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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>

This was ignored up to now, even with `--cuda-graphs 0`.

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

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

# What does this PR do?

- Changed all models to extract `embed_tokens` in order to enable llava
to separately call the embeddings and the core model layers.
- Added VlmCausalLM to inherit from FlashMistral in order to be
maximally supported. The only added logics sits on top and parses images
into pixel values, preallocates input_ids space for the image
embeddings, and passes them for the model.
- Added Clip for the vision tower.
- Didn't add flash for the vision tower since there's no padding anyway.
- Added heuristic (potentially incomplete) to calculate number of
features *before* calculating the clip patches (allows for easier logic
reuse of the LLM under the hood).


Still needs to be done:

- [x] Implement the image parsing in the controller side, to avoid
downloading n times per TP shard and also refusing requests too large
early and avoid issues where the truncation actually truncates the
image.
- [ ] Make sure it works with quantization properly.
- [x] Make sure it works with TP>1



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# 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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This PR fixes parallel grammar requests, currently grammar states are
not concatenated correctly when a new request is added to the batch and
this results in incorrect generation. This PR updates the `concatenate`
function to correctly include the previous states.

fixes: #1601

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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"
}
```

Using a single `os.getenv` statement instead of multiple.
Should make truthful values easier to catch

In the end didn't move towards full CLI because modifying globals in
Python is error prone (depends on code import order).

Added an error when mamba is launched with TP.


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- Move float16 to bfloat16, which has less imprecisions (load test are
  failing with the update kernels + f16, all working under bf16).

  Another note, is that we are not respecting the layer norm in f32
  defined in the configuration (this is OK in my book, but that could
  impact the f16 precision)

- Moved to update kernels. Triton overhead is super high, removed by
  switching to cuda graphs works great (update cuda graph is available
  in TRT-LLM if needed, seems *exactly* like the regular ssm kernel.

- Moved inference_params struct in order to make only 2 tensors, to
  reduce the overhead of copying back and forth to the cuda graphs.

- Left over overhead seems entirely in the tokenization bit. (Still 4
  copies are paid before launching the graph)


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

# 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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Superseed #1024


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---------
Co-authored-by: bangoz <ch_xie@pku.edu.cn>

# What does this PR do?

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---------
Co-authored-by: Vincent Brouwers <vincent.brouwers@ing.com>

Close #673

Just trying to get the integration tests to pass.


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---------
Co-authored-by: Felix Marty <9808326+fxmarty@users.noreply.github.com>

Close
https://github.com/huggingface/text-generation-inference/issues/649
Close
https://github.com/huggingface/text-generation-inference/issues/651
Close
https://github.com/huggingface/text-generation-inference/issues/653
Close #636

Close #571

@njhill FYI

Closes #478

Close #288

Co-authored-by: Joel Lamy-Poirier <joel.lamy-poirier@servicenow.com>

Closes #307 #308