6d4451ffe1" from cache


/src: (copy (src neural_nets_lib.opam arrayjit.opam) (dst ./))
2025-05-22 20:01.17 ---> saved as "459278b62ebc9bf3bae8a23c439e02ba9180143363e8b791b96cd47a22246de2"


/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 20:01.51 ---> saved as "be6ac93863a1b5b642aa9b6e9b96a10dca23c117cb04d816475d42b89fddd193"


/src: (run (network host)
(shell "echo '(lang dune 3.0)' > './dune-project'"))
2025-05-22 20:01.52 ---> saved as "85b9d1160afd8d29949124b6ec2da9b16bb9badbdc27dac47545b80a70e6e87b"


/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.3.19.0 dune-configurator.3.19.0 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 "zypper" "--non-interactive" "refresh"
- Retrieving repository 'Update repository of openSUSE Backports' metadata [...
- .........done]
- Building repository 'Update repository of openSUSE Backports' cache [..
- ..done]
- Retrieving repository 'Update repository with updates from SUSE Linux Enterprise 15' metadata [..
- ........
- ..........
- ..........
- ..........
- .........
- ..........
- .....
- .done]
- Building repository 'Update repository with updates from SUSE Linux Enterprise 15' cache [..
- ..done]
- Repository 'Main Update Repository' is up to date.
- Repository 'Update Repository (Non-Oss)' is up to date.
- Repository 'Non-OSS Repository' is up to date.
- Repository 'Main Repository' is up to date.
- All repositories have been refreshed.


<><> Synchronising pinned packages ><><><><><><><><><><><><><><><><><><><><><><>
[neural_nets_lib.dev] synchronised (file:///src)
[arrayjit.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 "zypper" "--non-interactive" "install" "libffi-devel"
- Loading repository data...
- Reading installed packages...
- Resolving package dependencies...
- 
- The following NEW package is going to be installed:
-   libffi-devel
- 
- 1 new package to install.
- 
- Package download size:    26.7 KiB
- 
- Package install size change:
-               |      29.1 KiB  required by packages that will be installed
-     29.1 KiB  |  -      0 B    released by packages that will be removed
- 
- Backend:  classic_rpmtrans
- Continue? [y/n/v/...? shows all options] (y): y
- Retrieving: libffi-devel-3.2.1.git259-10.8.x86_64 (Main Repository) (1/1),  26.7 KiB
- Retrieving: libffi-devel-3.2.1.git259-10.8.x86_64.rpm [.
- .done (26.7 KiB/s)]
- 
- Checking for file conflicts: [..done]
- (1/1) Installing: libffi-devel-3.2.1.git259-10.8.x86_64 [..done]
2025-05-22 20:03.04 ---> saved as "1f67e902ca7d0a707837105946108c10581cc82ec7da85f806339e507e156f8e"


/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                    3.19.0
- install dune-configurator       3.19.0
- 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 cmdliner.1.3.0  (cached)
-> retrieved cppo.1.8.0  (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 fmt.0.10.0  (cached)
-> retrieved integers.0.7.0  (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 multicore-magic.2.3.1  (cached)
-> retrieved mdx.2.5.0  (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 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_enumerate.v0.17.0  (cached)
-> retrieved ppx_deriving.6.0.3  (cached)
-> retrieved ppx_expect.v0.17.2  (cached)
-> retrieved ppx_fields_conv.v0.17.0  (cached)
-> retrieved ppx_globalize.v0.17.0  (cached)
-> retrieved ppx_here.v0.17.0  (cached)
-> retrieved ppx_hash.v0.17.0  (cached)
-> retrieved ppx_inline_test.v0.17.0  (cached)
-> retrieved ppx_optcomp.v0.17.0  (cached)
-> retrieved dune.3.19.0, dune-configurator.3.19.0  (cached)
-> retrieved ppx_minidebug.2.2.0  (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 ppxlib_jane.v0.17.2  (cached)
-> installed cmdliner.1.3.0
-> installed num.1.5-1
-> retrieved ptime.1.2.0  (cached)
-> retrieved re.1.12.0  (cached)
-> retrieved ppxlib.0.35.0  (cached)
-> retrieved result.1.5  (cached)
-> retrieved seq.base  (cached)
-> installed seq.base
-> retrieved sexplib.v0.17.0  (cached)
-> retrieved saturn_lockfree.0.5.0  (cached)
-> retrieved printbox.0.12, printbox-ext-plot.0.12, printbox-html.0.12, printbox-md.0.12, printbox-text.0.12  (cached)
-> retrieved 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 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 ocamlbuild.0.16.1
-> installed ocamlfind.1.9.8
-> 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.3.19.0
-> installed jane-street-headers.v0.17.0
-> installed ppx_derivers.1.2.1
-> installed backoff.0.1.1
-> installed result.1.5
-> installed printbox.0.12
-> installed csexp.1.5.2
-> installed bigarray-compat.1.1.0
-> installed camlp-streams.5.0.1
-> installed multicore-magic.2.3.1
-> installed ocaml-compiler-libs.v0.17.0
-> installed ocaml-syntax-shims.1.0.0
-> installed cppo.1.8.0
-> installed ocaml-version.4.0.0
-> installed ocaml_intrinsics_kernel.v0.17.1
-> installed pprint.20230830
-> installed re.1.12.0
-> 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 dune-configurator.3.19.0
-> installed parsexp.v0.17.0
-> 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 uucp.16.0.0
-> installed ctypes.0.23.0
-> installed printbox-text.0.12
-> installed printbox-md.0.12
-> installed printbox-ext-plot.0.12
-> installed base.v0.17.2
-> installed fieldslib.v0.17.0
-> installed ctypes-foreign.0.23.0
-> installed variantslib.v0.17.0
-> installed stdio.v0.17.0
-> installed ppxlib.0.35.0
-> installed ppxlib_jane.v0.17.2
-> installed ppx_optcomp.v0.17.0
-> installed ppx_here.v0.17.0
-> installed ppx_cold.v0.17.0
-> installed ppx_variants_conv.v0.17.0
-> installed ppx_fields_conv.v0.17.0
-> installed ppx_compare.v0.17.0
-> installed ppx_deriving.6.0.3
-> installed ppx_enumerate.v0.17.0
-> installed ppx_globalize.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 20:05.47 ---> saved as "547ea84987e73b6c78cdad10e200daf6adc18bc2fdf6481b7ab9baff252fb2bf"


/src: (copy (src .) (dst /src))
2025-05-22 20:05.48 ---> saved as "43b44bcd1f19abfaed5e2a18dc604a585993e3c33ab8c2e885c5b0e3706a8d9a"


/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
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
Fatal error: exception Sys_error("log_files/micrograd_demo_logging.raw: No such file or directory")
Raised by primitive operation at Stdlib.open_out_gen in file "stdlib.ml", line 331, characters 29-55
Called from Stdlib.open_out_bin in file "stdlib.ml" (inlined), line 339, characters 2-76
Called from Minidebug_runtime.PrevRun.init_run in file "minidebug_runtime.ml", line 677, characters 18-51
Called from Minidebug_runtime.debug_file in file "minidebug_runtime.ml", lines 2106-2108, characters 4-56
Called from Thread_local_storage.get_default in file "src/thread_local_storage.ml" (inlined), line 118, characters 12-22
Called from Minidebug_runtime.local_runtime.get_local in file "minidebug_runtime.ml", line 2250, characters 21-76
Called from Minidebug_runtime.local_runtime.(fun) in file "minidebug_runtime.ml", line 2252, characters 41-53
Called from Utils.set_log_level.Debug_runtime in file "arrayjit/lib/utils.ml", lines 415-418, characters 29-42
Called from Utils.restore_settings in file "arrayjit/lib/utils.ml", line 421, characters 2-34
Called from Utils in file "arrayjit/lib/utils.ml", line 438, characters 9-28
(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/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/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/default/test && .tutorials.inline-tests/inline-test-runner.exe inline-test-runner tutorials -partition 'Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/983d1ee5d6c7cf82cb61c966c497d671/default/test/ocannl_config.' -source-tree-root .. -diff-cmd -)


Welcome to OCANNL! Reading configuration defaults from /src/_build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/ocannl_config.
Retrieving commandline, environment, or config file variable ocannl_log_level
Found 0, in the config file
(cd _build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/micrograd_demo.ml.corrected
diff --git a/_build/default/test/micrograd_demo.ml b/_build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/default/test/micrograd_demo.ml.corrected
index 77e46c6..ab81526 100644
--- a/_build/default/test/micrograd_demo.ml
+++ b/_build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/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/ea9c4717a1d77418173e02e9f481ce78/default/test/hello_world_op.ml.corrected
diff --git a/_build/default/test/hello_world_op.ml b/_build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/default/test/hello_world_op.ml.corrected
index ba9d7ef..6bfa309 100644
--- a/_build/default/test/hello_world_op.ml
+++ b/_build/.sandbox/ea9c4717a1d77418173e02e9f481ce78/default/test/hello_world_op.ml.corrected
@@ -102,36 +102,46 @@ 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 {|
+    [0]: [  1.00 , 2.00 , 3.00  ;  4.00 , 5.00 , 6.00  ]_hey shape 1:3->0:2  [
+       1.00 , 2.00 , 3.00
+      ;  4.00 , 5.00 , 6.00
+    ]
+    |}];
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]: [  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 │                                             │
+    │└──────┴──────────────────┘                                             │
+    └────────────────────────────────────────────────────────────────────────┘
|}];
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]: [| [ 1.00 ; 2.00 ; 3.00 ] ; [ 4.00 ; 5.00 ; 6.00 ] |]_hoo shape 0:2|1:3  [|
+      [ 1.00 ; 2.00 ; 3.00 ]
+      ; [ 4.00 ; 5.00 ; 6.00 ]
+    |]
+    |}];
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]: [| [ 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 │                                                  │
+    │└──────┴──────────────────┘                                                  │
+    └─────────────────────────────────────────────────────────────────────────────┘
|}];
let%op hey2 =
[
@@ -145,10 +155,12 @@ 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)]
+    [2]: c4x2x3_hey2 shape 1:2,2:3->0:4  [
+       ( 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 )
+    ]
|}];
Tensor.print ~with_code:false ~with_grad:false `Default @@ hey2;
[%expect
@@ -178,10 +190,12 @@ 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]]|]
+    [3]: c4x2x3_hoo2 shape 0:4|1:2,2:3  [|
+      [ [ 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 ] ]
+    |]
|}];
Tensor.print ~with_code:false ~with_grad:false `Default @@ hoo2;
[%expect
@@ -209,10 +223,12 @@ 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]|]|]
+    [4]: c4x2x3_heyhoo shape 0:4,1:2|2:3  [|
+      [| [ 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 ] |]
+    |]
|}];
Tensor.print ~with_code:false ~with_grad:false `Default @@ heyhoo;
[%expect
@@ -240,15 +256,24 @@ let%expect_test "Print constant tensor" =
Tensor.print ~with_code:false ~with_grad:false `Inline @@ heyhoo2;
[%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]]|]|]
+    [5]: c4x2x3x2_heyhoo2 shape 0:4,1:2|2:3,3:2  [|
+      [|
+        [ [ 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 ] ]
+      |]
+    |]
|}];
Tensor.print ~with_code:false ~with_grad:false `Default @@ heyhoo2;
[%expect
@@ -293,17 +318,28 @@ let%expect_test "Print constant tensor" =
Tensor.print ~with_code:false ~with_grad:false `Inline @@ heyhoo3;
[%expect
{|
-    [|
+    [6]: c2x2x2x3x2_heyhoo3 shape 0:2,1:2|2:2,3:3,4:2  [|
[|
-        [[[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 ] ]
+        ]
+      |]
+    |]
|}];
Tensor.print ~with_code:false ~with_grad:false `Default @@ heyhoo3;
[%expect
@@ -353,17 +389,28 @@ let%expect_test "Print constant tensor" =
Tensor.print ~with_code:false ~with_grad:false `Inline @@ heyhoo4;
[%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]]];
+    [7]: c2x2x2x3x2_heyhoo4 shape 0:2|4:2->1:2,2:2,3:3  [|
[
-        [[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  ]
+        ]
+      ]
+    |]
|}];
Tensor.print ~with_code:false ~with_grad:false `Default @@ heyhoo4;
[%expect
@@ -462,8 +509,29 @@ 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]
+    [2]: 0...20 shape 0:21  [
+      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
+    ]
|}];
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=0.199500, batch loss=8.539634, epoch loss=32.149087
Batch=179, step=180, lr=0.199500, batch loss=2.621123, epoch loss=34.770210
Batch=239, step=240, lr=0.199000, batch loss=0.845226, epoch loss=35.615435
Batch=299, step=300, lr=0.198750, batch loss=1.456835, epoch loss=37.072270
Batch=359, step=360, lr=0.198750, batch loss=1.325217, epoch loss=38.397487
Batch=419, step=420, lr=0.198250, batch loss=0.622963, epoch loss=39.020450
Batch=479, step=480, lr=0.198000, batch loss=0.815356, epoch loss=39.835806
Batch=539, step=540, lr=0.197750, batch loss=0.701159, epoch loss=40.536965
Batch=599, step=600, lr=0.197750, batch loss=1.069898, epoch loss=41.606864
Batch=659, step=660, lr=0.197250, batch loss=0.483505, epoch loss=42.090369
Batch=719, step=720, lr=0.197000, batch loss=0.411658, epoch loss=42.502026
Batch=779, step=780, lr=0.197000, batch loss=0.469721, epoch loss=42.971747
Batch=839, step=840, lr=0.196500, batch loss=0.444091, epoch loss=43.415839
Batch=899, step=900, lr=0.196250, batch loss=0.384409, epoch loss=43.800248
Batch=959, step=960, lr=0.196000, batch loss=0.238270, epoch loss=44.038517
Batch=1019, step=1020, lr=0.195750, batch loss=0.440749, epoch loss=44.479266
Batch=1079, step=1080, lr=0.195750, batch loss=0.225675, epoch loss=44.704941
Batch=1139, step=1140, lr=0.195250, batch loss=0.315955, epoch loss=45.020895
Batch=1199, step=1200, lr=0.195000, batch loss=0.263589, epoch loss=45.284485
Epoch=0, step=1200, lr=0.195000, epoch loss=45.284485
Batch=59, step=1260, lr=0.194750, batch loss=0.262446, epoch loss=0.262446
Batch=119, step=1320, lr=0.194500, batch loss=0.205742, epoch loss=0.468188
Batch=179, step=1380, lr=0.194250, batch loss=0.242615, epoch loss=0.710803
Batch=239, step=1440, lr=0.194000, batch loss=0.347070, epoch loss=1.057874
Batch=299, step=1500, lr=0.193750, batch loss=0.253560, epoch loss=1.311433
Batch=359, step=1560, lr=0.193500, batch loss=0.318727, epoch loss=1.630161
Batch=419, step=1620, lr=0.193500, batch loss=0.311883, epoch loss=1.942044
Batch=479, step=1680, lr=0.193250, batch loss=0.277519, epoch loss=2.219562
Batch=539, step=1740, lr=0.193000, batch loss=0.214593, epoch loss=2.434156
Batch=599, step=1800, lr=0.192750, batch loss=0.259305, epoch loss=2.693461
Batch=659, step=1860, lr=0.192500, batch loss=0.378949, epoch loss=3.072410
Batch=719, step=1920, lr=0.192250, batch loss=0.355249, epoch loss=3.427659
Batch=779, step=1980, lr=0.191750, batch loss=0.378239, epoch loss=3.805898
Batch=839, step=2040, lr=0.191750, batch loss=0.341025, epoch loss=4.146923
Batch=899, step=2100, lr=0.191250, batch loss=0.294165, epoch loss=4.441088
Batch=959, step=2160, lr=0.191250, batch loss=0.214877, epoch loss=4.655965
Batch=1019, step=2220, lr=0.190750, batch loss=0.331133, epoch loss=4.987098
Batch=1079, step=2280, lr=0.190500, batch loss=0.194617, epoch loss=5.181715
Batch=1139, step=2340, lr=0.190250, batch loss=0.271881, epoch loss=5.453596
Batch=1199, step=2400, lr=0.190000, batch loss=0.219513, epoch loss=5.673109
Epoch=1, step=2400, lr=0.190000, epoch loss=5.673109
Batch=59, step=2460, lr=0.189750, batch loss=0.228851, epoch loss=0.228851
Batch=119, step=2520, lr=0.189750, batch loss=0.188624, epoch loss=0.417475
Batch=179, step=2580, lr=0.189250, batch loss=0.218796, epoch loss=0.636271
Batch=239, step=2640, lr=0.189000, batch loss=0.330026, epoch loss=0.966297
Batch=299, step=2700, lr=0.189000, batch loss=0.214681, epoch loss=1.180978
Batch=359, step=2760, lr=0.188500, batch loss=0.293622, epoch loss=1.474600
Batch=419, step=2820, lr=0.188250, batch loss=0.280782, epoch loss=1.755382
Batch=479, step=2880, lr=0.188250, batch loss=0.258621, epoch loss=2.014003
Batch=539, step=2940, lr=0.187750, batch loss=0.199549, epoch loss=2.213552
Batch=599, step=3000, lr=0.187750, batch loss=0.247591, epoch loss=2.461143
Batch=659, step=3060, lr=0.187250, batch loss=0.345597, epoch loss=2.806739
Batch=719, step=3120, lr=0.187000, batch loss=0.349709, epoch loss=3.156449
Batch=779, step=3180, lr=0.186750, batch loss=0.362272, epoch loss=3.518721
Batch=839, step=3240, lr=0.186750, batch loss=0.325134, epoch loss=3.843854
Batch=899, step=3300, lr=0.186500, batch loss=0.293809, epoch loss=4.137663
Batch=959, step=3360, lr=0.186250, batch loss=0.228574, epoch loss=4.366237
Batch=1019, step=3420, lr=0.186000, batch loss=0.337037, epoch loss=4.703273
Batch=1079, step=3480, lr=0.185750, batch loss=0.193618, epoch loss=4.896892
Batch=1139, step=3540, lr=0.185250, batch loss=0.251009, epoch loss=5.147901
Batch=1199, step=3600, lr=0.185250, batch loss=0.199656, epoch loss=5.347557
Epoch=2, step=3600, lr=0.185250, epoch loss=5.347557
Batch=59, step=3660, lr=0.185000, batch loss=0.229659, epoch loss=0.229659
Batch=119, step=3720, lr=0.184500, batch loss=0.194354, epoch loss=0.424013
Batch=179, step=3780, lr=0.184500, batch loss=0.212598, epoch loss=0.636610
Batch=239, step=3840, lr=0.184000, batch loss=0.318064, epoch loss=0.954675
Batch=299, step=3900, lr=0.183750, batch loss=0.207336, epoch loss=1.162010
Batch=359, step=3960, lr=0.183750, batch loss=0.286510, epoch loss=1.448520
Batch=419, step=4020, lr=0.183250, batch loss=0.279763, epoch loss=1.728283
Batch=479, step=4080, lr=0.183250, batch loss=0.254247, epoch loss=1.982530
Batch=539, step=4140, lr=0.182750, batch loss=0.202779, epoch loss=2.185309
Batch=599, step=4200, lr=0.182500, batch loss=0.248946, epoch loss=2.434255
Batch=659, step=4260, lr=0.182500, batch loss=0.335938, epoch loss=2.770193
Batch=719, step=4320, lr=0.182250, batch loss=0.346899, epoch loss=3.117092
Batch=779, step=4380, lr=0.182000, batch loss=0.345900, epoch loss=3.462992
Batch=839, step=4440, lr=0.181500, batch loss=0.319046, epoch loss=3.782038
Batch=899, step=4500, lr=0.181250, batch loss=0.290882, epoch loss=4.072920
Batch=959, step=4560, lr=0.181000, batch loss=0.243840, epoch loss=4.316759
Batch=1019, step=4620, lr=0.181000, batch loss=0.344689, epoch loss=4.661448
Batch=1079, step=4680, lr=0.180500, batch loss=0.217188, epoch loss=4.878636
Batch=1139, step=4740, lr=0.180500, batch loss=0.249274, epoch loss=5.127910
Batch=1199, step=4800, lr=0.180250, batch loss=0.191713, epoch loss=5.319623
Epoch=3, step=4800, lr=0.180250, epoch loss=5.319623
Batch=59, step=4860, lr=0.179750, batch loss=0.223805, epoch loss=0.223805
Batch=119, step=4920, lr=0.179750, batch loss=0.186869, epoch loss=0.410673
Batch=179, step=4980, lr=0.179250, batch loss=0.205905, epoch loss=0.616579
Batch=239, step=5040, lr=0.179000, batch loss=0.307348, epoch loss=0.923927
Batch=299, step=5100, lr=0.179000, batch loss=0.208734, epoch loss=1.132661
Batch=359, step=5160, lr=0.178500, batch loss=0.273836, epoch loss=1.406498
Batch=419, step=5220, lr=0.178500, batch loss=0.265591, epoch loss=1.672088
Batch=479, step=5280, lr=0.178250, batch loss=0.241043, epoch loss=1.913131
Batch=539, step=5340, lr=0.177750, batch loss=0.189677, epoch loss=2.102808
Batch=599, step=5400, lr=0.177750, batch loss=0.230932, epoch loss=2.333740
Batch=659, step=5460, lr=0.177500, batch loss=0.323493, epoch loss=2.657233
Batch=719, step=5520, lr=0.177250, batch loss=0.324621, epoch loss=2.981854
Batch=779, step=5580, lr=0.177000, batch loss=0.338604, epoch loss=3.320459
Batch=839, step=5640, lr=0.176750, batch loss=0.313372, epoch loss=3.633830
Batch=899, step=5700, lr=0.176500, batch loss=0.276481, epoch loss=3.910311
Batch=959, step=5760, lr=0.176250, batch loss=0.209984, epoch loss=4.120294
Batch=1019, step=5820, lr=0.175750, batch loss=0.337993, epoch loss=4.458288
Batch=1079, step=5880, lr=0.175500, batch loss=0.192477, epoch loss=4.650765
Batch=1139, step=5940, lr=0.175250, batch loss=0.223670, epoch loss=4.874435
Batch=1199, step=6000, lr=0.175000, batch loss=0.188406, epoch loss=5.062842
Epoch=4, step=6000, lr=0.175000, epoch loss=5.062842
Batch=59, step=6060, lr=0.174750, batch loss=0.235150, epoch loss=0.235150
Batch=119, step=6120, lr=0.174750, batch loss=0.190359, epoch loss=0.425509
Batch=179, step=6180, lr=0.174500, batch loss=0.201179, epoch loss=0.626688
Batch=239, step=6240, lr=0.174000, batch loss=0.299685, epoch loss=0.926374
Batch=299, step=6300, lr=0.174000, batch loss=0.207779, epoch loss=1.134152
Batch=359, step=6360, lr=0.173500, batch loss=0.265801, epoch loss=1.399953
Batch=419, step=6420, lr=0.173500, batch loss=0.260519, epoch loss=1.660472
Batch=479, step=6480, lr=0.173000, batch loss=0.236632, epoch loss=1.897104
Batch=539, step=6540, lr=0.173000, batch loss=0.187190, epoch loss=2.084294
Batch=599, step=6600, lr=0.172500, batch loss=0.227616, epoch loss=2.311911
Batch=659, step=6660, lr=0.172250, batch loss=0.316351, epoch loss=2.628262
Batch=719, step=6720, lr=0.172250, batch loss=0.314238, epoch loss=2.942500
Batch=779, step=6780, lr=0.171750, batch loss=0.334350, epoch loss=3.276851
Batch=839, step=6840, lr=0.171750, batch loss=0.303845, epoch loss=3.580695
Batch=899, step=6900, lr=0.171250, batch loss=0.266880, epoch loss=3.847575
Batch=959, step=6960, lr=0.171250, batch loss=0.208548, epoch loss=4.056123
Batch=1019, step=7020, lr=0.171000, batch loss=0.328781, epoch loss=4.384904
Batch=1079, step=7080, lr=0.170500, batch loss=0.181963, epoch loss=4.566867
Batch=1139, step=7140, lr=0.170250, batch loss=0.215831, epoch loss=4.782698
Batch=1199, step=7200, lr=0.170250, batch loss=0.182153, epoch loss=4.964851
Epoch=5, step=7200, lr=0.170250, epoch loss=4.964851
Batch=59, step=7260, lr=0.170000, batch loss=0.233643, epoch loss=0.233643
Batch=119, step=7320, lr=0.169750, batch loss=0.183470, epoch loss=0.417112
Batch=179, step=7380, lr=0.169500, batch loss=0.195885, epoch loss=0.612998
Batch=239, step=7440, lr=0.169250, batch loss=0.293644, epoch loss=0.906642
Batch=299, step=7500, lr=0.169000, batch loss=0.204394, epoch loss=1.111036
Batch=359, step=7560, lr=0.168500, batch loss=0.263726, epoch loss=1.374763
Batch=419, step=7620, lr=0.168500, batch loss=0.258880, epoch loss=1.633643
Batch=479, step=7680, lr=0.168250, batch loss=0.233728, epoch loss=1.867371
Batch=539, step=7740, lr=0.167750, batch loss=0.191467, epoch loss=2.058838
Batch=599, step=7800, lr=0.167750, batch loss=0.227950, epoch loss=2.286788
Batch=659, step=7860, lr=0.167250, batch loss=0.305143, epoch loss=2.591931
Batch=719, step=7920, lr=0.167000, batch loss=0.310215, epoch loss=2.902146
Batch=779, step=7980, lr=0.166750, batch loss=0.329523, epoch loss=3.231669
Batch=839, step=8040, lr=0.166500, batch loss=0.292919, epoch loss=3.524588
Batch=899, step=8100, lr=0.166250, batch loss=0.263163, epoch loss=3.787751
Batch=959, step=8160, lr=0.166250, batch loss=0.198139, epoch loss=3.985890
Batch=1019, step=8220, lr=0.166000, batch loss=0.321730, epoch loss=4.307620
Batch=1079, step=8280, lr=0.165750, batch loss=0.178388, epoch loss=4.486008
Batch=1139, step=8340, lr=0.165500, batch loss=0.208085, epoch loss=4.694093
Batch=1199, step=8400, lr=0.165000, batch loss=0.180959, epoch loss=4.875052
Epoch=6, step=8400, lr=0.165000, epoch loss=4.875052
Batch=59, step=8460, lr=0.165000, batch loss=0.223599, epoch loss=0.223599
Batch=119, step=8520, lr=0.164500, batch loss=0.177852, epoch loss=0.401451
Batch=179, step=8580, lr=0.164250, batch loss=0.187991, epoch loss=0.589442
Batch=239, step=8640, lr=0.164250, batch loss=0.276891, epoch loss=0.866333
Batch=299, step=8700, lr=0.164000, batch loss=0.191359, epoch loss=1.057692
Batch=359, step=8760, lr=0.163500, batch loss=0.248759, epoch loss=1.306451
Batch=419, step=8820, lr=0.163250, batch loss=0.244997, epoch loss=1.551448
Batch=479, step=8880, lr=0.163250, batch loss=0.228468, epoch loss=1.779916
Batch=539, step=8940, lr=0.163000, batch loss=0.177841, epoch loss=1.957757
Batch=599, step=9000, lr=0.162500, batch loss=0.217681, epoch loss=2.175439
Batch=659, step=9060, lr=0.162500, batch loss=0.294454, epoch loss=2.469893
Batch=719, step=9120, lr=0.162250, batch loss=0.297765, epoch loss=2.767658
Batch=779, step=9180, lr=0.161750, batch loss=0.315566, epoch loss=3.083224
Batch=839, step=9240, lr=0.161500, batch loss=0.281772, epoch loss=3.364995
Batch=899, step=9300, lr=0.161250, batch loss=0.251434, epoch loss=3.616429
Batch=959, step=9360, lr=0.161000, batch loss=0.188921, epoch loss=3.805350
Batch=1019, step=9420, lr=0.160750, batch loss=0.316196, epoch loss=4.121546
Batch=1079, step=9480, lr=0.160750, batch loss=0.187020, epoch loss=4.308567
Batch=1139, step=9540, lr=0.160500, batch loss=0.212742, epoch loss=4.521308
Batch=1199, step=9600, lr=0.160250, batch loss=0.167902, epoch loss=4.689210
Epoch=7, step=9600, lr=0.160250, epoch loss=4.689210
Batch=59, step=9660, lr=0.160000, batch loss=0.198675, epoch loss=0.198675
Batch=119, step=9720, lr=0.159500, batch loss=0.164669, epoch loss=0.363343
Batch=179, step=9780, lr=0.159500, batch loss=0.178930, epoch loss=0.542273
Batch=239, step=9840, lr=0.159000, batch loss=0.262206, epoch loss=0.804479
Batch=299, step=9900, lr=0.158750, batch loss=0.183875, epoch loss=0.988354
Batch=359, step=9960, lr=0.158500, batch loss=0.238910, epoch loss=1.227264
Batch=419, step=10020, lr=0.158500, batch loss=0.233640, epoch loss=1.460904
Batch=479, step=10080, lr=0.158000, batch loss=0.214009, epoch loss=1.674913
Batch=539, step=10140, lr=0.157750, batch loss=0.172445, epoch loss=1.847358
Batch=599, step=10200, lr=0.157500, batch loss=0.201880, epoch loss=2.049238
Batch=659, step=10260, lr=0.157250, batch loss=0.282663, epoch loss=2.331901
Batch=719, step=10320, lr=0.157000, batch loss=0.283526, epoch loss=2.615427
Batch=779, step=10380, lr=0.157000, batch loss=0.295655, epoch loss=2.911083
Batch=839, step=10440, lr=0.156500, batch loss=0.272359, epoch loss=3.183441
Batch=899, step=10500, lr=0.156500, batch loss=0.236592, epoch loss=3.420034
Batch=959, step=10560, lr=0.156250, batch loss=0.180113, epoch loss=3.600146
Batch=1019, step=10620, lr=0.155750, batch loss=0.296882, epoch loss=3.897029
Batch=1079, step=10680, lr=0.155750, batch loss=0.178452, epoch loss=4.075481
Batch=1139, step=10740, lr=0.155500, batch loss=0.199105, epoch loss=4.274586
Batch=1199, step=10800, lr=0.155250, batch loss=0.155237, epoch loss=4.429823
Epoch=8, step=10800, lr=0.155250, epoch loss=4.429823
Batch=59, step=10860, lr=0.154750, batch loss=0.178592, epoch loss=0.178592
Batch=119, step=10920, lr=0.154750, batch loss=0.152300, epoch loss=0.330892
Batch=179, step=10980, lr=0.154250, batch loss=0.166996, epoch loss=0.497888
Batch=239, step=11040, lr=0.154000, batch loss=0.247465, epoch loss=0.745352
Batch=299, step=11100, lr=0.153750, batch loss=0.160358, epoch loss=0.905710
Batch=359, step=11160, lr=0.153500, batch loss=0.217129, epoch loss=1.122839
Batch=419, step=11220, lr=0.153250, batch loss=0.217519, epoch loss=1.340358
Batch=479, step=11280, lr=0.153250, batch loss=0.210642, epoch loss=1.551000
Batch=539, step=11340, lr=0.153000, batch loss=0.164189, epoch loss=1.715189
Batch=599, step=11400, lr=0.152500, batch loss=0.176886, epoch loss=1.892075
Batch=659, step=11460, lr=0.152500, batch loss=0.266692, epoch loss=2.158768
Batch=719, step=11520, lr=0.152000, batch loss=0.264442, epoch loss=2.423210
Batch=779, step=11580, lr=0.152000, batch loss=0.273464, epoch loss=2.696674
Batch=839, step=11640, lr=0.151500, batch loss=0.249292, epoch loss=2.945966
Batch=899, step=11700, lr=0.151500, batch loss=0.222494, epoch loss=3.168459
Batch=959, step=11760, lr=0.151250, batch loss=0.183048, epoch loss=3.351508
Batch=1019, step=11820, lr=0.151000, batch loss=0.277368, epoch loss=3.628876
Batch=1079, step=11880, lr=0.150750, batch loss=0.145394, epoch loss=3.774269
Batch=1139, step=11940, lr=0.150250, batch loss=0.180092, epoch loss=3.954361
Batch=1199, step=12000, lr=0.150250, batch loss=0.139944, epoch loss=4.094305
Epoch=9, step=12000, lr=0.150250, epoch loss=4.094305
Batch=59, step=12060, lr=0.150000, batch loss=0.161189, epoch loss=0.161189
Batch=119, step=12120, lr=0.149750, batch loss=0.131681, epoch loss=0.292870
Batch=179, step=12180, lr=0.149250, batch loss=0.151939, epoch loss=0.444809
Batch=239, step=12240, lr=0.149000, batch loss=0.222875, epoch loss=0.667683
Batch=299, step=12300, lr=0.149000, batch loss=0.142570, epoch loss=0.810253
Batch=359, step=12360, lr=0.148500, batch loss=0.197552, epoch loss=1.007805
Batch=419, step=12420, lr=0.148500, batch loss=0.207138, epoch loss=1.214943
Batch=479, step=12480, lr=0.148000, batch loss=0.179154, epoch loss=1.394097
Batch=539, step=12540, lr=0.147750, batch loss=0.143009, epoch loss=1.537106
Batch=599, step=12600, lr=0.147750, batch loss=0.149284, epoch loss=1.686390
Batch=659, step=12660, lr=0.147500, batch loss=0.228742, epoch loss=1.915132
Batch=719, step=12720, lr=0.147250, batch loss=0.236341, epoch loss=2.151473
Batch=779, step=12780, lr=0.146750, batch loss=0.265324, epoch loss=2.416797
Batch=839, step=12840, lr=0.146500, batch loss=0.234970, epoch loss=2.651767
Batch=899, step=12900, lr=0.146250, batch loss=0.199218, epoch loss=2.850985
Batch=959, step=12960, lr=0.146250, batch loss=0.153386, epoch loss=3.004371
Batch=1019, step=13020, lr=0.146000, batch loss=0.263051, epoch loss=3.267422
Batch=1079, step=13080, lr=0.145750, batch loss=0.116328, epoch loss=3.383750
Batch=1139, step=13140, lr=0.145250, batch loss=0.151300, epoch loss=3.535050
Batch=1199, step=13200, lr=0.145250, batch loss=0.117967, epoch loss=3.653017
Epoch=10, step=13200, lr=0.145250, epoch loss=3.653017
Batch=59, step=13260, lr=0.145000, batch loss=0.138558, epoch loss=0.138558
Batch=119, step=13320, lr=0.144750, batch loss=0.118523, epoch loss=0.257081
Batch=179, step=13380, lr=0.144250, batch loss=0.127844, epoch loss=0.384925
Batch=239, step=13440, lr=0.144250, batch loss=0.184212, epoch loss=0.569138
Batch=299, step=13500, lr=0.143750, batch loss=0.121533, epoch loss=0.690670
Batch=359, step=13560, lr=0.143500, batch loss=0.162016, epoch loss=0.852687
Batch=419, step=13620, lr=0.143500, batch loss=0.161760, epoch loss=1.014447
Batch=479, step=13680, lr=0.143250, batch loss=0.147092, epoch loss=1.161539
Batch=539, step=13740, lr=0.142750, batch loss=0.118991, epoch loss=1.280530
Batch=599, step=13800, lr=0.142500, batch loss=0.121455, epoch loss=1.401985
Batch=659, step=13860, lr=0.142250, batch loss=0.177453, epoch loss=1.579439
Batch=719, step=13920, lr=0.142250, batch loss=0.172901, epoch loss=1.752340
Batch=779, step=13980, lr=0.141750, batch loss=0.181664, epoch loss=1.934004
Batch=839, step=14040, lr=0.141750, batch loss=0.200511, epoch loss=2.134515
Batch=899, step=14100, lr=0.141250, batch loss=0.216448, epoch loss=2.350964
Batch=959, step=14160, lr=0.141250, batch loss=0.107389, epoch loss=2.458352
Batch=1019, step=14220, lr=0.140750, batch loss=0.192068, epoch loss=2.650420
Batch=1079, step=14280, lr=0.140500, batch loss=0.086110, epoch loss=2.736531
Batch=1139, step=14340, lr=0.140500, batch loss=0.146749, epoch loss=2.883280
Batch=1199, step=14400, lr=0.140250, batch loss=0.089930, epoch loss=2.973210
Epoch=11, step=14400, lr=0.140250, epoch loss=2.973210
Batch=59, step=14460, lr=0.139750, batch loss=0.107019, epoch loss=0.107019
Batch=119, step=14520, lr=0.139500, batch loss=0.099625, epoch loss=0.206644
Batch=179, step=14580, lr=0.139500, batch loss=0.103011, epoch loss=0.309656
Batch=239, step=14640, lr=0.139250, batch loss=0.142347, epoch loss=0.452003
Batch=299, step=14700, lr=0.138750, batch loss=0.078832, epoch loss=0.530835
Batch=359, step=14760, lr=0.138500, batch loss=0.120704, epoch loss=0.651539
Batch=419, step=14820, lr=0.138500, batch loss=0.133614, epoch loss=0.785153
Batch=479, step=14880, lr=0.138250, batch loss=0.101162, epoch loss=0.886314
Batch=539, step=14940, lr=0.138000, batch loss=0.098786, epoch loss=0.985101
Batch=599, step=15000, lr=0.137500, batch loss=0.085092, epoch loss=1.070193
Batch=659, step=15060, lr=0.137500, batch loss=0.134062, epoch loss=1.204256
Batch=719, step=15120, lr=0.137000, batch loss=0.159745, epoch loss=1.364000
Batch=779, step=15180, lr=0.137000, batch loss=0.262921, epoch loss=1.626921
Batch=839, step=15240, lr=0.136750, batch loss=0.152575, epoch loss=1.779496
Batch=899, step=15300, lr=0.136500, batch loss=0.151267, epoch loss=1.930762
Batch=959, step=15360, lr=0.136250, batch loss=0.080423, epoch loss=2.011185
Batch=1019, step=15420, lr=0.135750, batch loss=0.164767, epoch loss=2.175952
Batch=1079, step=15480, lr=0.135500, batch loss=0.041040, epoch loss=2.216992
Batch=1139, step=15540, lr=0.135250, batch loss=0.090535, epoch loss=2.307526
Batch=1199, step=15600, lr=0.135250, batch loss=0.058365, epoch loss=2.365891
Epoch=12, step=15600, lr=0.135250, epoch loss=2.365891
Batch=59, step=15660, lr=0.135000, batch loss=0.081778, epoch loss=0.081778
Batch=119, step=15720, lr=0.134500, batch loss=0.129712, epoch loss=0.211491
Batch=179, step=15780, lr=0.134500, batch loss=0.094917, epoch loss=0.306407
Batch=239, step=15840, lr=0.134250, batch loss=0.096789, epoch loss=0.403196
Batch=299, step=15900, lr=0.133750, batch loss=0.041188, epoch loss=0.444384
Batch=359, step=15960, lr=0.133500, batch loss=0.081904, epoch loss=0.526289
Batch=419, step=16020, lr=0.133250, batch loss=0.084255, epoch loss=0.610544
Batch=479, step=16080, lr=0.133250, batch loss=0.067724, epoch loss=0.678268
Batch=539, step=16140, lr=0.133000, batch loss=0.054964, epoch loss=0.733231
Batch=599, step=16200, lr=0.132500, batch loss=0.100749, epoch loss=0.833981
Batch=659, step=16260, lr=0.132250, batch loss=0.079632, epoch loss=0.913613
Batch=719, step=16320, lr=0.132000, batch loss=0.070373, epoch loss=0.983985
Batch=779, step=16380, lr=0.131750, batch loss=0.071710, epoch loss=1.055695
Batch=839, step=16440, lr=0.131500, batch loss=0.104662, epoch loss=1.160357
Batch=899, step=16500, lr=0.131500, batch loss=0.161450, epoch loss=1.321807
Batch=959, step=16560, lr=0.131250, batch loss=0.052967, epoch loss=1.374775
Batch=1019, step=16620, lr=0.130750, batch loss=0.132971, epoch loss=1.507746
Batch=1079, step=16680, lr=0.130750, batch loss=0.029459, epoch loss=1.537205
Batch=1139, step=16740, lr=0.130250, batch loss=0.059764, epoch loss=1.596969
Batch=1199, step=16800, lr=0.130250, batch loss=0.029225, epoch loss=1.626194
Epoch=13, step=16800, lr=0.130250, epoch loss=1.626194
Batch=59, step=16860, lr=0.129750, batch loss=0.040284, epoch loss=0.040284
Batch=119, step=16920, lr=0.129750, batch loss=0.069320, epoch loss=0.109604
Batch=179, step=16980, lr=0.129250, batch loss=0.054646, epoch loss=0.164251
Batch=239, step=17040, lr=0.129250, batch loss=0.066055, epoch loss=0.230306
Batch=299, step=17100, lr=0.129000, batch loss=0.030880, epoch loss=0.261186
Batch=359, step=17160, lr=0.128500, batch loss=0.048606, epoch loss=0.309792
Batch=419, step=17220, lr=0.128250, batch loss=0.050727, epoch loss=0.360518
Batch=479, step=17280, lr=0.128000, batch loss=0.030235, epoch loss=0.390753
Batch=539, step=17340, lr=0.128000, batch loss=0.056667, epoch loss=0.447420
Batch=599, step=17400, lr=0.127500, batch loss=0.035378, epoch loss=0.482798
Batch=659, step=17460, lr=0.127250, batch loss=0.047417, epoch loss=0.530214
Batch=719, step=17520, lr=0.127000, batch loss=0.052915, epoch loss=0.583130
Batch=779, step=17580, lr=0.127000, batch loss=0.107515, epoch loss=0.690644
Batch=839, step=17640, lr=0.126500, batch loss=0.111571, epoch loss=0.802215
Batch=899, step=17700, lr=0.126250, batch loss=0.157995, epoch loss=0.960210
Batch=959, step=17760, lr=0.126250, batch loss=0.021350, epoch loss=0.981560
Batch=1019, step=17820, lr=0.125750, batch loss=0.040308, epoch loss=1.021868
Batch=1079, step=17880, lr=0.125500, batch loss=0.012768, epoch loss=1.034636
Batch=1139, step=17940, lr=0.125500, batch loss=0.037808, epoch loss=1.072444
Batch=1199, step=18000, lr=0.125250, batch loss=0.016454, epoch loss=1.088898
Epoch=14, step=18000, lr=0.125250, epoch loss=1.088898
Batch=59, step=18060, lr=0.125000, batch loss=0.015734, epoch loss=0.015734
Batch=119, step=18120, lr=0.124500, batch loss=0.026714, epoch loss=0.042448
Batch=179, step=18180, lr=0.124250, batch loss=0.063342, epoch loss=0.105789
Batch=239, step=18240, lr=0.124250, batch loss=0.038163, epoch loss=0.143952
Batch=299, step=18300, lr=0.123750, batch loss=0.014685, epoch loss=0.158637
Batch=359, step=18360, lr=0.123500, batch loss=0.042958, epoch loss=0.201595
Batch=419, step=18420, lr=0.123250, batch loss=0.031573, epoch loss=0.233169
Batch=479, step=18480, lr=0.123000, batch loss=0.020679, epoch loss=0.253848
Batch=539, step=18540, lr=0.123000, batch loss=0.029502, epoch loss=0.283349
Batch=599, step=18600, lr=0.122750, batch loss=0.025662, epoch loss=0.309011
Batch=659, step=18660, lr=0.122500, batch loss=0.031696, epoch loss=0.340707
Batch=719, step=18720, lr=0.122000, batch loss=0.047498, epoch loss=0.388205
Batch=779, step=18780, lr=0.121750, batch loss=0.106625, epoch loss=0.494829
Batch=839, step=18840, lr=0.121750, batch loss=0.057378, epoch loss=0.552207
Batch=899, step=18900, lr=0.121500, batch loss=0.055886, epoch loss=0.608094
Batch=959, step=18960, lr=0.121000, batch loss=0.013958, epoch loss=0.622052
Batch=1019, step=19020, lr=0.121000, batch loss=0.023434, epoch loss=0.645486
Batch=1079, step=19080, lr=0.120750, batch loss=0.010681, epoch loss=0.656168
Batch=1139, step=19140, lr=0.120500, batch loss=0.023355, epoch loss=0.679522
Batch=1199, step=19200, lr=0.120000, batch loss=0.009659, epoch loss=0.689181
Epoch=15, step=19200, lr=0.120000, epoch loss=0.689181
Batch=59, step=19260, lr=0.120000, batch loss=0.004394, epoch loss=0.004394
Batch=119, step=19320, lr=0.119500, batch loss=0.012676, epoch loss=0.017070
Batch=179, step=19380, lr=0.119250, batch loss=0.024997, epoch loss=0.042067
Batch=239, step=19440, lr=0.119000, batch loss=0.027042, epoch loss=0.069109
Batch=299, step=19500, lr=0.119000, batch loss=0.013854, epoch loss=0.082963
Batch=359, step=19560, lr=0.118500, batch loss=0.017215, epoch loss=0.100177
Batch=419, step=19620, lr=0.118500, batch loss=0.020573, epoch loss=0.120751
Batch=479, step=19680, lr=0.118250, batch loss=0.008029, epoch loss=0.128780
Batch=539, step=19740, lr=0.118000, batch loss=0.017002, epoch loss=0.145782
Batch=599, step=19800, lr=0.117500, batch loss=0.022698, epoch loss=0.168480
Batch=659, step=19860, lr=0.117250, batch loss=0.019428, epoch loss=0.187908
Batch=719, step=19920, lr=0.117250, batch loss=0.049303, epoch loss=0.237212
Batch=779, step=19980, lr=0.117000, batch loss=0.079577, epoch loss=0.316789
Batch=839, step=20040, lr=0.116750, batch loss=0.031585, epoch loss=0.348374
Batch=899, step=20100, lr=0.116500, batch loss=0.029288, epoch loss=0.377662
Batch=959, step=20160, lr=0.116000, batch loss=0.013731, epoch loss=0.391393
Batch=1019, step=20220, lr=0.116000, batch loss=0.023883, epoch loss=0.415277
Batch=1079, step=20280, lr=0.115500, batch loss=0.003334, epoch loss=0.418610
Batch=1139, step=20340, lr=0.115500, batch loss=0.016692, epoch loss=0.435303
Batch=1199, step=20400, lr=0.115000, batch loss=0.006826, epoch loss=0.442129
Epoch=16, step=20400, lr=0.115000, epoch loss=0.442129
Batch=59, step=20460, lr=0.114750, batch loss=0.003229, epoch loss=0.003229
Batch=119, step=20520, lr=0.114500, batch loss=0.010105, epoch loss=0.013335
Batch=179, step=20580, lr=0.114500, batch loss=0.027274, epoch loss=0.040608
Batch=239, step=20640, lr=0.114000, batch loss=0.014279, epoch loss=0.054887
Batch=299, step=20700, lr=0.113750, batch loss=0.002929, epoch loss=0.057816
Batch=359, step=20760, lr=0.113750, batch loss=0.013670, epoch loss=0.071485
Batch=419, step=20820, lr=0.113500, batch loss=0.017058, epoch loss=0.088543
Batch=479, step=20880, lr=0.113000, batch loss=0.006324, epoch loss=0.094867
Batch=539, step=20940, lr=0.112750, batch loss=0.016632, epoch loss=0.111500
Batch=599, step=21000, lr=0.112500, batch loss=0.018227, epoch loss=0.129727
Batch=659, step=21060, lr=0.112250, batch loss=0.014415, epoch loss=0.144142
Batch=719, step=21120, lr=0.112000, batch loss=0.044610, epoch loss=0.188752
Batch=779, step=21180, lr=0.112000, batch loss=0.070222, epoch loss=0.258974
Batch=839, step=21240, lr=0.111500, batch loss=0.026121, epoch loss=0.285094
Batch=899, step=21300, lr=0.111500, batch loss=0.028251, epoch loss=0.313346
Batch=959, step=21360, lr=0.111000, batch loss=0.010717, epoch loss=0.324062
Batch=1019, step=21420, lr=0.110750, batch loss=0.012041, epoch loss=0.336103
Batch=1079, step=21480, lr=0.110500, batch loss=0.002417, epoch loss=0.338520
Batch=1139, step=21540, lr=0.110250, batch loss=0.012095, epoch loss=0.350615
Batch=1199, step=21600, lr=0.110250, batch loss=0.004861, epoch loss=0.355476
Epoch=17, step=21600, lr=0.110250, epoch loss=0.355476
Batch=59, step=21660, lr=0.110000, batch loss=0.001825, epoch loss=0.001825
Batch=119, step=21720, lr=0.109750, batch loss=0.007781, epoch loss=0.009606
Batch=179, step=21780, lr=0.109250, batch loss=0.015982, epoch loss=0.025588
Batch=239, step=21840, lr=0.109000, batch loss=0.014187, epoch loss=0.039775
Batch=299, step=21900, lr=0.108750, batch loss=0.003029, epoch loss=0.042804
Batch=359, step=21960, lr=0.108750, batch loss=0.011812, epoch loss=0.054616
Batch=419, step=22020, lr=0.108500, batch loss=0.012488, epoch loss=0.067104
Batch=479, step=22080, lr=0.108250, batch loss=0.003076, epoch loss=0.070180
Batch=539, step=22140, lr=0.108000, batch loss=0.017308, epoch loss=0.087489
Batch=599, step=22200, lr=0.107750, batch loss=0.016439, epoch loss=0.103928
Batch=659, step=22260, lr=0.107250, batch loss=0.015116, epoch loss=0.119044
Batch=719, step=22320, lr=0.107000, batch loss=0.025923, epoch loss=0.144967
Batch=779, step=22380, lr=0.107000, batch loss=0.042334, epoch loss=0.187301
Batch=839, step=22440, lr=0.106500, batch loss=0.022055, epoch loss=0.209356
Batch=899, step=22500, lr=0.106250, batch loss=0.021999, epoch loss=0.231355
Batch=959, step=22560, lr=0.106000, batch loss=0.010995, epoch loss=0.242350
Batch=1019, step=22620, lr=0.106000, batch loss=0.009608, epoch loss=0.251958
Batch=1079, step=22680, lr=0.105750, batch loss=0.000530, epoch loss=0.252487
Batch=1139, step=22740, lr=0.105250, batch loss=0.010545, epoch loss=0.263032
Batch=1199, step=22800, lr=0.105250, batch loss=0.004216, epoch loss=0.267248
Epoch=18, step=22800, lr=0.105250, epoch loss=0.267248
Batch=59, step=22860, lr=0.105000, batch loss=0.001245, epoch loss=0.001245
Batch=119, step=22920, lr=0.104750, batch loss=0.005673, epoch loss=0.006918
Batch=179, step=22980, lr=0.104500, batch loss=0.010979, epoch loss=0.017897
Batch=239, step=23040, lr=0.104000, batch loss=0.009052, epoch loss=0.026949
Batch=299, step=23100, lr=0.103750, batch loss=0.008767, epoch loss=0.035716
Batch=359, step=23160, lr=0.103500, batch loss=0.012859, epoch loss=0.048575
Batch=419, step=23220, lr=0.103250, batch loss=0.010522, epoch loss=0.059097
Batch=479, step=23280, lr=0.103000, batch loss=0.002451, epoch loss=0.061548
Batch=539, step=23340, lr=0.102750, batch loss=0.017408, epoch loss=0.078955
Batch=599, step=23400, lr=0.102500, batch loss=0.013798, epoch loss=0.092754
Batch=659, step=23460, lr=0.102250, batch loss=0.011763, epoch loss=0.104517
Batch=719, step=23520, lr=0.102250, batch loss=0.011252, epoch loss=0.115769
Batch=779, step=23580, lr=0.102000, batch loss=0.017513, epoch loss=0.133282
Batch=839, step=23640, lr=0.101750, batch loss=0.026480, epoch loss=0.159762
Batch=899, step=23700, lr=0.101250, batch loss=0.022248, epoch loss=0.182010
Batch=959, step=23760, lr=0.101000, batch loss=0.008453, epoch loss=0.190464
Batch=1019, step=23820, lr=0.100750, batch loss=0.008900, epoch loss=0.199363
Batch=1079, step=23880, lr=0.100500, batch loss=0.000895, epoch loss=0.200258
Batch=1139, step=23940, lr=0.100250, batch loss=0.008825, epoch loss=0.209083
Batch=1199, step=24000, lr=0.100000, batch loss=0.004618, epoch loss=0.213702
Epoch=19, step=24000, lr=0.100000, epoch loss=0.213702


Half-moons scatterplot and decision boundary:
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└────────────────────────────────────────────────────────────────────────────────────────────────────┘
"/usr/bin/env" "bash" "-c" "opam exec -- dune build @install @check @runtest && rm -rf _build" failed with exit status 1
2025-05-22 20:07.15: Job failed: Failed: Build failed