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# What does this PR do?


This should enable more aggressive by default stacking, meaning better
throughput (in throughput constrained environements).

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# What does this PR do?

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---------
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

# What does this PR do?


On TPU (and probably inferentia). The model needs to know right off the
bat about BATCH_SIZE and MAX_TOTAL_TOKENS (since the entire cache will
be determined by both).

This PR sends that information to the shards to they can allocate
accordingly. Should be no-op for other backends.
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This was ignored up to now, even with `--cuda-graphs 0`.

With this fix, `--cuda-graphs` is obeyed to.

This PR allows the `CompletionRequest.prompt` to be sent as a string or
array of strings. When an array is sent the first value will be used if
it's a string; otherwise the according error will be thrown

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1690
Similar to: https://github.com/vllm-project/vllm/pull/323/files

# What does this PR do?

- Renamed `max_input_length` into `max_input_tokens` for consistency
(backward compatible change, will yell if both are set.)
- Will now use the config for `max_input_tokens` `max_total_token` and
`max_batch_total_tokens`.
- Capping the values to 16k in order to save VRAM on behalf of users
(overriddable by simply setting the values).

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# What does this PR do?

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---------
Co-authored-by: Dong Shin <d0104.shin@gmail.com>

wrap text-generation-launcher in docker image
mask ldconfig failures to user (no need in most cases anyway)

---------
Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>

This reverts commit b83aab9b.

@Narsil @drbh this will update flash attention v2 and vllm.
You will need to re-install them.

fixes
https://github.com/huggingface/text-generation-inference/issues/1711

Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>

# What does this PR do?

```
text-generation-launcher --model-id XXX # Uses cuda graphs by default
text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
```
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# What does this PR do?
Fix the following carsh when build the docker on Ubuntu22.04

```
error[E0432]: unresolved import `nix::sys::signal::Signal`
 --> launcher/src/main.rs:2:30
  |
2 | use nix::sys::signal::{self, Signal};
  |                              ^^^^^^ no `Signal` in `sys::signal`
  |
  = help: consider importing this type alias instead:
          ctrlc::Signal

error[E0432]: unresolved import `nix::unistd::Pid`
   --> launcher/src/main.rs:3:5
    |
3   | use nix::unistd::Pid;
    |     ^^^^^^^^^^^^^^^^ no `Pid` in `unistd`
    |
note: found an item that was configured out
   --> /usr/local/cargo/registry/src/index.crates.io-6f17d22bba15001f/nix-0.27.1/src/unistd.rs:183:12
    |
183 | pub struct Pid(pid_t);
    |            ^^^
    = note: the item is gated behind the `process` feature

error[E0425]: cannot find function `kill` in module `signal`

```



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---------
Signed-off-by: yuanwu <yuan.wu@intel.com>
Co-authored-by: drbh <david.richard.holtz@gmail.com>

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"
}
```

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

Some hardware require a maximum batch size.

# What does this PR do?

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This PR adds the `tokenizer-config-path` to the launcher and passes it
to the router

Fixes:
https://github.com/huggingface/text-generation-inference/pull/1427

# What does this PR do?

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---------
Co-authored-by: Andres Restrepo <andres@thelinuxkid.com>

#1186

This PR just bumps the latest rust version and makes clippy happy

```bash
cargo clippy --all -- -D warnings
#    Finished dev [unoptimized + debuginfo] target(s) in 0.10s
```

# What does this PR do?

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---------
Co-authored-by: zhaosida <zhaosida@corp.netease.com>

# What does this PR do?

Upgrade all relevant versions and dependencies.

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# Add AWQ quantization inference support

Fixes
https://github.com/huggingface/text-generation-inference/issues/781

This PR (partially) adds support for AWQ quantization for inference.
More information on AWQ [here](https://arxiv.org/abs/2306.00978). In
general, AWQ is faster and more accurate than GPTQ, which is currently
supported by TGI.

This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors
(in `requirements.txt`, just one line change).

Quick way to test this PR would be bring up TGI as follows:

```
text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq

text-generation-launcher \
--huggingface-hub-cache ~/.cache/huggingface/hub/ \
--model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \
--trust-remote-code --port 8080 \
--max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \
--quantize awq
```

Please note:
* This PR was tested with FlashAttention v2 and vLLM.
* This PR adds support for AWQ inference, not quantizing the models.
That needs to be done outside of TGI, instructions

[here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa).
* This PR only adds support for `FlashLlama` models for now.
* Multi-GPU setup has not been tested. 
* No integration tests have been added so far, will add later if
maintainers are interested in this change.
* This PR can be tested on any of the models released

[here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models).

Please refer to the linked issue for benchmarks for

[abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq)
vs

[TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ).

Please note, AWQ has released faster (and in case of Llama, fused)
kernels for 4-bit GEMM, currently at the top of the `main` branch at
https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit
that has been tested to work. We can switch to latest commit later on.

## Who can review?

@OlivierDehaene OR @Narsil

---------



# What does this PR do?

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Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com>
Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>

# What does this PR do?

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# What does this PR do?


See #626 
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- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
  chosen model id**

PROs:

- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE

CONs:

- Creates a local merged model in unusual location, potentially
  not saved across docker reloads, or ovewriting some files if the PEFT
  itself was local and containing other files in addition to the lora

Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
  code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
  location for this new model), but it would
  introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
  `download-weights` and asking user to restart with the actual local
  model location


Fix #482 


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# What does this PR do?


- Adds Rope NTK scaling.

Done because
https://github.com/huggingface/text-generation-inference/pull/529 was
closed
Took some code from
https://github.com/huggingface/transformers/pull/24653

- `--rope-scaling` and `--rope-factor` are added separately. I
considered having a single one and parsing something line ("linear:4.0"
, or "dynamic") but decided against
it because it would push more parsing+validation a bit everywhere (both
in the launcher and the server).


Fixes #512




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Close #673

# What does this PR do?

In title. Adds argument `--hostname` in router to support something like
`--hostname ::`. Tested with

```commandline
cargo run -- --port 8080 --hostname ::
curl -I -X GET 'http://[::1]:8080/health

'  # failed before this commit
```

Trigger CI

---------
Co-authored-by: Phil Chen <philchen2000@gmail.com>