GitLab

* (backend) use parking_lot crate for RwLock fairness

# Conflicts:
#	backends/trtllm/src/backend.rs

* (launcher) default new server::run parameters to false for now

* (chore) fmt ... why?

* (ffi) use const for GetSamplingConfig

* (server) expose new SchedulingError

* (trt)

* (build) setup ccache if available

* (ffi) add max_new_tokens parameters

* (backend) cleanup a bit

* (backend) expose PullNewTokens

* (ffi) cleanup again

* (ffi) add missing headers imports

* (ffi) add template specialization to catch and convert to Rust Result<T, tensorrt_llm::common::TllmException>

* (looper) new looper initial implementation

* (ffi) remove narrowing type warning

* (ffi) encode the provided user prompt within each request thread

* (misc) change scope identifiers

* (backend) implement the post_processor background thread

* (misc) missing Result types for Rust

* use blocking_recv in looper to consume awaiting_requests at max before pulling in a single step

* (server) forward auth_token to server::run

* (build) fetchcontent use archives instead of git

* (ffi) fix usage of wrong vector constructor making a capacity fill call

* (ffi) missing namespace for tle::Response

* (ffi) do not use reference capture in lambda as we are not capturing anything

* (backend) refactor & cleanup

* (Dockerfile.trtllm) delete for now

* (misc) simplify [make_]move_iterator by using c++20 type inference

* (misc) no need to move for uint32_t items

* (scheduler) rework submit/pull logic

* (post) impl postprocessing

* (misc) delete backend.rs

* (misc) rerun-if-changed all the cmake modules

* (misc) move to latest trtllm

* (fix): HOPPER_SM_MAJOR is 9 not 8

* (misc: build for sm_{75,80,86,89,90} by default

* (misc): build with trtllm 0.13.0

* (misc): increase verbosity of spdlog

* (fix): do not recreate the stateful hashmap at every it

* (misc): update dependency in trtllm dockerfile

* (misc): update dependency in trtllm dockerfile

* (misc): disable logging in release mode

* (misc): improve trtllm download script robustness

* (fix): ore fixes for Dockerfile

* misc(cuda): require 12.6

* chore(cmake): use correct policy for download_timestamp

* feat(looper): check engine and executorWorker paths exist before creating the backend

* chore(cmake): download timestamp should be before URL

* feat(looper): minor optimizations to avoid growing too much the containers

* chore(trtllm): move dockerfile to right place

* chore(trtllm): disable tokenizer parallelism by default

* chore(trtllm): fmt

* chore(trtllm): post-rebase commit

* chore(trtllm): remove unused method

* feat(trtllm): cache maxNumTokens to avoid calling JSON everytime

* misc(router): remove SchedulingError

* feat(trtllm): do not tokenize twice

* Revert "chore(trtllm): remove unused method"

This reverts commit 31747163

* chore(rebase): fix invalid references

* chore(router): add python dependency

* Lint.

* Fix bad rebase

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

specifiying a value.

* feat: allow any supported payload on /invocations

* update openAPI

* update doc

* wip

* rollback

* refactor to use prefix/postfix namming + fix all_input_ids_tensor

* maybe patching vlms?

* fix filter and concat

* wip, no filter, no concat

* current

* add prepare_for_prefill

* working

* load tested

* re-create slots

* re-create slots

* fix slot_filtering_indices

* feedback loop

* remove log

* fix benchmarker

* fix vlm and seq2seq

* rename to cache and input lengths

* fix prefill logprobs

* fix launcher

* fix logprobs?

* idk at this point

* max input length

* omfg

* remove debugging lines

* fix tests

* fix mllama

* fix cargo tests

* remove support chunking for paged

* Fixing non blocked attentions

* Fixing dtype + AMD, Ipex targets.

* lint fix.

* rename

* Fix prefix_caching variable, remove defaults in server (confusing a lot
of the times).

* Add simple resolution when user specifies ATTENTION=paged.

* Put back non default simple tests.

* Fix env name

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

* adding max_token_capacity_metric

* added tgi to name of metric

* Adding max capacity metric.

* Add description for the metrics

---------
Co-authored-by: Edwinhr716 <Edandres249@gmail.com>

* wip

* added v2

* Adding a test for FD.

* Fixing flashdecoding (empty batch doesn't work).

* Fixing the invalid popping.

* Fixing radix with block_size > 1

* Last reference.

* Use an actual hash.

* Update hash for slice.len() == 1

* Update the locks.

* Increasing docker timeout.

* Fixing odd tokenization self modifications on the Rust side (load and
resave in Python).

* Fixing the builds ?

* Fix the gh action?

* Fixing the location ?

* Validation is odd.

* Try a faster runner

* Upgrade python version.

* Remove sccache

* No sccache.

* Getting libpython maybe ?

* List stuff.

* Monkey it up.

* have no idea at this point

* Tmp.

* Shot in the dark.

* Tmate the hell out of this.

* Desperation.

* WTF.

* -y.

* Apparently 3.10 is not available anymore.

* Updating the dockerfile to make libpython discoverable at runtime too.

* Put back rust tests.

* Why do we want mkl on AMD ?

* Forcing 3.11 ?

* Adding prefix test.

* [WIP] tmp dump of integration load tests.

* Remove other tensor creation.

* Fixed the radix tree.

Used a slice everywhere in radix.rs to keep the cheap Arc cloning
instead of recomputing the input_ids.

* Fix parsing

* Is it really flashinfer version ?

* Remove some comments.

* Revert the max prefix hit.

* Adding numpy to diff.

* Upgraded flashinfer.

* Upgrading some stuff.

* Are we done yet ?

* Minor fixup

* Remove 1 log and put back the other.

* Add comment for why slot 0 is OK.

* Mounting on the job.

* Get me a debug branch

* Debugging CIs is fun.

* Attempt #28

* wip

* Tmate.

* Praying.

* Updating VLM causal model with updated context.

* Important line got squashed.

* Tmate again.

* Fingers crossed.

* We want only 1 run of integration tests.....

---------
Co-authored-by: Guillaume LEGENDRE <glegendre01@gmail.com>

These should all be cheap assertions.

Also:

* Fixup some comments.
* Delete a `remove` that was done unnecessarily twice.

The minimum batch size logic could cause prefix blocks to be
deallocated without prefill. The next allocation of the same
prefix would then use garbage blocks.

* 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>

* fix: support tojson and avoid message indexing issue in template

* fix: prefer minijinja native methods and prefer workspace level dependency

* fix: adjust comment typo

* Prefix caching WIP

* Fixing prefix attention.

* Fixing flashinfer import.

* Fixing black.

* Fixing medusa (still wrong outputs, but functional).

* Just medusa values now.

* Fixing medusa without prefix caching.

* Fixing prefix caching.

* Medusa requires reshaping.

* Removing the logs.

* Remove router.nix

* Fixup:

- Remove logs
- Disable VLMs (they do not work)
- Disable prefix caching when user wants prefill logprobs.

* Update flake.lock

---------
Co-authored-by: Daniël de Kok <me@danieldk.eu>

* (backend) use parking_lot crate for RwLock fairness

* (docker) let's put rust in the TRTLLM folder when building

* (docker) build ompi with SLURM support

* (launcher) default new server::run parameters to false for now

* (chore) fmt ... why?

Co-authored-by: Daniël de Kok <me@danieldk.eu>

This change adds support for prefix caching to the v3 router. This
is broken up from the backend support to ease reviewing.

For now prefix caching is only enabled with `USE_PREFIX_CACHING=1`
in this case, the router will switch to `RadixAllocator`. This
allocator uses a radix trie to keep track of prefills that were
seen prior. If a new prefill is a prefix of a previously-seen
prefil, the router will send a request with `prefix_len>0`, which
can be used by the backend to decide to reuse KV blocks from the
cache, rather than recomputing them.

Even though backend support is not added in this PR, the backend
will still work with prefix caching enabled. The prefix lengths
are just ignored and not used.

* Using an enum for flash backens (paged/flashdecoding/flashinfer)

* Early exit on server too.

* Clippy.

* Fix clippy and fmt.

* Fix unsigned integer underflow

Passing --max-batch-size to the launcher actually had no effect
because after a few requests the max_size passed to State::next_batch
would underflow becoming a largo positive number.

In the scheduler, as soon as the cached batch size reached the
max_batch_size the max_size passed to next_batch becomes 0.
Since the only check in that funcion is
```
if Some(batch_requests.len()) == max_size {
    break;
}
```
and it's called after the `batch_requests.len()` has
become 1, it doesn't do anything to prevent more than 0
requests from being batched.

Now we have cached batch in the server that is large than
max_batch_size and `max_size - batch_size as usize`
underflows.
Signed-off-by: Max de Bayser <mbayser@br.ibm.com>

* fix: update v3 scheduler and ensure max_batch_size > 0

---------
Signed-off-by: Max de Bayser <mbayser@br.ibm.com>
Co-authored-by: Max de Bayser <mbayser@br.ibm.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`

* refactor usage stats

* Update docs/source/usage_statistics.md
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Update router/src/server.rs
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* changes based on feedback

* run python3 udpate_doc.py

* fix pre-commit

* Update router/src/server.rs
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* delete option around usage stats arg

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

* 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>