GitLab

* Making prefix/flashinfer the default and testing the full release tests.

* Include flashinfer in the docker.

* Using prebuilt.

* Allowing window_left_size (dummy version).

* Disabling flashinfer/prefix caching on odd head_dim

* Disable prefix caching for lora.

* More specific codes.

* Update lock

* Updating integration tests with new values with FI/FD.

Remove paged as a default too, and using FD everywhere.

* Update cargo lock ?

* Upgrade to 1.80 because of bitstream...

* Everywhere 1.80

* Forgot last default place.

* Apply suggestions from code review
Co-authored-by: drbh <david.richard.holtz@gmail.com>

* Updated flake lock

* Tmp

* Upgrade resolution system for less errors in resolution.

* Remove lambda for cleaner function.

* Handling debugger.

* OVerride the env in server tests.

* Is this enough to make it work ?

* This seems to be working.

* Downgrade some logs.

* Fixing the default for vlm.

* Don't enable prefix caching on VLM just yet.

* Change `add_special_tokens` in order to have the correct tokens for chat
input and not (since it's super important with the prefixing now)

* Fixing prefix caching for flashdecoding.

* Update all models.

* Fixed flashinfer version.

* add_special_tokens is internal only

* Fixing seqlen with the new vlms.

* Fixing the issue with `add_special_tokens` not being passed around.

* Fixing the test.

* Removing encoder_decoder (seq2seq).

* Update the chat test.

* Fixing the batching tokenization in flash causal lm.

* Truncating left for radix purposes.

* Oops this doesn't belong here.

* Put back default pure shell.

* Update server tests

- Default to throughput test in k6
- Use TGI_WIGGLE_ROOM to adjust wiggle room

* Only n_heads / process_group.size() are necessary.

* Revert the integrationt tests change (seem linked to head_size
modification).

* Adding error message when assert is violated.

* Fixing the free algorithm to handle times where the common prefix is
smaller.

* Apply suggestions from code review
Co-authored-by: OlivierDehaene <olivier@huggingface.co>

* Update server/text_generation_server/layers/attention/common.py
Co-authored-by: OlivierDehaene <olivier@huggingface.co>

* Fix disabling prefix caching - Fix windowing checks.

* Revert the Cohere tokenizer change (for now using a revision instead).

* Fmt.

---------
Co-authored-by: drbh <david.richard.holtz@gmail.com>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>

* All integration tests back everywhere (too many failed CI).

* Upgrade integration tests after 12.4

* Attempt to remove the specifed compute cap.

* Common arch list.

* Punica uses raw ASM which is not valid on 9.0 apparently.

* doc: Add metrics documentation and add a 'Reference' section

* doc: Add API reference

* doc: Refactor API reference

* fix: Message API link

* Bad rebase

* Moving the docs.

---------
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

add intel-cpu docker image
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* Fix cache block size for flash decoding

This seems to have been accidentally dropped during the TRT-LLM
PR rebase.

* Also run CI on changes to `backends`

* wip

wip

refacto

refacto

Initial setup for CXX binding to TRTLLM

Working FFI call for TGI and TRTLLM backend

Remove unused parameters annd force tokenizer name to be set

Overall build TRTLLM and deps through CMake build system

Enable end to end CMake build

First version loading engines and making it ready for inference

Remembering to check how we can detect support for chunked context

Move to latest TensorRT-LLM version

Specify which default log level to use depending on CMake build type

make leader executor mode working

unconditionally call InitializeBackend on the FFI layer

bind to CUDA::nvml to retrieve compute capabilities at runtime

updated logic and comment to detect cuda compute capabilities

implement the Stream method to send new tokens through a callback

use spdlog release 1.14.1 moving forward

update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c

correctly tell cmake to build dependent tensorrt-llm required libraries

create cmake install target to put everything relevant in installation folder

add auth_token CLI argument to provide hf hub authentification token

allow converting huggingface::tokenizers error to TensorRtLlmBackendError

use correct include for spdlog

include guard to build example in cmakelists

working setup of the ffi layer

remove fmt import

use external fmt lib

end to end ffi flow working

make sure to track include/ffi.h to trigger rebuild from cargo

impl the rust backend which currently cannot move the actual computation in background thread

expose shutdown function at ffi layer

impl RwLock scenario for TensorRtLllmBackend

oops missing c++ backend definitions

compute the number of maximum new tokens for each request independently

make sure the context is not dropped in the middle of the async decoding.

remove unnecessary log

add all the necessary plumbery to return the generated content

update invalid doc in cpp file

correctly forward back the log probabilities

remove unneeded scope variable for now

refactor Stream impl for Generation to factorise code

expose the internal missing start/queue timestamp

forward tgi parameters rep/freq penalty

add some more validation about grammar not supported

define a shared struct to hold the result of a decoding step

expose information about potential error happening while decoding

remove logging

add logging in case of decoding error

make sure executor_worker is provided

add initial Dockerfile for TRTLLM backend

add some more information in CMakeLists.txt to correctly install executorWorker

add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper

simplify prebuilt trtllm libraries name definition

do the same name definition stuff for tensorrt_llm_executor_static

leverage pkg-config to probe libraries paths and reuse new install structure from cmake

fix bad copy/past missing nvinfer linkage direction

align all the linker search dependency

add missing pkgconfig folder for MPI in Dockerfile

correctly setup linking search path for runtime layer

fix missing / before tgi lib path

adding missing ld_library_path for cuda stubs in Dockerfile

update tgi entrypoint

commenting out Python part for TensorRT installation

refactored docker image

move to TensorRT-LLM v0.11.0

make docker linter happy with same capitalization rule

fix typo

refactor the compute capabilities detection along with num gpus

update TensorRT-LLM to latest version

update TensorRT install script to latest

update build.rs to link to cuda 12.5

add missing dependant libraries for linking

clean up a bit

install to decoder_attention target

add some custom stuff for nccl linkage

fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time

use std::env::const::ARCH

make sure variable live long enough...

look for cuda 12.5

add some more basic info in README.md

* Rebase.

* Fix autodocs.

* Let's try to enable trtllm backend.

* Ignore backends/v3 by default.

* Fixing client.

* Fix makefile + autodocs.

* Updating the schema thing + redocly.

* Fix trtllm lint.

* Adding pb files ?

* Remove cargo fmt temporarily.

* ?

* Tmp.

* Remove both check + clippy  ?

* Backporting telemetry.

* Backporting 457fb0a1



* Remove PB from git.

* Fixing PB with default member backends/client

* update TensorRT-LLM to latest version

* provided None for api_key

* link against libtensorrt_llm and not libtensorrt-llm

---------
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>

Signed-off-by: Adrien <adrien@huggingface.co>

* Using g6 instead of g5.

* Update the idefics2 snapshot.

* test new instances
Signed-off-by: Adrien <adrien@huggingface.co>

* improve build ci
Signed-off-by: Adrien <adrien@huggingface.co>

---------
Signed-off-by: Adrien <adrien@huggingface.co>

* feat(fp8): add support for fbgemm

* allow loading fp8 weights directly

* update outlines

* fix makefile

* build fbgemm

* avoid circular import and fix dockerfile

* add default dtype

* refactored weights loader

* fix auto conversion

* fix quantization config parsing

* force new nccl on install

* missing get_weights implementation

* increase timeout

* re-push to internal registry
Signed-off-by: Adrien <adrien@huggingface.co>

* fix name
Signed-off-by: Adrien <adrien@huggingface.co>

* debug
Signed-off-by: Adrien <adrien@huggingface.co>

* debug
Signed-off-by: Adrien <adrien@huggingface.co>

* wip
Signed-off-by: Adrien <adrien@huggingface.co>

* wip
Signed-off-by: Adrien <adrien@huggingface.co>

* wip debug
Signed-off-by: Adrien <adrien@huggingface.co>

* add debug
Signed-off-by: Adrien <adrien@huggingface.co>

* should
Signed-off-by: Adrien <adrien@huggingface.co>

* wip
Signed-off-by: Adrien <adrien@huggingface.co>

* ww
Signed-off-by: Adrien <adrien@huggingface.co>

* wip
Signed-off-by: Adrien <adrien@huggingface.co>

* wip
Signed-off-by: Adrien <adrien@huggingface.co>

* ww
Signed-off-by: Adrien <adrien@huggingface.co>

* wip
Signed-off-by: Adrien <adrien@huggingface.co>

* wip
Signed-off-by: Adrien <adrien@huggingface.co>

* debug
Signed-off-by: Adrien <adrien@huggingface.co>

* w
Signed-off-by: Adrien <adrien@huggingface.co>

* revert tests
Signed-off-by: Adrien <adrien@huggingface.co>

* last reverts
Signed-off-by: Adrien <adrien@huggingface.co>

* another one
Signed-off-by: Adrien <adrien@huggingface.co>

---------
Signed-off-by: Adrien <adrien@huggingface.co>

* Updating the self check

* Fix.

* Revert the CLI .

* cli.

* Space.

* Revert cargo update.

* Update build.yaml

* Update build.yaml

* change to S3 cache

* change to CPU Runners

* remove comments

* Consistently take `prefix` in model constructors

* Release test check fix

* Misc refactor-related fixes

* Add more representative Llama GPTQ test

The Llama GPTQ test is updated to use a model with the commonly-used
quantizer config format and activation sorting. The old test is
kept around (but renamed) since it tests the format produced by
`text-generation-server quantize`.

* Add support for manually triggering a release build

* feat: add pre commit step to force schema update when router changes

* fix: prefer improved update_doc and start server and compare

* fix: adjust typo

* fix: adjust revert typo

* fix: update workflow to use update_doc md command

* feat: improve workflow to check openapi schema too

* fix: adjust timeout for CI

* fix: adjust raise condition and install server in ci

* fix: install protoc before server

* feat: improve update doc and add command to print router schema

* fix: adjust autodoc workflow

* fix: explicitly install protoc and python

* fix: alllow trailing space in openapi schema diff

* first test with registry mirror

* change push registry

* remove comments

* Move cache to push registry

* fix registry url

* Update .github/workflows/ci_build.yaml

---------
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Add pytest release marker

Annotate a test with `@pytest.mark.release` and it only gets run
with `pytest integration-tests --release`.

* Mark many models as `release` to speed up CI

* Removing IPEX_AVAIL.

Chose to unify CPU and XPU under `ipex`. Most code is exactly similar
except for a very few spots.

The biggest number of spots is the kv-cache layout and the flash_xxx.py
files.
Since those files should be removed soon and factored away, we should
not need them.

* Forgot a few places.

* Unrelated change.

* Fixing HF_TOKEN.

* HF_TOKEN

* Support HF_TOKEN environement variable

* Load test.

---------
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* New runner. Manual squash.

* Network host.

* Put back trufflehog with proper extension.

* No network host ?

* Moving buildx install after tailscale ?

* 1.79

* test local tailscale

* Update build.yaml

* Update build.yaml

* Update build.yaml

* Update build.yaml

* wait for ssh

* network host

* change step order

* Set maximum grpc message receive size to 2GiB

The previous default was 4MiB, which doesn't really work well for
multi-modal models.

* Update to Rust 1.79.0

* Fixup formatting to make PR pass

* feat: support response_format in chat

* fix: adjust typos

* fix: add trufflehog lint

The router will now send the input as chunks besides as a single
string. This change modifies the server to process chunked input
rather than strings. This also allows us to remove the image
extraction code from the server.

This reverts commit 101ac9a7.

# What does this PR do?

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