Commit Graph

48 Commits

Author SHA1 Message Date
OlivierDehaene a6a0c97ed9
feat: prefill chunking (#2600)
* 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>
2024-10-16 12:49:33 +02:00
Nicolas Patry cf04a43fb1
Fixing linters. (#2650) 2024-10-15 12:43:49 +02:00
Dmitry Rogozhkin 58848cb471
feat: enable pytorch xpu support for non-attention models (#2561)
XPU backend is available natively (without IPEX) in pytorch starting
from pytorch 2.4. This commit extends TGI to cover the case when user
has XPU support thru pytorch 2.4, but does not have IPEX installed.
Models which don't require attention can work. For attention required
models more work is needed to provide attention implementation.

Tested with the following models:
* teknium/OpenHermes-2.5-Mistral-7B
* bigscience/bloom-560m
* google/gemma-7b
* google/flan-t5-xxl

Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
2024-10-14 18:28:49 +02:00
Nicolas Patry 57b3495823
Fixing exl2 and other quanize tests again. (#2419)
* Fixing exl2 and other quanize tests again.

* Mark exl2 as non release (so CI tests them, needs to be removed latet).

* Fixing exl2 (by disabling cuda graphs)

* Fix quantization defaults without cuda graphs on exl2 (linked to new
issues with it).

* Removing serde override.

* Go back to released exl2 and remove log.

* Adding warnings for deprecated bitsandbytes + upgrade info to warn.
2024-08-15 11:12:51 +02:00
Nicolas Patry f3b5c69441
Upgrading exl2. (#2415)
* Upgrading exl2.

* Fixing the other pathways.

* Fix idefics.
2024-08-14 11:58:08 +02:00
drbh bab02ff2bc
feat: add ruff and resolve issue (#2262)
* feat: add ruff and resolve issue

* fix: update client exports and adjust after rebase

* fix: adjust syntax to avoid circular import

* fix: adjust client ruff settings

* fix: lint and refactor import check and avoid model enum as global names

* fix: improve fbgemm_gpu check and lints

* fix: update lints

* fix: prefer comparing model enum over str

* fix: adjust lints and ignore specific rules

* fix: avoid unneeded quantize check
2024-07-26 10:29:09 -04:00
Daniël de Kok 8511669cb2
Move quantized weight handling out of the `Weights` class (#2194)
Quantized weights were loaded in the `Weights` class, but this was
getting quite unwieldy, where every higher level method to load weights
was a long conditional to cover all the different quantizers.

This change moves loading of quantized weights out of the `Weights`
class. This is done by defining a simple `WeightsLoader` interface
that is implemented by `Exl2WeightsLoader`, `GPTQWeightsLoader`,
and `MarlinWeightsLoader`. These implementations are in the quantizers'
respective modules. The `Weights` class provides the low-level load
operations (such as loading tensors or sharded tensors), but delegates
loads that need quantizer-specific weight processing to a loader. The
loaders still use the low-level functionality provided by `Weights`.

I initially tried making a hierarchy where a class like `GPTQWeights`
would inherit from `Weights`. But it is not very flexible (e.g. does
not work well with the new weight storage mock used in tests) and
the implicit indirections made the code harder to follow.
2024-07-09 20:04:03 +02:00
Nicolas Patry fb2f74e2b9
Refactor dead code - Removing all `flash_xxx.py` files. (#2166)
* Refactor dead code.

* First working step.

* Remove a lot of duplicated code.

* More dead code.

* More cleanup.

* Fix Santacoder test.

* Fixing the simple tests.

* Fixing sharding.

* Fixes for VLM.

* Fixing santacoder (num_kv_heads hardcoded).

* Removing more dead code.

* Fixing `config.n_head`.

* Stopping earlier because of `<end_of_utterance>` in idefics2.

* Addresses comments.

* Removing the dead code.

* Fuse back mistral into FlashCausalLM.

* Finish removal.

* Fixing docs + causal_lm `batch_class`.

* Fixing docs + causal.lm.

* Add default to Gemma Causality.

* Default value for gemma/gemma2.

* Wrong default.
2024-07-05 10:29:56 +02:00
drbh 04e1af94d7
Enable multiple LoRa adapters (#2010)
* feat: first draft load multiple lora

* feat: load weights within layer and refactor lora pass

* fix: refactor and reduce lora math

* feat: baseline impl single request multi lora support

* feat: prefer lorax implementation and port loading logic

* fix: prefer adapter_data and refactors

* feat: perfer loraxs custom punica kernels and add mlp loras

* fix: adjust batch for bgmv

* fix: adjust adapter_segments logic when in batch

* fix: refactor and move changes to v3 proto

* fix: pass model_id for all flash causal lms

* fix: pass model_id for all causal and seq2seq lms

* fix: add model_id to model test

* feat: add lora support to mistral and refactors

* feat: prefer model id in request

* fix: include rust code for adapter id

* feat: bump launcher and add new lora docs

* feat: support base model generation and refactors

* fix: rename doc to retry ci build

* feat: support if vlm models

* fix: add adapter_data param and avoid missing layers

* fix: add adapter_data param to phi and neox

* fix: update all models forwards to include adapter_data

* fix: add model_id to IdeficsCausalLM

* Update lora.md

Fixed a typo

* Update lora.md

Fixing spam image

* fix: add lora kernel to dockerfile, support running without kernels and refactors

* fix: avoid dockerfile conflict

* fix: refactors and adjust flash llama lora logic

* fix: skip llama test due to CI issue (temp)

* fix: skip llama test CI (temp) 2

* fix: revert skips and prefer updated ci token for tests

* fix: refactors and helpful comments

* fix: add noop in TensorParallelAdapterRowLinear too

* fix: refactor and move shard_lora_weights logic

* fix: exit early if no adapter_data

---------

Co-authored-by: Derek <datavistics@gmail.com>
2024-06-25 14:46:27 -04:00
Daniël de Kok bf3c813782 server: use chunked inputs
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.
2024-06-07 08:09:04 +02:00
Nicolas Patry e3d765645a
MLPSpeculator. (#1865)
# What does this PR do?

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---------

Co-authored-by: Joshua Rosenkranz <joshua.rosenkranz@gmail.com>
2024-05-14 12:33:18 +02:00
OlivierDehaene 26cdea5c0c
feat: Qwen2 (#1608)
See #1584

---------

Co-authored-by: Cheng Kuan Yong Jason <jasoncky96@gmail.com>
2024-02-28 15:50:31 +01:00
Nicolas Patry bf700e7eef
Revamp medusa implementation so that every model can benefit. (#1588)
# What does this PR do?

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2024-02-26 19:49:28 +01:00
OlivierDehaene 9946165ee0
chore: add pre-commit (#1569) 2024-02-16 11:58:58 +01:00
drbh cef0553d59
Outlines guided generation (#1539)
This WIP PR starts to add grammar support via outlines, currently this
PR supports very simple regex grammars and does not optimize for
precompiling or caching grammar fsm's.

todo:
- [X] add simple outlines guidance to `NextTokenChooser`
- [X] update protos for grammar
- [X] update generation params API
- [X] constrain simple grammar
- [ ] support parsing more complex grammar into fsm
- [ ] support all outline support grammar types
- [ ] explore optimizations to avoid recompiling grammars

guided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data-raw '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6,
        "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+"
    }
}' | jq
```
response
```json
{
  "generated_text": "david@example.com"
}
```

unguided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6
    }
}' | jq
```
response
```json
{
  "generated_text": "    email = 'david"
}
```
2024-02-15 10:28:10 +01:00
OlivierDehaene 09b7c26bbd
feat(server): add frequency penalty (#1541) 2024-02-08 18:41:25 +01:00
Nicolas Patry 069895b985
Fixing top_n_tokens. (#1497)
# What does this PR do?

Superseeds #1459

The fix works as follows.
We updated next_token_chooser to return all logprbs, then
batch_top_n_tokens, now also gets accepted_ids + speculated_length (so
it knows how to interpret the flat logprobs).

We then update the code to return lists ot `Tokens` that it expects.
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2024-01-26 20:13:47 +01:00
OlivierDehaene 50b495f3d8
feat: add more latency metrics in forward (#1346) 2023-12-14 15:59:38 +01:00
OlivierDehaene 72ee382ded chore: formatting 2023-12-11 14:49:52 +01:00
Nicolas Patry 9ecfa16b12
Speculative (#1308) 2023-12-11 12:46:30 +01:00
OlivierDehaene 47954b81e9
feat: format code (#1070) 2023-09-27 12:22:09 +02:00
Nicolas Patry b32e9ce9d5
Remove the stripping of the prefix space (and any other mangling that tokenizers might do). (#1065)
Superseed #1024


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---------

Co-authored-by: bangoz <ch_xie@pku.edu.cn>
2023-09-27 12:13:45 +02:00
Vincent Brouwers 8672cad2cb
Fix top_n_tokens returning non-log probs for some models (#1023)
# What does this PR do?

I made an embarrassing mistake where I accidentally passed normal
softmax probabilities into `batch_top_tokens` for `CausalLM` and
`Seq2SeqLM`.

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@Narsil
2023-09-26 16:16:43 +02:00
Wang, Yi eeaa22ab04
enable bfloat16 for cpu (#1034)
if there's no cuda. disable custom kernels

# What does this PR do?

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
2023-09-19 17:19:28 +02:00
Nicolas Patry 211b54ac41
Rebased #617 (#868)
# What does this PR do?

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---------

Co-authored-by: Vincent Brouwers <vincent.brouwers@ing.com>
2023-08-28 11:43:47 +02:00
Nicolas Patry ecf6dc3a5a
feat: Add the option to force another dtype than `f16`. (#513) 2023-06-30 20:30:09 +02:00
OlivierDehaene e74bd41e0f
feat(server): add paged attention to flash models (#516)
Closes #478
2023-06-30 19:09:59 +02:00
OlivierDehaene 895c5f1562
feat(server): only compute prefill logprobs when asked (#406)
Close #288
2023-06-02 17:12:30 +02:00
OlivierDehaene 62f91f78ac
feat(server): support vectorized warpers in flash causal lm (#317)
Co-authored-by: Joel Lamy-Poirier <joel.lamy-poirier@servicenow.com>
2023-05-26 12:30:27 +02:00
OlivierDehaene 218c9adaa5
feat: decrease IPC proto size (#367)
Closes #307 #308
2023-05-24 19:19:57 +02:00
OlivierDehaene e3e487dc71
feat(server): support trust_remote_code (#363) 2023-05-23 20:40:39 +02:00
OlivierDehaene e9669a4085
feat(server): do not use device_map auto on single GPU (#362) 2023-05-23 19:12:12 +02:00
OlivierDehaene 5a58226130
fix(server): fix decode token (#334)
Fixes #333

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-05-16 23:23:27 +02:00
Nicolas Patry 76a48cd365
feat(server): GPTQ quantization (step1) (#277)
Changes only the type from `bool` to `Option<Enum>` pretty much
everywhere.
- Use `Optional[str]` in Python (easier to manage than importing type
everywhere). Except for the cli to get proper validation
- Updated all models to handle gracefully new values. (Error out if
unknown value, or gptq since not implemented).

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## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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      Pull Request section?
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- [ ] Did you write any new necessary tests?


## Who can review?

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2023-05-12 14:46:41 +02:00
OlivierDehaene 745f596c88
feat(server): use float16 (#304) 2023-05-10 15:51:10 +02:00
OlivierDehaene 68e9d6ab33
feat(server): shard token decode (#303) 2023-05-10 15:48:21 +02:00
Nick Hill 34bca0b8d3
fix(server): Small tidy of code from recent changes (#251)
remaining_decode_tokens was calculated twice in Seq2SeqLMBatch.filter()
2023-04-27 09:57:28 +02:00
OlivierDehaene ebc74d5666
feat(router): use number of tokens in batch as input for dynamic batching (#226)
Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-04-24 17:59:00 +02:00
Nick Hill 4a7dd4085a
feat(server): reduce memory requirement (#214) 2023-04-24 14:15:42 +02:00
OlivierDehaene 343437c7b5
feat(router): add device and dtype info (#215) 2023-04-21 15:36:29 +02:00
OlivierDehaene 709d8936f6
feat(router): drop requests when client closes the channel (#202) 2023-04-20 11:07:40 +02:00
OlivierDehaene 5fa8ae041c
feat(server): optimize decode for sane tokenizers (#170) 2023-04-12 12:03:10 +02:00
OlivierDehaene 299217c95c
feat(server): add flash attention llama (#144) 2023-04-11 16:38:22 +02:00
OlivierDehaene 9987960062
feat(router): make router input validation optional (#164) 2023-04-09 20:22:27 +02:00
OlivierDehaene b49dbf2d88
fix(server): use server tokenizer as gt (#128) 2023-03-16 12:12:26 +01:00
OlivierDehaene 8ad60b752f
fix(server): add position ids to neox (#126) 2023-03-15 13:12:49 +01:00
OlivierDehaene 941cd42e0c
fix(server): fix index out of range for watermarking (#110) 2023-03-08 18:29:08 +01:00
OlivierDehaene 3fef90d50f
feat(clients): Python client (#103) 2023-03-07 18:52:22 +01:00