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When ggml_backend_buffer_free() is called, the device memory
is released but not all backends consistently release the actual
ggml_backend_buffer_t in system RAM, causing a memory leak.

Bug #10040

Mistral is a popular research lab making open source models. This updates
the forward pass of llama architecture models to support both llama models
and mistral models by accounting for additional metadata present in mistral
models, and finding the correct dimensions for the output projection.

* macOS has different definition per info from @mxyng

Signed-off-by: shane.xb.qian <shane.qian@foxmail.com>

some tensors are expected to be used in repeating layers but are not
themselves repeated. this change copies these tensors into the same
backends as their repeating counterparts to minimize copying tensors
between backends

use a similar strategy as llama.cpp for deciding where tensors should be
allocated. this will be improved later to be aware of usable memory
before assigning the tensor

- output backend system info when initializing the backend. this ensures
  this information is always present without needing to be called
  explicitly
- convert to structured logging
- enumerate devices rather than backends since devices are ordered
- track device indices grouped by device name

expand backend loading error handling to catch more problems and log
them instead of panicing

Fixes sync filters and lowers CUDA version to 11.3 in test.yaml

During work on our new registry client, I ran into frustrations with CI
where a misspelling in a comment caused the linter to fail, which caused
the tests to not run, which caused the build to not be cached, which
caused the next run to be slow, which caused me to be sad.

This commit address these issues, and pulls in some helpful changes
we've had in CI on ollama.com for some time now.

They are:

* Always run tests, even if the other checks fail.

Tests are the most important part of CI, and should always run. Failures
in tests can be correlated with failures in other checks, and can help
surface the root cause of the failure sooner. This is especially
important when the failure is platform specific, and the tests are not
platform independent.

* Check that `go generate` is clean.

This prevents 'go generate' abuse regressions. This codebase used to use
it to generate platform specific binary build artifacts. Let's make sure
that does not happen again and this powerful tool is used correctly, and
the generated code is checked in.

Also, while adding `go generate` the check, it was revealed that the
generated metal code was putting dates in the comments, resulting in
non-deterministic builds. This is a bad practice, and this commit fixes
that. Git tells us the most important date: the commit date along with
other associated changes.

* Check that `go mod tidy` is clean.

A new job to check that `go mod tidy` is clean was added, to prevent
easily preventable merge conflicts or go.mod changes being deferred to a
future PR that is unrelated to the change that caused the go.mod to
change.

* More robust caching.

We now cache the go build cache, and the go mod download cache
independently. This is because the download cache contains zips that can
be unpacked in parallel faster than they can be fetched and extracted by
tar. This speeds up the build significantly.

The linter is hostile enough. It does not need to also punish us with
longer build times due to small failures like misspellings.

sapphire rapids has amx support but it ends up having a negative
performance impact.

emerald rapids also has amx support with a positive performance impact
however there's no reasonable way in ggml to differentiate between the
two. the impact is small (~6%) so disable amx entirely for simplicity

* wrap ggml_backend_load_best in try/catch
* ignore non-ollama paths

* chore: update gitattributes
* chore: add build info source

This reverts commit bea1f1fa.

* add build to .dockerignore

* test: only build one arch

* add build to .gitignore

* fix ccache path

* filter amdgpu targets

* only filter if autodetecting

* Don't clobber gpu list for default runner

This ensures the GPU specific environment variables are set properly

* explicitly set CXX compiler for HIP

* Update build_windows.ps1

This isn't complete, but is close.  Dependencies are missing, and it only builds the "default" preset.

* build: add ollama subdir

* add .git to .dockerignore

* docs: update development.md

* update build_darwin.sh

* remove unused scripts

* llm: add cwd and build/lib/ollama to library paths

* default DYLD_LIBRARY_PATH to LD_LIBRARY_PATH in runner on macOS

* add additional cmake output vars for msvc

* interim edits to make server detection logic work with dll directories like lib/ollama/cuda_v12

* remove unncessary filepath.Dir, cleanup

* add hardware-specific directory to path

* use absolute server path

* build: linux arm

* cmake install targets

* remove unused files

* ml: visit each library path once

* build: skip cpu variants on arm

* build: install cpu targets

* build: fix workflow

* shorter names

* fix rocblas install

* docs: clean up development.md

* consistent build dir removal in development.md

* silence -Wimplicit-function-declaration build warnings in ggml-cpu

* update readme

* update development readme

* llm: update library lookup logic now that there is one runner (#8587)

* tweak development.md

* update docs

* add windows cuda/rocm tests

---------
Co-authored-by: jmorganca <jmorganca@gmail.com>
Co-authored-by: Daniel Hiltgen <daniel@ollama.com>