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Unverified Commit 31e2253a authored by OlivierDehaene's avatar OlivierDehaene Committed by GitHub
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feat(server): use latest flash attention commit (#543) 

@njhill FYI
parent e4b26aa1
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server/Makefile-flash-att
View file @ 31e2253a
flash_att_commit := 06ece1a1525ebcf4e183ac76b1e5108d2872f57f flash_att_commit := 3a9bfd076f98746c73362328958dbc68d145fbec
flash-attention: flash-attention:
# Clone flash attention # Clone flash attention
pip install packaging pip install packaging
git clone https://github.com/OlivierDehaene/flash-attention.git git clone https://github.com/HazyResearch/flash-attention.git
build-flash-attention: flash-attention build-flash-attention: flash-attention
cd flash-attention && git fetch && git checkout $(flash_att_commit) cd flash-attention && git fetch && git checkout $(flash_att_commit)
......
server/poetry.lock
View file @ 31e2253a
# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
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...@@ -23,138 +18,50 @@ dev = ["black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-buil ...@@ -23,138 +18,50 @@ dev = ["black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-buil
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optional = false optional = false
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...@@ -746,12 +401,9 @@ test = ["pytest-grpc"] ...@@ -746,12 +401,9 @@ test = ["pytest-grpc"]
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...@@ -768,12 +420,9 @@ test = ["responses (==0.22.0)"] ...@@ -768,12 +420,9 @@ test = ["responses (==0.22.0)"]
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...@@ -784,12 +433,9 @@ wrapt = ">=1.0.0,<2.0.0" ...@@ -784,12 +433,9 @@ wrapt = ">=1.0.0,<2.0.0"
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category = "main"
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...@@ -806,12 +452,9 @@ test = ["opentelemetry-instrumentation-grpc[instruments]", "opentelemetry-sdk (> ...@@ -806,12 +452,9 @@ test = ["opentelemetry-instrumentation-grpc[instruments]", "opentelemetry-sdk (>
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...@@ -820,12 +463,9 @@ protobuf = ">=3.19,<5.0" ...@@ -820,12 +463,9 @@ protobuf = ">=3.19,<5.0"
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description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
optional = false
python-versions = ">=3.6"
files = [
{file = "typer-0.6.1-py3-none-any.whl", hash = "sha256:54b19e5df18654070a82f8c2aa1da456a4ac16a2a83e6dcd9f170e291c56338e"}, {file = "typer-0.6.1-py3-none-any.whl", hash = "sha256:54b19e5df18654070a82f8c2aa1da456a4ac16a2a83e6dcd9f170e291c56338e"},
{file = "typer-0.6.1.tar.gz", hash = "sha256:2d5720a5e63f73eaf31edaa15f6ab87f35f0690f8ca233017d7d23d743a91d73"}, {file = "typer-0.6.1.tar.gz", hash = "sha256:2d5720a5e63f73eaf31edaa15f6ab87f35f0690f8ca233017d7d23d743a91d73"},
] ]
typing-extensions = [
[package.dependencies] {file = "typing_extensions-4.7.1-py3-none-any.whl", hash = "sha256:440d5dd3af93b060174bf433bccd69b0babc3b15b1a8dca43789fd7f61514b36"},
click = ">=7.1.1,<9.0.0" {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"},
[package.extras]
all = ["colorama (>=0.4.3,<0.5.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2.17.0,<3.0.0)"]
doc = ["mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)"]
test = ["black (>=22.3.0,<23.0.0)", "coverage (>=5.2,<6.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.910)", "pytest (>=4.4.0,<5.4.0)", "pytest-cov (>=2.10.0,<3.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "pytest-xdist (>=1.32.0,<2.0.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
[[package]]
name = "typing-extensions"
version = "4.6.3"
description = "Backported and Experimental Type Hints for Python 3.7+"
optional = false
python-versions = ">=3.7"
files = [
{file = "typing_extensions-4.6.3-py3-none-any.whl", hash = "sha256:88a4153d8505aabbb4e13aacb7c486c2b4a33ca3b3f807914a9b4c844c471c26"},
{file = "typing_extensions-4.6.3.tar.gz", hash = "sha256:d91d5919357fe7f681a9f2b5b4cb2a5f1ef0a1e9f59c4d8ff0d3491e05c0ffd5"},
] ]
urllib3 = [
[[package]]
name = "urllib3"
version = "2.0.3"
description = "HTTP library with thread-safe connection pooling, file post, and more."
optional = false
python-versions = ">=3.7"
files = [
{file = "urllib3-2.0.3-py3-none-any.whl", hash = "sha256:48e7fafa40319d358848e1bc6809b208340fafe2096f1725d05d67443d0483d1"}, {file = "urllib3-2.0.3-py3-none-any.whl", hash = "sha256:48e7fafa40319d358848e1bc6809b208340fafe2096f1725d05d67443d0483d1"},
{file = "urllib3-2.0.3.tar.gz", hash = "sha256:bee28b5e56addb8226c96f7f13ac28cb4c301dd5ea8a6ca179c0b9835e032825"}, {file = "urllib3-2.0.3.tar.gz", hash = "sha256:bee28b5e56addb8226c96f7f13ac28cb4c301dd5ea8a6ca179c0b9835e032825"},
] ]
win32-setctime = [
[package.extras]
brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.1.0)", "urllib3-secure-extra"]
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["zstandard (>=0.18.0)"]
[[package]]
name = "win32-setctime"
version = "1.1.0"
description = "A small Python utility to set file creation time on Windows"
optional = false
python-versions = ">=3.5"
files = [
{file = "win32_setctime-1.1.0-py3-none-any.whl", hash = "sha256:231db239e959c2fe7eb1d7dc129f11172354f98361c4fa2d6d2d7e278baa8aad"}, {file = "win32_setctime-1.1.0-py3-none-any.whl", hash = "sha256:231db239e959c2fe7eb1d7dc129f11172354f98361c4fa2d6d2d7e278baa8aad"},
{file = "win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"}, {file = "win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"},
] ]
wrapt = [
[package.extras]
dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
[[package]]
name = "wrapt"
version = "1.15.0"
description = "Module for decorators, wrappers and monkey patching."
optional = false
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
files = [
{file = "wrapt-1.15.0-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:ca1cccf838cd28d5a0883b342474c630ac48cac5df0ee6eacc9c7290f76b11c1"}, {file = "wrapt-1.15.0-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:ca1cccf838cd28d5a0883b342474c630ac48cac5df0ee6eacc9c7290f76b11c1"},
{file = "wrapt-1.15.0-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:e826aadda3cae59295b95343db8f3d965fb31059da7de01ee8d1c40a60398b29"}, {file = "wrapt-1.15.0-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:e826aadda3cae59295b95343db8f3d965fb31059da7de01ee8d1c40a60398b29"},
{file = "wrapt-1.15.0-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:5fc8e02f5984a55d2c653f5fea93531e9836abbd84342c1d1e17abc4a15084c2"}, {file = "wrapt-1.15.0-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:5fc8e02f5984a55d2c653f5fea93531e9836abbd84342c1d1e17abc4a15084c2"},
...@@ -1589,12 +1653,3 @@ files = [ ...@@ -1589,12 +1653,3 @@ files = [
{file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"}, {file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"},
{file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"}, {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
] ]
[extras]
accelerate = ["accelerate"]
bnb = ["bitsandbytes"]
[metadata]
lock-version = "2.0"
python-versions = "^3.9"
content-hash = "3174a211d30bed5990ed5f8418416c951bb6c585153fb51b62809baa89ef07d0"
server/pyproject.toml
View file @ 31e2253a
...@@ -26,7 +26,7 @@ hf-transfer = "^0.1.2" ...@@ -26,7 +26,7 @@ hf-transfer = "^0.1.2"
sentencepiece = "^0.1.97" sentencepiece = "^0.1.97"
tokenizers = "0.13.3" tokenizers = "0.13.3"
huggingface-hub = "^0.14.1" huggingface-hub = "^0.14.1"
transformers = "^4.29.2" transformers = "4.29.2"
einops = "^0.6.1" einops = "^0.6.1"
[tool.poetry.extras] [tool.poetry.extras]
......
server/requirements.txt
View file @ 31e2253a
backoff==2.2.1 ; python_version >= "3.9" and python_version < "4.0" backoff==2.2.1 ; python_version >= "3.9" and python_version < "4.0"
bitsandbytes==0.38.1 ; python_version >= "3.9" and python_version < "4.0"
certifi==2023.5.7 ; python_version >= "3.9" and python_version < "4.0" certifi==2023.5.7 ; python_version >= "3.9" and python_version < "4.0"
charset-normalizer==3.1.0 ; python_version >= "3.9" and python_version < "4.0" charset-normalizer==3.1.0 ; python_version >= "3.9" and python_version < "4.0"
click==8.1.3 ; python_version >= "3.9" and python_version < "4.0" click==8.1.3 ; python_version >= "3.9" and python_version < "4.0"
colorama==0.4.6 ; python_version >= "3.9" and python_version < "4.0" and (sys_platform == "win32" or platform_system == "Windows") colorama==0.4.6 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32" or python_version >= "3.9" and python_version < "4.0" and platform_system == "Windows"
deprecated==1.2.14 ; python_version >= "3.9" and python_version < "4.0" deprecated==1.2.14 ; python_version >= "3.9" and python_version < "4.0"
einops==0.6.1 ; python_version >= "3.9" and python_version < "4.0" einops==0.6.1 ; python_version >= "3.9" and python_version < "4.0"
filelock==3.12.2 ; python_version >= "3.9" and python_version < "4.0" filelock==3.12.2 ; python_version >= "3.9" and python_version < "4.0"
fsspec==2023.6.0 ; python_version >= "3.9" and python_version < "4.0" fsspec==2023.6.0 ; python_version >= "3.9" and python_version < "4.0"
googleapis-common-protos==1.59.1 ; python_version >= "3.9" and python_version < "4.0" googleapis-common-protos==1.59.1 ; python_version >= "3.9" and python_version < "4.0"
grpc-interceptor==0.15.2 ; python_version >= "3.9" and python_version < "4.0" grpc-interceptor==0.15.2 ; python_version >= "3.9" and python_version < "4.0"
grpcio-reflection==1.54.2 ; python_version >= "3.9" and python_version < "4.0" grpcio-reflection==1.56.0 ; python_version >= "3.9" and python_version < "4.0"
grpcio-status==1.54.2 ; python_version >= "3.9" and python_version < "4.0" grpcio-status==1.56.0 ; python_version >= "3.9" and python_version < "4.0"
grpcio==1.54.2 ; python_version >= "3.9" and python_version < "4.0" grpcio==1.56.0 ; python_version >= "3.9" and python_version < "4.0"
hf-transfer==0.1.3 ; python_version >= "3.9" and python_version < "4.0" hf-transfer==0.1.3 ; python_version >= "3.9" and python_version < "4.0"
huggingface-hub==0.14.1 ; python_version >= "3.9" and python_version < "4.0" huggingface-hub==0.14.1 ; python_version >= "3.9" and python_version < "4.0"
idna==3.4 ; python_version >= "3.9" and python_version < "4.0" idna==3.4 ; python_version >= "3.9" and python_version < "4.0"
loguru==0.6.0 ; python_version >= "3.9" and python_version < "4.0" loguru==0.6.0 ; python_version >= "3.9" and python_version < "4.0"
numpy==1.24.3 ; python_version >= "3.9" and python_version < "4.0" numpy==1.25.0 ; python_version >= "3.9" and python_version < "4.0"
opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
opentelemetry-exporter-otlp-proto-grpc==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-exporter-otlp-proto-grpc==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
opentelemetry-exporter-otlp-proto-http==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-exporter-otlp-proto-http==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
...@@ -27,18 +28,18 @@ opentelemetry-proto==1.15.0 ; python_version >= "3.9" and python_version < "4.0" ...@@ -27,18 +28,18 @@ opentelemetry-proto==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
opentelemetry-sdk==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-sdk==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
opentelemetry-semantic-conventions==0.36b0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-semantic-conventions==0.36b0 ; python_version >= "3.9" and python_version < "4.0"
packaging==23.1 ; python_version >= "3.9" and python_version < "4.0" packaging==23.1 ; python_version >= "3.9" and python_version < "4.0"
protobuf==4.23.2 ; python_version >= "3.9" and python_version < "4.0" protobuf==4.23.3 ; python_version >= "3.9" and python_version < "4.0"
pyyaml==6.0 ; python_version >= "3.9" and python_version < "4.0" pyyaml==6.0 ; python_version >= "3.9" and python_version < "4.0"
regex==2023.6.3 ; python_version >= "3.9" and python_version < "4.0" regex==2023.6.3 ; python_version >= "3.9" and python_version < "4.0"
requests==2.31.0 ; python_version >= "3.9" and python_version < "4.0" requests==2.31.0 ; python_version >= "3.9" and python_version < "4.0"
safetensors==0.3.1 ; python_version >= "3.9" and python_version < "4.0" safetensors==0.3.1 ; python_version >= "3.9" and python_version < "4.0"
sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "4.0" sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "4.0"
setuptools==67.8.0 ; python_version >= "3.9" and python_version < "4.0" setuptools==68.0.0 ; python_version >= "3.9" and python_version < "4.0"
tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "4.0" tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "4.0"
tqdm==4.65.0 ; python_version >= "3.9" and python_version < "4.0" tqdm==4.65.0 ; python_version >= "3.9" and python_version < "4.0"
transformers==4.30.2 ; python_version >= "3.9" and python_version < "4.0" transformers==4.29.2 ; python_version >= "3.9" and python_version < "4.0"
typer==0.6.1 ; python_version >= "3.9" and python_version < "4.0" typer==0.6.1 ; python_version >= "3.9" and python_version < "4.0"
typing-extensions==4.6.3 ; python_version >= "3.9" and python_version < "4.0" typing-extensions==4.7.1 ; python_version >= "3.9" and python_version < "4.0"
urllib3==2.0.3 ; python_version >= "3.9" and python_version < "4.0" urllib3==2.0.3 ; python_version >= "3.9" and python_version < "4.0"
win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32" win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32"
wrapt==1.15.0 ; python_version >= "3.9" and python_version < "4.0" wrapt==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
server/text_generation_server/models/custom_modeling/flash_llama_modeling.py
View file @ 31e2253a
...@@ -135,8 +135,7 @@ class FlashLlamaAttention(torch.nn.Module): ...@@ -135,8 +135,7 @@ class FlashLlamaAttention(torch.nn.Module):
hidden_states, hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -158,17 +157,15 @@ class FlashLlamaAttention(torch.nn.Module): ...@@ -158,17 +157,15 @@ class FlashLlamaAttention(torch.nn.Module):
attn_output = torch.empty_like(qkv[:, 0]) attn_output = torch.empty_like(qkv[:, 0])
# Prefill # Prefill
if start_seq_prefill is not None: if cu_seqlen_prefill is not None:
# flash attention # flash attention
flash_attn_cuda.fwd( flash_attn_cuda.fwd(
qkv[:, 0], qkv[:, 0],
qkv[:, 1], qkv[:, 1],
qkv[:, 2], qkv[:, 2],
attn_output, attn_output,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill, cu_seqlen_prefill,
start_seq_prefill,
end_seq_prefill,
max_s, max_s,
max_s, max_s,
0.0, 0.0,
...@@ -261,8 +258,7 @@ class FlashLlamaLayer(nn.Module): ...@@ -261,8 +258,7 @@ class FlashLlamaLayer(nn.Module):
residual, residual,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -276,8 +272,7 @@ class FlashLlamaLayer(nn.Module): ...@@ -276,8 +272,7 @@ class FlashLlamaLayer(nn.Module):
normed_hidden_states, normed_hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -329,8 +324,7 @@ class FlashLlamaModel(torch.nn.Module): ...@@ -329,8 +324,7 @@ class FlashLlamaModel(torch.nn.Module):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
kv_cache: List[Tuple[torch.Tensor, torch.Tensor]], kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
...@@ -352,8 +346,7 @@ class FlashLlamaModel(torch.nn.Module): ...@@ -352,8 +346,7 @@ class FlashLlamaModel(torch.nn.Module):
residual, residual,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache[i], kv_cache[i],
block_tables, block_tables,
slots, slots,
...@@ -381,8 +374,7 @@ class FlashLlamaForCausalLM(torch.nn.Module): ...@@ -381,8 +374,7 @@ class FlashLlamaForCausalLM(torch.nn.Module):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
kv_cache: List[Tuple[torch.Tensor, torch.Tensor]], kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
...@@ -393,8 +385,7 @@ class FlashLlamaForCausalLM(torch.nn.Module): ...@@ -393,8 +385,7 @@ class FlashLlamaForCausalLM(torch.nn.Module):
hidden_states = self.model( hidden_states = self.model(
input_ids, input_ids,
position_ids, position_ids,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
......
server/text_generation_server/models/custom_modeling/flash_neox_modeling.py
View file @ 31e2253a
...@@ -123,8 +123,7 @@ class FlashNeoxAttention(torch.nn.Module): ...@@ -123,8 +123,7 @@ class FlashNeoxAttention(torch.nn.Module):
hidden_states, hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -146,17 +145,15 @@ class FlashNeoxAttention(torch.nn.Module): ...@@ -146,17 +145,15 @@ class FlashNeoxAttention(torch.nn.Module):
attn_output = torch.empty_like(qkv[:, 0]) attn_output = torch.empty_like(qkv[:, 0])
# Prefill # Prefill
if start_seq_prefill is not None: if cu_seqlen_prefill is not None:
# flash attention # flash attention
flash_attn_cuda.fwd( flash_attn_cuda.fwd(
qkv[:, 0], qkv[:, 0],
qkv[:, 1], qkv[:, 1],
qkv[:, 2], qkv[:, 2],
attn_output, attn_output,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill, cu_seqlen_prefill,
start_seq_prefill,
end_seq_prefill,
max_s, max_s,
max_s, max_s,
0.0, 0.0,
...@@ -246,8 +243,7 @@ class FlashNeoXLayer(nn.Module): ...@@ -246,8 +243,7 @@ class FlashNeoXLayer(nn.Module):
residual, residual,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -261,8 +257,7 @@ class FlashNeoXLayer(nn.Module): ...@@ -261,8 +257,7 @@ class FlashNeoXLayer(nn.Module):
ln1_hidden_states, ln1_hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -286,8 +281,7 @@ class FlashNeoXLayer(nn.Module): ...@@ -286,8 +281,7 @@ class FlashNeoXLayer(nn.Module):
hidden_states, hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -341,8 +335,7 @@ class FlashGPTNeoXModel(FlashGPTNeoXPreTrainedModel): ...@@ -341,8 +335,7 @@ class FlashGPTNeoXModel(FlashGPTNeoXPreTrainedModel):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
kv_cache: List[Tuple[torch.Tensor, torch.Tensor]], kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
...@@ -364,8 +357,7 @@ class FlashGPTNeoXModel(FlashGPTNeoXPreTrainedModel): ...@@ -364,8 +357,7 @@ class FlashGPTNeoXModel(FlashGPTNeoXPreTrainedModel):
residual, residual,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache[i], kv_cache[i],
block_tables, block_tables,
slots, slots,
...@@ -391,8 +383,7 @@ class FlashGPTNeoXForCausalLM(FlashGPTNeoXPreTrainedModel): ...@@ -391,8 +383,7 @@ class FlashGPTNeoXForCausalLM(FlashGPTNeoXPreTrainedModel):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
kv_cache: List[Tuple[torch.Tensor, torch.Tensor]], kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
...@@ -403,8 +394,7 @@ class FlashGPTNeoXForCausalLM(FlashGPTNeoXPreTrainedModel): ...@@ -403,8 +394,7 @@ class FlashGPTNeoXForCausalLM(FlashGPTNeoXPreTrainedModel):
hidden_states = self.gpt_neox( hidden_states = self.gpt_neox(
input_ids, input_ids,
position_ids, position_ids,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
......
server/text_generation_server/models/custom_modeling/flash_rw_modeling.py
View file @ 31e2253a
...@@ -144,8 +144,7 @@ class FlashRWAttention(torch.nn.Module): ...@@ -144,8 +144,7 @@ class FlashRWAttention(torch.nn.Module):
hidden_states, hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -176,7 +175,7 @@ class FlashRWAttention(torch.nn.Module): ...@@ -176,7 +175,7 @@ class FlashRWAttention(torch.nn.Module):
attn_output = torch.empty_like(query) attn_output = torch.empty_like(query)
# Prefill # Prefill
if start_seq_prefill is not None: if cu_seqlen_prefill is not None:
if self.num_heads_kv == 1: if self.num_heads_kv == 1:
# Expand to query shape # Expand to query shape
kv = kv.expand(-1, 2, self.num_heads, self.head_size) kv = kv.expand(-1, 2, self.num_heads, self.head_size)
...@@ -187,10 +186,8 @@ class FlashRWAttention(torch.nn.Module): ...@@ -187,10 +186,8 @@ class FlashRWAttention(torch.nn.Module):
torch.select(kv, dim=1, index=0), torch.select(kv, dim=1, index=0),
torch.select(kv, dim=1, index=1), torch.select(kv, dim=1, index=1),
attn_output, attn_output,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill, cu_seqlen_prefill,
start_seq_prefill,
end_seq_prefill,
max_s, max_s,
max_s, max_s,
0.0, 0.0,
...@@ -276,8 +273,7 @@ class FlashRWLargeAttention(torch.nn.Module): ...@@ -276,8 +273,7 @@ class FlashRWLargeAttention(torch.nn.Module):
hidden_states, hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -311,7 +307,7 @@ class FlashRWLargeAttention(torch.nn.Module): ...@@ -311,7 +307,7 @@ class FlashRWLargeAttention(torch.nn.Module):
attn_output = torch.empty_like(query) attn_output = torch.empty_like(query)
# Prefill # Prefill
if start_seq_prefill is not None: if cu_seqlen_prefill is not None:
# Expand to query shape # Expand to query shape
kv = ( kv = (
kv.unsqueeze(2) kv.unsqueeze(2)
...@@ -325,10 +321,8 @@ class FlashRWLargeAttention(torch.nn.Module): ...@@ -325,10 +321,8 @@ class FlashRWLargeAttention(torch.nn.Module):
torch.select(kv, dim=2, index=0), torch.select(kv, dim=2, index=0),
torch.select(kv, dim=2, index=1), torch.select(kv, dim=2, index=1),
attn_output, attn_output,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill, cu_seqlen_prefill,
start_seq_prefill,
end_seq_prefill,
max_s, max_s,
max_s, max_s,
0.0, 0.0,
...@@ -428,8 +422,7 @@ class FlashRWLayer(nn.Module): ...@@ -428,8 +422,7 @@ class FlashRWLayer(nn.Module):
residual, residual,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -443,8 +436,7 @@ class FlashRWLayer(nn.Module): ...@@ -443,8 +436,7 @@ class FlashRWLayer(nn.Module):
ln_hidden_states, ln_hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -466,8 +458,7 @@ class FlashRWLayer(nn.Module): ...@@ -466,8 +458,7 @@ class FlashRWLayer(nn.Module):
hidden_states, hidden_states,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -516,8 +507,7 @@ class FlashRWLargeLayer(nn.Module): ...@@ -516,8 +507,7 @@ class FlashRWLargeLayer(nn.Module):
residual, residual,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -532,8 +522,7 @@ class FlashRWLargeLayer(nn.Module): ...@@ -532,8 +522,7 @@ class FlashRWLargeLayer(nn.Module):
ln_attn, ln_attn,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -597,8 +586,7 @@ class FlashRWModel(FlashRWPreTrainedModel): ...@@ -597,8 +586,7 @@ class FlashRWModel(FlashRWPreTrainedModel):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
kv_cache: List[Tuple[torch.Tensor, torch.Tensor]], kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
...@@ -620,8 +608,7 @@ class FlashRWModel(FlashRWPreTrainedModel): ...@@ -620,8 +608,7 @@ class FlashRWModel(FlashRWPreTrainedModel):
residual, residual,
cos, cos,
sin, sin,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache[i], kv_cache[i],
block_tables, block_tables,
slots, slots,
...@@ -648,8 +635,7 @@ class FlashRWForCausalLM(FlashRWPreTrainedModel): ...@@ -648,8 +635,7 @@ class FlashRWForCausalLM(FlashRWPreTrainedModel):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
kv_cache: List[Tuple[torch.Tensor, torch.Tensor]], kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
...@@ -660,8 +646,7 @@ class FlashRWForCausalLM(FlashRWPreTrainedModel): ...@@ -660,8 +646,7 @@ class FlashRWForCausalLM(FlashRWPreTrainedModel):
hidden_states = self.transformer( hidden_states = self.transformer(
input_ids, input_ids,
position_ids, position_ids,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
......
server/text_generation_server/models/custom_modeling/flash_santacoder_modeling.py
View file @ 31e2253a
...@@ -232,8 +232,7 @@ class FlashMQAttention(torch.nn.Module): ...@@ -232,8 +232,7 @@ class FlashMQAttention(torch.nn.Module):
def forward( def forward(
self, self,
hidden_states, hidden_states,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -259,7 +258,7 @@ class FlashMQAttention(torch.nn.Module): ...@@ -259,7 +258,7 @@ class FlashMQAttention(torch.nn.Module):
attn_output = torch.empty_like(query) attn_output = torch.empty_like(query)
# Prefill # Prefill
if start_seq_prefill is not None: if cu_seqlen_prefill is not None:
# Expand from 1 to num_heads # Expand from 1 to num_heads
key_value = key_value.expand(-1, 2, self.num_heads, self.head_size) key_value = key_value.expand(-1, 2, self.num_heads, self.head_size)
...@@ -269,10 +268,8 @@ class FlashMQAttention(torch.nn.Module): ...@@ -269,10 +268,8 @@ class FlashMQAttention(torch.nn.Module):
torch.select(key_value, dim=1, index=0), torch.select(key_value, dim=1, index=0),
torch.select(key_value, dim=1, index=1), torch.select(key_value, dim=1, index=1),
attn_output, attn_output,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill, cu_seqlen_prefill,
start_seq_prefill,
end_seq_prefill,
max_s, max_s,
max_s, max_s,
0.0, 0.0,
...@@ -357,8 +354,7 @@ class Block(nn.Module): ...@@ -357,8 +354,7 @@ class Block(nn.Module):
self, self,
hidden_states, hidden_states,
residual, residual,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -369,8 +365,7 @@ class Block(nn.Module): ...@@ -369,8 +365,7 @@ class Block(nn.Module):
hidden_states = self.attn( hidden_states = self.attn(
hidden_states, hidden_states,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
...@@ -423,8 +418,7 @@ class FlashSantacoderModel(nn.Module): ...@@ -423,8 +418,7 @@ class FlashSantacoderModel(nn.Module):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
kv_cache: List[Tuple[torch.Tensor, torch.Tensor]], kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
...@@ -441,8 +435,7 @@ class FlashSantacoderModel(nn.Module): ...@@ -441,8 +435,7 @@ class FlashSantacoderModel(nn.Module):
hidden_states, residual = layer( hidden_states, residual = layer(
hidden_states, hidden_states,
residual, residual,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache[i], kv_cache[i],
block_tables, block_tables,
slots, slots,
...@@ -467,8 +460,7 @@ class FlashSantacoderForCausalLM(nn.Module): ...@@ -467,8 +460,7 @@ class FlashSantacoderForCausalLM(nn.Module):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
kv_cache: List[Tuple[torch.Tensor, torch.Tensor]], kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
...@@ -479,8 +471,7 @@ class FlashSantacoderForCausalLM(nn.Module): ...@@ -479,8 +471,7 @@ class FlashSantacoderForCausalLM(nn.Module):
hidden_states = self.transformer( hidden_states = self.transformer(
input_ids, input_ids,
position_ids, position_ids,
start_seq_prefill, cu_seqlen_prefill,
end_seq_prefill,
kv_cache, kv_cache,
block_tables, block_tables,
slots, slots,
......
server/text_generation_server/models/flash_causal_lm.py
View file @ 31e2253a
...@@ -121,10 +121,10 @@ class FlashCausalLMBatch(Batch): ...@@ -121,10 +121,10 @@ class FlashCausalLMBatch(Batch):
input_ids: torch.Tensor input_ids: torch.Tensor
position_ids: torch.Tensor position_ids: torch.Tensor
# tensor of length b holding starting offset of each sequence, only used in prefill # Flash Attention values
start_seq_prefill: Optional[torch.Tensor]
# tensor of length b holding ending offset of each sequence, only used in prefill # tensor of length b containing the cumulative sequence lengths of the sequences in the batch, only used in prefill
end_seq_prefill: Optional[torch.Tensor] cu_seqlen_prefill: Optional[torch.Tensor]
# Paged Attention values # Paged Attention values
...@@ -197,8 +197,7 @@ class FlashCausalLMBatch(Batch): ...@@ -197,8 +197,7 @@ class FlashCausalLMBatch(Batch):
)["input_ids"] )["input_ids"]
position_ids = [] position_ids = []
start_seq_prefill = [] cu_seqlen_prefill = [0]
end_seq_prefill = []
needed_blocks_slots = [] needed_blocks_slots = []
start_slots = [] start_slots = []
slot_indices = [] slot_indices = []
...@@ -250,8 +249,7 @@ class FlashCausalLMBatch(Batch): ...@@ -250,8 +249,7 @@ class FlashCausalLMBatch(Batch):
position_ids.append(request_position_ids) position_ids.append(request_position_ids)
# Add cumulative lengths of all previous inputs # Add cumulative lengths of all previous inputs
start_seq_prefill.append(cumulative_length) cu_seqlen_prefill.append(cumulative_length + input_length)
end_seq_prefill.append(cumulative_length + input_length)
next_token_chooser_parameters.append(r.parameters) next_token_chooser_parameters.append(r.parameters)
...@@ -329,11 +327,8 @@ class FlashCausalLMBatch(Batch): ...@@ -329,11 +327,8 @@ class FlashCausalLMBatch(Batch):
position_ids = position_ids[0] position_ids = position_ids[0]
slot_indices = slot_indices[0] slot_indices = slot_indices[0]
start_seq_prefill = torch.tensor( cu_seqlen_prefill = torch.tensor(
start_seq_prefill, device=device, dtype=torch.int32 cu_seqlen_prefill, device=device, dtype=torch.int32
)
end_seq_prefill = torch.tensor(
end_seq_prefill, device=device, dtype=torch.int32
) )
position_ids = position_ids.to(device) position_ids = position_ids.to(device)
...@@ -345,9 +340,9 @@ class FlashCausalLMBatch(Batch): ...@@ -345,9 +340,9 @@ class FlashCausalLMBatch(Batch):
if all_prefill_logprobs: if all_prefill_logprobs:
prefill_head_indices = None prefill_head_indices = None
prefill_next_token_indices = end_seq_prefill - 1 prefill_next_token_indices = cu_seqlen_prefill[1:] - 1
elif no_prefill_logprobs: elif no_prefill_logprobs:
prefill_head_indices = end_seq_prefill - 1 prefill_head_indices = cu_seqlen_prefill[1:] - 1
prefill_next_token_indices = None prefill_next_token_indices = None
else: else:
prefill_head_indices = torch.tensor( prefill_head_indices = torch.tensor(
...@@ -363,8 +358,7 @@ class FlashCausalLMBatch(Batch): ...@@ -363,8 +358,7 @@ class FlashCausalLMBatch(Batch):
requests_idx_mapping=requests_idx_mapping, requests_idx_mapping=requests_idx_mapping,
input_ids=input_ids, input_ids=input_ids,
position_ids=position_ids, position_ids=position_ids,
start_seq_prefill=start_seq_prefill, cu_seqlen_prefill=cu_seqlen_prefill,
end_seq_prefill=end_seq_prefill,
start_slots=start_slots, start_slots=start_slots,
slot_indices=slot_indices, slot_indices=slot_indices,
needed_blocks_slots=needed_blocks_slots, needed_blocks_slots=needed_blocks_slots,
...@@ -504,8 +498,7 @@ class FlashCausalLMBatch(Batch): ...@@ -504,8 +498,7 @@ class FlashCausalLMBatch(Batch):
requests_idx_mapping=requests_idx_mapping, requests_idx_mapping=requests_idx_mapping,
input_ids=input_ids, input_ids=input_ids,
position_ids=position_ids, position_ids=position_ids,
start_seq_prefill=None, cu_seqlen_prefill=None,
end_seq_prefill=None,
start_slots=start_slots, start_slots=start_slots,
slot_indices=slot_indices, slot_indices=slot_indices,
needed_blocks_slots=None, needed_blocks_slots=None,
...@@ -652,8 +645,7 @@ class FlashCausalLMBatch(Batch): ...@@ -652,8 +645,7 @@ class FlashCausalLMBatch(Batch):
requests_idx_mapping=requests_idx_mapping, requests_idx_mapping=requests_idx_mapping,
input_ids=input_ids, input_ids=input_ids,
position_ids=position_ids, position_ids=position_ids,
start_seq_prefill=None, cu_seqlen_prefill=None,
end_seq_prefill=None,
start_slots=start_slots, start_slots=start_slots,
slot_indices=slot_indices, slot_indices=slot_indices,
needed_blocks_slots=None, needed_blocks_slots=None,
...@@ -750,8 +742,7 @@ class FlashCausalLM(Model): ...@@ -750,8 +742,7 @@ class FlashCausalLM(Model):
self, self,
input_ids: torch.Tensor, input_ids: torch.Tensor,
position_ids: torch.Tensor, position_ids: torch.Tensor,
start_seq_prefill: Optional[torch.Tensor], cu_seqlen_prefill: Optional[torch.Tensor],
end_seq_prefill: Optional[torch.Tensor],
block_tables: torch.Tensor, block_tables: torch.Tensor,
slots: torch.Tensor, slots: torch.Tensor,
input_lengths: torch.Tensor, input_lengths: torch.Tensor,
...@@ -764,8 +755,7 @@ class FlashCausalLM(Model): ...@@ -764,8 +755,7 @@ class FlashCausalLM(Model):
return self.model.forward( return self.model.forward(
input_ids=input_ids, input_ids=input_ids,
position_ids=position_ids, position_ids=position_ids,
start_seq_prefill=start_seq_prefill, cu_seqlen_prefill=cu_seqlen_prefill,
end_seq_prefill=end_seq_prefill,
kv_cache=CACHE_MANAGER.kv_cache, kv_cache=CACHE_MANAGER.kv_cache,
block_tables=block_tables, block_tables=block_tables,
slots=slots, slots=slots,
...@@ -778,7 +768,7 @@ class FlashCausalLM(Model): ...@@ -778,7 +768,7 @@ class FlashCausalLM(Model):
def generate_token( def generate_token(
self, batch: FlashCausalLMBatch self, batch: FlashCausalLMBatch
) -> Tuple[List[Generation], Optional[FlashCausalLMBatch]]: ) -> Tuple[List[Generation], Optional[FlashCausalLMBatch]]:
prefill = batch.start_seq_prefill is not None prefill = batch.cu_seqlen_prefill is not None
prefill_logprobs = batch.prefill_next_token_indices is not None prefill_logprobs = batch.prefill_next_token_indices is not None
if batch.needed_blocks_slots: if batch.needed_blocks_slots:
...@@ -788,8 +778,7 @@ class FlashCausalLM(Model): ...@@ -788,8 +778,7 @@ class FlashCausalLM(Model):
out = self.forward( out = self.forward(
batch.input_ids, batch.input_ids,
batch.position_ids, batch.position_ids,
batch.start_seq_prefill, batch.cu_seqlen_prefill,
batch.end_seq_prefill,
batch.block_tables_tensor, batch.block_tables_tensor,
batch.slots[batch.slot_indices], batch.slots[batch.slot_indices],
batch.input_lengths_tensor, batch.input_lengths_tensor,
...@@ -815,10 +804,9 @@ class FlashCausalLM(Model): ...@@ -815,10 +804,9 @@ class FlashCausalLM(Model):
prefill_tokens_indices = batch.input_ids.new_zeros(len(out)) prefill_tokens_indices = batch.input_ids.new_zeros(len(out))
next_position_ids = batch.position_ids.new_empty(len(batch)) next_position_ids = batch.position_ids.new_empty(len(batch))
batch.slot_indices = batch.slot_indices[batch.end_seq_prefill - 1] batch.slot_indices = batch.slot_indices[batch.cu_seqlen_prefill[1:] - 1]
# We do not need start_seq_prefill and end_seq_prefill anymore # We do not need cu_seqlen_prefill anymore
batch.start_seq_prefill = None batch.cu_seqlen_prefill = None
batch.end_seq_prefill = None
else: else:
prefill_logprobs = None prefill_logprobs = None
next_position_ids = batch.position_ids next_position_ids = batch.position_ids
......
server/text_generation_server/models/mpt.py
View file @ 31e2253a
...@@ -66,7 +66,9 @@ class MPTSharded(CausalLM): ...@@ -66,7 +66,9 @@ class MPTSharded(CausalLM):
if local_path.exists(): if local_path.exists():
filename = str(local_path.resolve()) filename = str(local_path.resolve())
else: else:
filename = hf_hub_download(model_id, revision=revision, filename="config.json") filename = hf_hub_download(
model_id, revision=revision, filename="config.json"
)
with open(filename, "r") as f: with open(filename, "r") as f:
config = json.load(f) config = json.load(f)
config = PretrainedConfig(**config) config = PretrainedConfig(**config)
......
server/text_generation_server/utils/layers.py
View file @ 31e2253a
...@@ -359,7 +359,7 @@ try: ...@@ -359,7 +359,7 @@ try:
def __init__(self, inv_freq): def __init__(self, inv_freq):
super().__init__() super().__init__()
self.register_buffer("inv_freq", inv_freq) self.inv_freq = inv_freq
self._seq_len_cached = 0 self._seq_len_cached = 0
self._cos_cached = None self._cos_cached = None
self._sin_cached = None self._sin_cached = None
......
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