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Prefix test - Different kind of load test to trigger prefix test bugs. (#2490) 

* 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>
This commit is contained in:
Nicolas Patry 2024-09-11 18:10:40 +02:00 committed by GitHub
parent eabbbbda23
commit a4e3e8c608
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
19 changed files with 4113 additions and 1077 deletions
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3
backends/v3/src/backend.rs
View File

@ -376,10 +376,9 @@ fn filter_send_generations(generations: Vec<Generation>, entries: &mut IntMap<u6
// Send generation responses back to the infer task
// If the receive an error from the Flume channel, it means that the client dropped the
// request and we need to stop generating hence why we unwrap_or(true)
let stopped = send_responses(generation, entry).map_err(|err| {
let stopped = send_responses(generation, entry).inspect_err(|_err| {
tracing::error!("Entry response channel error.");
metrics::counter!("tgi_request_failure", "err" => "dropped").increment(1);
err
}).unwrap_or(true);
if stopped {
entries.remove(&id).expect("ID not found in entries. This is a bug.");

2
backends/v3/src/radix.rs
View File

@ -123,8 +123,6 @@ impl Allocator for RadixAllocator {
prefill_tokens: prefill_tokens.clone(),
};
tracing::debug!("Blocks {blocks:?}");
self.allocation_id += 1;
self.allocations.insert(self.allocation_id, allocation);

58
flake.lock
View File

@ -492,6 +492,24 @@
"type": "github"
}
},
"flake-utils_7": {
"inputs": {
"systems": "systems_7"
},
"locked": {
"lastModified": 1710146030,
"narHash": "sha256-SZ5L6eA7HJ/nmkzGG7/ISclqe6oZdOZTNoesiInkXPQ=",
"owner": "numtide",
"repo": "flake-utils",
"rev": "b1d9ab70662946ef0850d488da1c9019f3a9752a",
"type": "github"
},
"original": {
"owner": "numtide",
"repo": "flake-utils",
"type": "github"
}
},
"gitignore": {
"inputs": {
"nixpkgs": [
@ -700,16 +718,16 @@
},
"nixpkgs_6": {
"locked": {
"lastModified": 1723912943,
"narHash": "sha256-39F9GzyhxYcY3wTeKuEFWRJWcrGBosO4nf4xzMTWZX8=",
"owner": "danieldk",
"lastModified": 1724915739,
"narHash": "sha256-7PgRge4mn5akFvhPwefuaLQGbF5BnmxlwZJEf7CgbrE=",
"owner": "nixos",
"repo": "nixpkgs",
"rev": "b82cdca86dbb30013b76c4b55d48806476820a5c",
"rev": "85be051bb60943d3328d91aaf2598798f87e19af",
"type": "github"
},
"original": {
"owner": "danieldk",
"ref": "cuda-12.4",
"owner": "nixos",
"ref": "nixos-unstable-small",
"repo": "nixpkgs",
"type": "github"
}
@ -835,11 +853,11 @@
]
},
"locked": {
"lastModified": 1724638882,
"narHash": "sha256-ap2jIQi/FuUHR6HCht6ASWhoz8EiB99XmI8Esot38VE=",
"lastModified": 1725848835,
"narHash": "sha256-u4lCr+tOEWhsFiww5G04U5jUNzaQJi0/ZMIDGiLeT14=",
"owner": "oxalica",
"repo": "rust-overlay",
"rev": "19b70f147b9c67a759e35824b241f1ed92e46694",
"rev": "2ef910a6276a2f34513d18f2f826a8dea72c3b3f",
"type": "github"
},
"original": {
@ -938,17 +956,33 @@
"type": "github"
}
},
"systems_7": {
"locked": {
"lastModified": 1681028828,
"narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
"owner": "nix-systems",
"repo": "default",
"rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
"type": "github"
},
"original": {
"owner": "nix-systems",
"repo": "default",
"type": "github"
}
},
"tgi-nix": {
"inputs": {
"flake-compat": "flake-compat_4",
"flake-utils": "flake-utils_7",
"nixpkgs": "nixpkgs_6"
},
"locked": {
"lastModified": 1725011596,
"narHash": "sha256-zfq8lOXFgJnKxxsqSelHuKUvhxgH3cEmLoAgsOO62Cg=",
"lastModified": 1725868835,
"narHash": "sha256-6OFEaFFRCG/JKkU6kHV08EPEGM1MCuKZ70NlGJcL/JY=",
"owner": "danieldk",
"repo": "tgi-nix",
"rev": "717c2b07e38538abf05237cca65b2d1363c2c9af",
"rev": "87afbe21e2d2cc17e177c9965a64ba68ad7c22da",
"type": "github"
},
"original": {

68
integration-tests/conftest.py
View File

@ -19,6 +19,7 @@ from syrupy.extensions.json import JSONSnapshotExtension
from text_generation import AsyncClient
from text_generation.types import (
BestOfSequence,
Message,
ChatComplete,
ChatCompletionChunk,
ChatCompletionComplete,
@ -97,25 +98,25 @@ class ResponseComparator(JSONSnapshotExtension):
) -> bool:
def convert_data(data):
data = json.loads(data)
if isinstance(data, Dict) and "choices" in data:
choices = data["choices"]
if isinstance(choices, List) and len(choices) >= 1:
if "delta" in choices[0]:
return ChatCompletionChunk(**data)
if "text" in choices[0]:
return Completion(**data)
return ChatComplete(**data)
return _convert_data(data)
def _convert_data(data):
if isinstance(data, Dict):
return Response(**data)
if "choices" in data:
data["choices"] = list(
sorted(data["choices"], key=lambda x: x["index"])
)
choices = data["choices"]
if isinstance(choices, List) and len(choices) >= 1:
if "delta" in choices[0]:
return ChatCompletionChunk(**data)
if "text" in choices[0]:
return Completion(**data)
return ChatComplete(**data)
else:
return Response(**data)
if isinstance(data, List):
if (
len(data) > 0
and "object" in data[0]
and data[0]["object"] == "text_completion"
):
return [Completion(**d) for d in data]
return [Response(**d) for d in data]
return [_convert_data(d) for d in data]
raise NotImplementedError
def eq_token(token: Token, other: Token) -> bool:
@ -571,3 +572,38 @@ def generate_load():
return await asyncio.gather(*futures)
return generate_load_inner
@pytest.fixture(scope="module")
def generate_multi():
async def generate_load_inner(
client: AsyncClient,
prompts: List[str],
max_new_tokens: int,
seed: Optional[int] = None,
) -> List[Response]:
import numpy as np
arange = np.arange(len(prompts))
perm = np.random.permutation(arange)
rperm = [-1] * len(perm)
for i, p in enumerate(perm):
rperm[p] = i
shuffled_prompts = [prompts[p] for p in perm]
futures = [
client.chat(
messages=[Message(role="user", content=prompt)],
max_tokens=max_new_tokens,
temperature=0,
seed=seed,
)
for prompt in shuffled_prompts
]
shuffled_responses = await asyncio.gather(*futures)
responses = [shuffled_responses[p] for p in rperm]
return responses
return generate_load_inner

30
integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_many_prompts.json
View File

@ -1,38 +1,38 @@
{
"choices": [
{
"finish_reason": "stop",
"finish_reason": "length",
"index": 0,
"logprobs": null,
"text": " A Beginner’s Guide\nDeep learning is a subset"
},
{
"finish_reason": "length",
"index": 1,
"logprobs": null,
"text": " PR for more information?"
"text": " This is a question that has puzzled many people for"
},
{
"finish_reason": "length",
"index": 3,
"logprobs": null,
"text": "hd20220811-"
},
{
"finish_reason": "length",
"index": 0,
"logprobs": null,
"text": "le Business Incubator is providing a workspace"
"text": "usculas_minusculas(s):\n \"\"\"\n"
},
{
"finish_reason": "length",
"index": 2,
"logprobs": null,
"text": " severely flawed and often has a substandard"
"text": " Paris\nWhat is the capital of France?\nThe"
}
],
"created": 1722014725,
"created": 1725877154,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native",
"usage": {
"completion_tokens": 36,
"prompt_tokens": 8,
"total_tokens": 44
"completion_tokens": 40,
"prompt_tokens": 22,
"total_tokens": 62
}
}

616
integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_many_prompts_stream.json
View File

@ -5,12 +5,12 @@
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": "\n"
"text": " A"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -20,12 +20,72 @@
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": "\n"
"text": " This"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": " Paris"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "us"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": " Beginner"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": " is"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -38,9 +98,9 @@
"text": "\n"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -50,12 +110,12 @@
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "hd"
"text": "cul"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -65,12 +125,12 @@
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": "\n"
"text": "’s"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -80,12 +140,12 @@
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": "\n"
"text": " a"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -95,12 +155,12 @@
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": "\n"
"text": "What"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -110,12 +170,12 @@
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "aho"
"text": "as"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -125,12 +185,12 @@
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": "2"
"text": " Guide"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -140,252 +200,12 @@
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": "2"
"text": " question"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": "2"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "ima"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": "."
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": "."
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": "."
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "\n"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": " Sarah"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": " Yes"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": " And"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "i"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": "'"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": ","
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": " what"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "'"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": "s"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": " Moh"
}
],
"created": 1724833943,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -398,9 +218,9 @@
"text": " is"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -410,12 +230,12 @@
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "m"
"text": "_minus"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -425,12 +245,12 @@
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": " Room"
"text": "\n"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -440,12 +260,12 @@
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": "s"
"text": " that"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -458,9 +278,9 @@
"text": " the"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -470,12 +290,12 @@
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": " tired"
"text": "cul"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -485,12 +305,12 @@
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": ":"
"text": "Deep"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -500,12 +320,12 @@
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": "'"
"text": " has"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -518,9 +338,9 @@
"text": " capital"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -530,12 +350,192 @@
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": ","
"text": "as"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": " learning"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": " puzzled"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": " of"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "(s"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": " is"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": " many"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": " France"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": "):\n"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": " a"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 1,
"logprobs": null,
"text": " people"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 2,
"logprobs": null,
"text": "?\n"
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
{
"choices": [
{
"finish_reason": "",
"index": 3,
"logprobs": null,
"text": " "
}
],
"created": 1725883643,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -545,12 +545,12 @@
"finish_reason": "length",
"index": 0,
"logprobs": null,
"text": " She"
"text": " subset"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -560,12 +560,12 @@
"finish_reason": "length",
"index": 1,
"logprobs": null,
"text": " scale"
"text": " for"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -575,12 +575,12 @@
"finish_reason": "length",
"index": 2,
"logprobs": null,
"text": " of"
"text": "The"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
},
@ -590,12 +590,12 @@
"finish_reason": "length",
"index": 3,
"logprobs": null,
"text": " its"
"text": " \"\"\"\n"
}
],
"created": 1724833943,
"created": 1725883643,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2.1-dev0-native"
}

12
integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_single_prompt.json
View File

@ -4,17 +4,17 @@
"finish_reason": "length",
"index": 0,
"logprobs": null,
"text": " PR for flake8"
"text": " A Beginner’s Guide\nDeep learning is a subset"
}
],
"created": 1713284454,
"created": 1725876621,
"id": "",
"model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.0.1-native",
"system_fingerprint": "2.2.1-dev0-native",
"usage": {
"completion_tokens": 5,
"completion_tokens": 10,
"prompt_tokens": 6,
"total_tokens": 11
"total_tokens": 16
}
}

2576
integration-tests/models/__snapshots__/test_flash_llama_prefix/test_flash_llama_load.json Normal file
View File

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46
integration-tests/models/test_completion_prompts.py
View File

@ -11,7 +11,7 @@ from text_generation.types import (
@pytest.fixture(scope="module")
def flash_llama_completion_handle(launcher):
with launcher(
"TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"meta-llama/Meta-Llama-3.1-8B-Instruct",
) as handle:
yield handle
@ -34,16 +34,19 @@ def test_flash_llama_completion_single_prompt(
f"{flash_llama_completion.base_url}/v1/completions",
json={
"model": "tgi",
"prompt": "Say this is a test",
"max_tokens": 5,
"seed": 0,
"prompt": "What is Deep Learning?",
"max_tokens": 10,
"temperature": 0.0,
},
headers=flash_llama_completion.headers,
stream=False,
)
response = response.json()
assert len(response["choices"]) == 1
assert (
response["choices"][0]["text"]
== " A Beginner’s Guide\nDeep learning is a subset"
)
assert response == response_snapshot
@ -53,9 +56,15 @@ def test_flash_llama_completion_many_prompts(flash_llama_completion, response_sn
f"{flash_llama_completion.base_url}/v1/completions",
json={
"model": "tgi",
"prompt": ["Say", "this", "is", "a"],
"prompt": [
"What is Deep Learning?",
"Is water wet?",
"What is the capital of France?",
"def mai",
],
"max_tokens": 10,
"seed": 0,
"temperature": 0.0,
},
headers=flash_llama_completion.headers,
stream=False,
@ -63,9 +72,16 @@ def test_flash_llama_completion_many_prompts(flash_llama_completion, response_sn
response = response.json()
assert len(response["choices"]) == 4
all_indexes = [choice["index"] for choice in response["choices"]]
all_indexes = [(choice["index"], choice["text"]) for choice in response["choices"]]
all_indexes.sort()
assert all_indexes == [0, 1, 2, 3]
all_indices, all_strings = zip(*all_indexes)
assert list(all_indices) == [0, 1, 2, 3]
assert list(all_strings) == [
" A Beginner’s Guide\nDeep learning is a subset",
" This is a question that has puzzled many people for",
" Paris\nWhat is the capital of France?\nThe",
'usculas_minusculas(s):\n """\n',
]
assert response == response_snapshot
@ -77,19 +93,21 @@ async def test_flash_llama_completion_many_prompts_stream(
request = {
"model": "tgi",
"prompt": [
"What color is the sky?",
"What is Deep Learning?",
"Is water wet?",
"What is the capital of France?",
"def mai",
],
"max_tokens": 10,
"seed": 0,
"temperature": 0.0,
"stream": True,
}
url = f"{flash_llama_completion.base_url}/v1/completions"
chunks = []
strings = [""] * 4
async with ClientSession(headers=flash_llama_completion.headers) as session:
async with session.post(url, json=request) as response:
# iterate over the stream
@ -108,7 +126,15 @@ async def test_flash_llama_completion_many_prompts_stream(
for c in chunk:
chunks.append(Completion(**c))
assert "choices" in c
assert 0 <= c["choices"][0]["index"] <= 4
index = c["choices"][0]["index"]
assert 0 <= index <= 4
strings[index] += c["choices"][0]["text"]
assert response.status == 200
assert list(strings) == [
" A Beginner’s Guide\nDeep learning is a subset",
" This is a question that has puzzled many people for",
" Paris\nWhat is the capital of France?\nThe",
'usculas_minusculas(s):\n """\n',
]
assert chunks == response_snapshot

229
integration-tests/models/test_flash_llama_prefix.py Normal file
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1379
integration-tests/poetry.lock generated
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5
integration-tests/pyproject.toml
View File

@ -6,9 +6,10 @@ authors = ["Nicolas Patry <nicolas@huggingface.co>"]
[tool.poetry.dependencies]
pydantic = "> 2, < 3"
python = ">=3.9,<3.13"
python = ">=3.10,<3.13"
syrupy = "^4.7.1"
text-generation = "^0.6.0"
pytest = "^7.4.0"
pytest-asyncio = "^0.21.1"
docker = "^6.1.3"
docker = "^7"
numpy = "^1.20"

69
integration-tests/requirements.txt
View File

@ -1,34 +1,35 @@
aiohttp==3.8.5 ; python_version >= "3.9" and python_version < "3.13"
aiosignal==1.3.1 ; python_version >= "3.9" and python_version < "3.13"
annotated-types==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
async-timeout==4.0.3 ; python_version >= "3.9" and python_version < "3.13"
attrs==23.1.0 ; python_version >= "3.9" and python_version < "3.13"
certifi==2023.7.22 ; python_version >= "3.9" and python_version < "3.13"
charset-normalizer==3.2.0 ; python_version >= "3.9" and python_version < "3.13"
colorama==0.4.6 ; python_version >= "3.9" and python_version < "3.13" and (sys_platform == "win32" or platform_system == "Windows")
docker==6.1.3 ; python_version >= "3.9" and python_version < "3.13"
exceptiongroup==1.1.3 ; python_version >= "3.9" and python_version < "3.11"
filelock==3.12.3 ; python_version >= "3.9" and python_version < "3.13"
frozenlist==1.4.0 ; python_version >= "3.9" and python_version < "3.13"
fsspec==2023.6.0 ; python_version >= "3.9" and python_version < "3.13"
huggingface-hub==0.16.4 ; python_version >= "3.9" and python_version < "3.13"
idna==3.4 ; python_version >= "3.9" and python_version < "3.13"
iniconfig==2.0.0 ; python_version >= "3.9" and python_version < "3.13"
multidict==6.0.4 ; python_version >= "3.9" and python_version < "3.13"
packaging==23.1 ; python_version >= "3.9" and python_version < "3.13"
pluggy==1.3.0 ; python_version >= "3.9" and python_version < "3.13"
pydantic-core==2.16.3 ; python_version >= "3.9" and python_version < "3.13"
pydantic==2.6.4 ; python_version >= "3.9" and python_version < "3.13"
pytest-asyncio==0.21.1 ; python_version >= "3.9" and python_version < "3.13"
pytest==7.4.0 ; python_version >= "3.9" and python_version < "3.13"
pywin32==306 ; python_version >= "3.9" and python_version < "3.13" and sys_platform == "win32"
pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "3.13"
requests==2.31.0 ; python_version >= "3.9" and python_version < "3.13"
syrupy==4.7.1 ; python_version >= "3.9" and python_version < "3.13"
text-generation==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
tomli==2.0.1 ; python_version >= "3.9" and python_version < "3.11"
tqdm==4.66.1 ; python_version >= "3.9" and python_version < "3.13"
typing-extensions==4.7.1 ; python_version >= "3.9" and python_version < "3.13"
urllib3==2.0.4 ; python_version >= "3.9" and python_version < "3.13"
websocket-client==1.6.2 ; python_version >= "3.9" and python_version < "3.13"
yarl==1.9.2 ; python_version >= "3.9" and python_version < "3.13"
aiohappyeyeballs==2.4.0 ; python_version >= "3.10" and python_version < "3.13"
aiohttp==3.10.5 ; python_version >= "3.10" and python_version < "3.13"
aiosignal==1.3.1 ; python_version >= "3.10" and python_version < "3.13"
annotated-types==0.7.0 ; python_version >= "3.10" and python_version < "3.13"
async-timeout==4.0.3 ; python_version >= "3.10" and python_version < "3.11"
attrs==24.2.0 ; python_version >= "3.10" and python_version < "3.13"
certifi==2024.8.30 ; python_version >= "3.10" and python_version < "3.13"
charset-normalizer==3.3.2 ; python_version >= "3.10" and python_version < "3.13"
colorama==0.4.6 ; python_version >= "3.10" and python_version < "3.13" and (sys_platform == "win32" or platform_system == "Windows")
docker==7.1.0 ; python_version >= "3.10" and python_version < "3.13"
exceptiongroup==1.2.2 ; python_version >= "3.10" and python_version < "3.11"
filelock==3.16.0 ; python_version >= "3.10" and python_version < "3.13"
frozenlist==1.4.1 ; python_version >= "3.10" and python_version < "3.13"
fsspec==2024.9.0 ; python_version >= "3.10" and python_version < "3.13"
huggingface-hub==0.24.6 ; python_version >= "3.10" and python_version < "3.13"
idna==3.8 ; python_version >= "3.10" and python_version < "3.13"
iniconfig==2.0.0 ; python_version >= "3.10" and python_version < "3.13"
multidict==6.1.0 ; python_version >= "3.10" and python_version < "3.13"
numpy==1.26.4 ; python_version >= "3.10" and python_version < "3.13"
packaging==24.1 ; python_version >= "3.10" and python_version < "3.13"
pluggy==1.5.0 ; python_version >= "3.10" and python_version < "3.13"
pydantic-core==2.23.3 ; python_version >= "3.10" and python_version < "3.13"
pydantic==2.9.1 ; python_version >= "3.10" and python_version < "3.13"
pytest-asyncio==0.21.2 ; python_version >= "3.10" and python_version < "3.13"
pytest==7.4.4 ; python_version >= "3.10" and python_version < "3.13"
pywin32==306 ; python_version >= "3.10" and python_version < "3.13" and sys_platform == "win32"
pyyaml==6.0.2 ; python_version >= "3.10" and python_version < "3.13"
requests==2.32.3 ; python_version >= "3.10" and python_version < "3.13"
syrupy==4.7.1 ; python_version >= "3.10" and python_version < "3.13"
text-generation==0.6.1 ; python_version >= "3.10" and python_version < "3.13"
tomli==2.0.1 ; python_version >= "3.10" and python_version < "3.11"
tqdm==4.66.5 ; python_version >= "3.10" and python_version < "3.13"
typing-extensions==4.12.2 ; python_version >= "3.10" and python_version < "3.13"
urllib3==2.2.2 ; python_version >= "3.10" and python_version < "3.13"
yarl==1.11.1 ; python_version >= "3.10" and python_version < "3.13"

3
launcher/src/main.rs
View File

@ -1843,9 +1843,8 @@ fn main() -> Result<(), LauncherError> {
shutdown.clone(),
&shutdown_receiver,
)
.map_err(|err| {
.inspect_err(|_| {
shutdown_shards(shutdown.clone(), &shutdown_receiver);
err
})?;
// Default exit code

3
router/src/infer/mod.rs
View File

@ -336,6 +336,8 @@ pub enum InferError {
ValidationError(#[from] ValidationError),
#[error("Incomplete generation")]
IncompleteGeneration,
#[error("Incomplete generation stream")]
IncompleteGenerationStream,
#[error("Template error: {0}")]
TemplateError(#[from] minijinja::Error),
#[error("Missing template vatiable: {0}")]
@ -351,6 +353,7 @@ impl InferError {
InferError::Overloaded(_) => "overloaded",
InferError::ValidationError(_) => "validation",
InferError::IncompleteGeneration => "incomplete_generation",
InferError::IncompleteGenerationStream => "incomplete_generation_stream",
InferError::TemplateError(_) => "template_error",
InferError::MissingTemplateVariable(_) => "missing_template_variable",
InferError::ToolError(_) => "tool_error",

8
router/src/server.rs
View File

@ -318,7 +318,10 @@ pub(crate) async fn generate_internal(
metrics::counter!("tgi_request_count").increment(1);
// Do not long ultra long inputs, like image payloads.
tracing::debug!("Input: {}", &req.inputs[..1000.min(req.inputs.len())]);
tracing::debug!(
"Input: {}",
&req.inputs.chars().take(1000).collect::<String>()
);
let compute_characters = req.inputs.chars().count();
let mut add_prompt = None;
@ -674,7 +677,7 @@ async fn generate_stream_internal(
// Check if generation reached the end
// Skip if we already sent an error
if !end_reached && !error {
let err = InferError::IncompleteGeneration;
let err = InferError::IncompleteGenerationStream;
metrics::counter!("tgi_request_failure", "err" => "incomplete").increment(1);
tracing::error!("{err}");
yield Ok(Event::from(err));
@ -2555,6 +2558,7 @@ impl From<InferError> for (StatusCode, Json<ErrorResponse>) {
InferError::Overloaded(_) => StatusCode::TOO_MANY_REQUESTS,
InferError::ValidationError(_) => StatusCode::UNPROCESSABLE_ENTITY,
InferError::IncompleteGeneration => StatusCode::INTERNAL_SERVER_ERROR,
InferError::IncompleteGenerationStream => StatusCode::INTERNAL_SERVER_ERROR,
InferError::TemplateError(_) => StatusCode::UNPROCESSABLE_ENTITY,
InferError::MissingTemplateVariable(_) => StatusCode::UNPROCESSABLE_ENTITY,
InferError::ToolError(_) => StatusCode::UNPROCESSABLE_ENTITY,

2
server/Makefile-flashinfer
View File

@ -1,2 +1,2 @@
install-flashinfer:
pip install flashinfer==0.1.5 -i https://flashinfer.ai/whl/cu124/torch2.4
pip install flashinfer==0.1.6 -i https://flashinfer.ai/whl/cu124/torch2.4

79
server/text_generation_server/models/flash_causal_lm.py
View File

@ -515,6 +515,7 @@ class FlashCausalLMBatch(Batch):
dtype: torch.dtype,
device: torch.device,
) -> "FlashCausalLMBatch":
assert len(pb.requests) > 0
batch_tokenized_inputs = cls.batch_tokenized_inputs(pb.requests, tokenizer)
return cls.from_tokenized(pb, tokenizer, batch_tokenized_inputs, dtype, device)
@ -640,6 +641,7 @@ class FlashCausalLMBatch(Batch):
adapter_segments = torch.tensor(
adapter_segments, dtype=torch.int32, device=device
)
# assert sum(len(b) for b in block_tables) == (block_tables_tensor != 0).sum()
return type(self)(
batch_id=self.batch_id,
@ -834,6 +836,8 @@ class FlashCausalLMBatch(Batch):
start_slots = torch.concat(start_slots)
# assert sum(len(b) for b in block_tables) == (block_tables_tensor != 0).sum()
next_token_chooser = HeterogeneousNextTokenChooser.from_pb(
next_token_chooser_parameters,
dtype=batches[0].next_token_chooser.dtype,
@ -1150,27 +1154,6 @@ class FlashCausalLM(Model):
input_lengths=input_lengths,
prefix_lens=prefix_lengths,
)
self.cuda_graphs[bs] = {
"input_ids": input_ids,
"position_ids": position_ids,
"kv_cache": self.kv_cache,
"block_tables": block_tables,
"slots": slots,
"input_lengths": input_lengths_tensor,
"prefix_lengths": prefix_lengths_tensor,
}
seqlen = Seqlen(
input_lengths=input_lengths_tensor,
prefix_lengths=prefix_lengths_tensor,
cu_seqlen_q=None,
max_q=1,
max_k=max_s,
)
graph = torch.cuda.CUDAGraph()
self.cuda_graphs[bs]["graph"] = graph
if ATTENTION == "flashinfer":
from text_generation_server.layers.attention.flashinfer import (
create_decode_state_cuda_graphs,
)
@ -1187,21 +1170,38 @@ class FlashCausalLM(Model):
num_heads=self.num_heads,
num_kv_heads=self.num_kv_heads,
)
self.cuda_graphs[bs]["state"] = state
else:
state = None
graph = torch.cuda.CUDAGraph()
self.cuda_graphs[bs] = {
"input_ids": input_ids,
"position_ids": position_ids,
"kv_cache": self.kv_cache,
"block_tables": block_tables,
"slots": slots,
"input_lengths": input_lengths_tensor,
"prefix_lengths": prefix_lengths_tensor,
"state": state,
"graph": graph,
}
torch.cuda.synchronize()
# Run once outside to warmup
with self._forward_context(
block_tables=block_tables,
cu_seqlen_prefill=None,
input_lengths=input_lengths,
input_lengths_tensor=input_lengths_tensor,
state=state,
prefix_lens=prefix_lengths,
prefix_lens_tensor=prefix_lengths_tensor,
):
seqlen = Seqlen(
input_lengths=input_lengths_tensor,
prefix_lengths=prefix_lengths_tensor,
cu_seqlen_q=None,
max_q=1,
max_k=max_s,
)
self.model.forward(
input_ids=input_ids,
position_ids=position_ids,
@ -1214,6 +1214,7 @@ class FlashCausalLM(Model):
prefill_cache_indices=None,
lm_head_indices=None,
)
del seqlen
torch.cuda.synchronize()
@ -1479,9 +1480,7 @@ class FlashCausalLM(Model):
with self._forward_context(
block_tables=block_tables,
cu_seqlen_prefill=cu_seqlen_prefill,
input_lengths=batch.input_lengths,
input_lengths_tensor=input_lengths + prefix_lens_tensor,
prefix_lens=batch.prefix_lens,
input_lengths_tensor=input_lengths,
prefix_lens_tensor=prefix_lens_tensor,
):
max_k = (input_lengths + prefix_lens_tensor).max().item()
@ -1519,26 +1518,28 @@ class FlashCausalLM(Model):
input_lengths=batch.input_lengths,
prefix_lens=batch.prefix_lens,
)
# assert block_tables.shape[0] >= slots.shape[0]
cuda_graph["block_tables"][: block_tables.shape[0]] = block_tables
else:
cuda_graph["block_tables"][
: block_tables.shape[0], : block_tables.shape[1]
] = block_tables
cuda_graph["slots"].fill_(-1)
# XXX: This is working only because block 0 is reserved for the healthcheck
# so it doesn't matter if we override it with bogus values.
cuda_graph["slots"].fill_(0)
cuda_graph["slots"][: slots.shape[0]] = slots
cuda_graph["input_lengths"].zero_()
cuda_graph["input_lengths"][: input_lengths.shape[0]] = (
input_lengths + prefix_lens_tensor
)
cuda_graph["input_lengths"][: input_lengths.shape[0]] = input_lengths
cuda_graph["prefix_lengths"].zero_()
cuda_graph["prefix_lengths"][: prefix_lens_tensor.shape[0]] = prefix_lens_tensor
with self._forward_context(
block_tables=cuda_graph["block_tables"],
cu_seqlen_prefill=None,
input_lengths=batch.input_lengths,
input_lengths_tensor=cuda_graph["input_lengths"],
prefix_lens=batch.prefix_lens,
prefix_lens_tensor=prefix_lens_tensor,
state=cuda_graph.get("state"),
prefix_lens_tensor=cuda_graph["prefix_lengths"],
state=cuda_graph["state"],
):
# Replay the graph
cuda_graph["graph"].replay()
@ -1767,7 +1768,7 @@ class FlashCausalLM(Model):
left = 0
if n_accepted_ids > 1:
log_master(logger.debug, f"Speculated ids {n_accepted_ids - 1}")
log_master(logger.debug, f"speculated ids {n_accepted_ids - 1}")
current_stopped = False
for j in range(index, index + n_accepted_ids):
@ -1922,9 +1923,7 @@ class FlashCausalLM(Model):
*,
block_tables: torch.Tensor,
cu_seqlen_prefill: Optional[torch.Tensor],
input_lengths: List[int],
input_lengths_tensor: torch.Tensor,
prefix_lens: List[int],
prefix_lens_tensor: torch.Tensor,
state: Optional[Any] = None,
) -> ContextManager:
@ -1950,7 +1949,7 @@ class FlashCausalLM(Model):
# ),
block_tables=block_tables,
cu_seqlens=cu_seqlen_prefill,
input_lengths=input_lengths_tensor,
input_lengths=input_lengths_tensor + prefix_lens_tensor,
num_heads=self.num_heads,
num_kv_heads=self.num_kv_heads,
head_size=self.head_size,
@ -1960,7 +1959,7 @@ class FlashCausalLM(Model):
assert input_lengths_tensor is not None
return use_decode_state(
state=state if state is not None else self.decode_state,
input_lengths=input_lengths_tensor,
input_lengths=input_lengths_tensor + prefix_lens_tensor,
block_tables=block_tables,
num_heads=self.num_heads,
num_kv_heads=self.num_kv_heads,

2
server/text_generation_server/models/vlm_causal_lm.py
View File

@ -367,9 +367,7 @@ class VlmCausalLM(FlashCausalLM):
with self._forward_context(
block_tables=block_tables,
cu_seqlen_prefill=cu_seqlen_prefill,
input_lengths=batch.input_lengths,
input_lengths_tensor=input_lengths,
prefix_lens=batch.prefix_lens,
prefix_lens_tensor=prefix_lens_tensor,
):
max_k = (input_lengths + prefix_lens_tensor).max().item()