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Add support for Llama 3 rotary embeddings (#2286) 

* Add support for Llama 3 rotary embeddings

* Update transformers to 4.43
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Daniël de Kok 2024-07-23 17:18:54 +02:00 committed by GitHub
parent 5d121a9705
commit 4ab4173767
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6 changed files with 176 additions and 131 deletions
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@ -794,74 +794,66 @@ setuptools = "*"
[[package]] [[package]]
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description = "" description = "Speed up file transfers with the Hugging Face Hub."
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
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[[package]] [[package]]
@ -3077,19 +3078,19 @@ telegram = ["requests"]
[[package]] [[package]]
name = "transformers" name = "transformers"
version = "4.42.4" version = "4.43.0"
description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow" description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
optional = false optional = false
python-versions = ">=3.8.0" python-versions = ">=3.8.0"
files = [ files = [
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filelock = "*" filelock = "*"
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numpy = ">=1.17,<2.0" numpy = ">=1.17"
packaging = ">=20.0" packaging = ">=20.0"
pyyaml = ">=5.1" pyyaml = ">=5.1"
regex = "!=2019.12.17" regex = "!=2019.12.17"
@ -3101,14 +3102,14 @@ tqdm = ">=4.27"
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@ -3131,15 +3132,15 @@ sigopt = ["sigopt"]
sklearn = ["scikit-learn"] sklearn = ["scikit-learn"]
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
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tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"] tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
timm = ["timm (<=0.9.16)"] timm = ["timm (<=0.9.16)"]
tokenizers = ["tokenizers (>=0.19,<0.20)"] tokenizers = ["tokenizers (>=0.19,<0.20)"]
torch = ["accelerate (>=0.21.0)", "torch"] torch = ["accelerate (>=0.21.0)", "torch"]
torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"] torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17,<2.0)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"] torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"]
video = ["av (==9.2.0)", "decord (==0.6.0)"] video = ["av (==9.2.0)", "decord (==0.6.0)"]
vision = ["Pillow (>=10.0.1,<=15.0)"] vision = ["Pillow (>=10.0.1,<=15.0)"]
@ -3564,4 +3565,4 @@ torch = ["torch"]
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.9,<3.13" python-versions = ">=3.9,<3.13"
content-hash = "877137815e7080bf0f021c1a6c137b2d02042fc9340c862347aa07fde53b5f93" content-hash = "ca4bcd76fba70266e0945883398a0ab5e38e751ea5e6776264cb6c5979cc2e40"

2
server/pyproject.toml
View File

@ -26,7 +26,7 @@ hf-transfer = "^0.1.2"
sentencepiece = "^0.1.97" sentencepiece = "^0.1.97"
tokenizers = "^0.19.1" tokenizers = "^0.19.1"
huggingface-hub = "^0.23" huggingface-hub = "^0.23"
transformers = "^4.42" transformers = "^4.43"
einops = "^0.6.1" einops = "^0.6.1"
texttable = { version = "^1.6.7", optional = true } texttable = { version = "^1.6.7", optional = true }
datasets = { version = "^2.14.0", optional = true } datasets = { version = "^2.14.0", optional = true }

6
server/requirements_cuda.txt
View File

@ -11,12 +11,12 @@ grpc-interceptor==0.15.4 ; python_version >= "3.9" and python_version < "3.13"
grpcio-reflection==1.62.2 ; python_version >= "3.9" and python_version < "3.13" grpcio-reflection==1.62.2 ; python_version >= "3.9" and python_version < "3.13"
grpcio-status==1.62.2 ; python_version >= "3.9" and python_version < "3.13" grpcio-status==1.62.2 ; python_version >= "3.9" and python_version < "3.13"
grpcio==1.65.1 ; python_version >= "3.9" and python_version < "3.13" grpcio==1.65.1 ; python_version >= "3.9" and python_version < "3.13"
hf-transfer==0.1.6 ; python_version >= "3.9" and python_version < "3.13" hf-transfer==0.1.8 ; python_version >= "3.9" and python_version < "3.13"
huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13" huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13"
idna==3.7 ; python_version >= "3.9" and python_version < "3.13" idna==3.7 ; python_version >= "3.9" and python_version < "3.13"
importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13" importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13"
loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13" loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
numpy==1.26.4 ; python_version >= "3.9" and python_version < "3.13" numpy==2.0.1 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-exporter-otlp-proto-grpc==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-exporter-otlp-proto-grpc==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
@ -41,7 +41,7 @@ sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13"
setuptools==71.1.0 ; python_version >= "3.9" and python_version < "3.13" setuptools==71.1.0 ; python_version >= "3.9" and python_version < "3.13"
tokenizers==0.19.1 ; python_version >= "3.9" and python_version < "3.13" tokenizers==0.19.1 ; python_version >= "3.9" and python_version < "3.13"
tqdm==4.66.4 ; python_version >= "3.9" and python_version < "3.13" tqdm==4.66.4 ; python_version >= "3.9" and python_version < "3.13"
transformers==4.42.4 ; python_version >= "3.9" and python_version < "3.13" transformers==4.43.0 ; python_version >= "3.9" and python_version < "3.13"
typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13" typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
typing-extensions==4.12.2 ; python_version >= "3.9" and python_version < "3.13" typing-extensions==4.12.2 ; python_version >= "3.9" and python_version < "3.13"
urllib3==2.2.2 ; python_version >= "3.9" and python_version < "3.13" urllib3==2.2.2 ; python_version >= "3.9" and python_version < "3.13"

6
server/requirements_intel.txt
View File

@ -11,12 +11,12 @@ grpc-interceptor==0.15.4 ; python_version >= "3.9" and python_version < "3.13"
grpcio-reflection==1.62.2 ; python_version >= "3.9" and python_version < "3.13" grpcio-reflection==1.62.2 ; python_version >= "3.9" and python_version < "3.13"
grpcio-status==1.62.2 ; python_version >= "3.9" and python_version < "3.13" grpcio-status==1.62.2 ; python_version >= "3.9" and python_version < "3.13"
grpcio==1.65.1 ; python_version >= "3.9" and python_version < "3.13" grpcio==1.65.1 ; python_version >= "3.9" and python_version < "3.13"
hf-transfer==0.1.6 ; python_version >= "3.9" and python_version < "3.13" hf-transfer==0.1.8 ; python_version >= "3.9" and python_version < "3.13"
huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13" huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13"
idna==3.7 ; python_version >= "3.9" and python_version < "3.13" idna==3.7 ; python_version >= "3.9" and python_version < "3.13"
importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13" importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13"
loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13" loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
numpy==1.26.4 ; python_version >= "3.9" and python_version < "3.13" numpy==2.0.1 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-exporter-otlp-proto-grpc==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-exporter-otlp-proto-grpc==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
@ -41,7 +41,7 @@ sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13"
setuptools==71.1.0 ; python_version >= "3.9" and python_version < "3.13" setuptools==71.1.0 ; python_version >= "3.9" and python_version < "3.13"
tokenizers==0.19.1 ; python_version >= "3.9" and python_version < "3.13" tokenizers==0.19.1 ; python_version >= "3.9" and python_version < "3.13"
tqdm==4.66.4 ; python_version >= "3.9" and python_version < "3.13" tqdm==4.66.4 ; python_version >= "3.9" and python_version < "3.13"
transformers==4.42.4 ; python_version >= "3.9" and python_version < "3.13" transformers==4.43.0 ; python_version >= "3.9" and python_version < "3.13"
typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13" typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
typing-extensions==4.12.2 ; python_version >= "3.9" and python_version < "3.13" typing-extensions==4.12.2 ; python_version >= "3.9" and python_version < "3.13"
urllib3==2.2.2 ; python_version >= "3.9" and python_version < "3.13" urllib3==2.2.2 ; python_version >= "3.9" and python_version < "3.13"

6
server/requirements_rocm.txt
View File

@ -11,12 +11,12 @@ grpc-interceptor==0.15.4 ; python_version >= "3.9" and python_version < "3.13"
grpcio-reflection==1.62.2 ; python_version >= "3.9" and python_version < "3.13" grpcio-reflection==1.62.2 ; python_version >= "3.9" and python_version < "3.13"
grpcio-status==1.62.2 ; python_version >= "3.9" and python_version < "3.13" grpcio-status==1.62.2 ; python_version >= "3.9" and python_version < "3.13"
grpcio==1.65.1 ; python_version >= "3.9" and python_version < "3.13" grpcio==1.65.1 ; python_version >= "3.9" and python_version < "3.13"
hf-transfer==0.1.6 ; python_version >= "3.9" and python_version < "3.13" hf-transfer==0.1.8 ; python_version >= "3.9" and python_version < "3.13"
huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13" huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13"
idna==3.7 ; python_version >= "3.9" and python_version < "3.13" idna==3.7 ; python_version >= "3.9" and python_version < "3.13"
importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13" importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13"
loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13" loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
numpy==1.26.4 ; python_version >= "3.9" and python_version < "3.13" numpy==2.0.1 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
opentelemetry-exporter-otlp-proto-grpc==1.25.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-exporter-otlp-proto-grpc==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
@ -41,7 +41,7 @@ sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13"
setuptools==71.1.0 ; python_version >= "3.9" and python_version < "3.13" setuptools==71.1.0 ; python_version >= "3.9" and python_version < "3.13"
tokenizers==0.19.1 ; python_version >= "3.9" and python_version < "3.13" tokenizers==0.19.1 ; python_version >= "3.9" and python_version < "3.13"
tqdm==4.66.4 ; python_version >= "3.9" and python_version < "3.13" tqdm==4.66.4 ; python_version >= "3.9" and python_version < "3.13"
transformers==4.42.4 ; python_version >= "3.9" and python_version < "3.13" transformers==4.43.0 ; python_version >= "3.9" and python_version < "3.13"
typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13" typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
typing-extensions==4.12.2 ; python_version >= "3.9" and python_version < "3.13" typing-extensions==4.12.2 ; python_version >= "3.9" and python_version < "3.13"
urllib3==2.2.2 ; python_version >= "3.9" and python_version < "3.13" urllib3==2.2.2 ; python_version >= "3.9" and python_version < "3.13"

60
server/text_generation_server/layers/rotary.py
View File

@ -1,4 +1,5 @@
import os import os
import math
import torch import torch
from torch import nn from torch import nn
from loguru import logger from loguru import logger
@ -85,9 +86,13 @@ class PositionRotaryEmbedding(nn.Module):
scaling_factor = None scaling_factor = None
rope_scaling = _get_rope_config(config) rope_scaling = _get_rope_config(config)
if rope_scaling is not None: if rope_scaling is not None:
if rope_scaling["type"] == "linear": # `rope_type` is now standard in transformers, but some existing models
# have `type` instead.
rope_type = rope_scaling.get("rope_type", rope_scaling.get("type", None))
if rope_type == "linear":
pass pass
elif rope_scaling["type"] == "dynamic": elif rope_type == "dynamic":
scaling_factor = rope_scaling["factor"] scaling_factor = rope_scaling["factor"]
return DynamicPositionRotaryEmbedding( return DynamicPositionRotaryEmbedding(
dim=dim, dim=dim,
@ -96,7 +101,20 @@ class PositionRotaryEmbedding(nn.Module):
device=inv_freq.device, device=inv_freq.device,
scaling_factor=scaling_factor, scaling_factor=scaling_factor,
) )
elif rope_scaling["type"] == "yarn": elif rope_type == "llama3":
inv_freq = apply_llama3_scaling(
inv_freq,
scaling_factor=rope_scaling["factor"],
low_freq_factor=rope_scaling["low_freq_factor"],
high_freq_factor=rope_scaling["high_freq_factor"],
original_max_position_embeddings=rope_scaling[
"original_max_position_embeddings"
],
)
return cls(inv_freq, scaling_factor)
elif rope_type == "yarn":
scaling_factor = rope_scaling["factor"] scaling_factor = rope_scaling["factor"]
mscale = rope_scaling.get("mscale", 1.0) mscale = rope_scaling.get("mscale", 1.0)
mscale_all_dim = rope_scaling.get("mscale_all_dim", 0.0) mscale_all_dim = rope_scaling.get("mscale_all_dim", 0.0)
@ -115,7 +133,7 @@ class PositionRotaryEmbedding(nn.Module):
mscale=mscale, mscale=mscale,
mscale_all_dim=mscale_all_dim, mscale_all_dim=mscale_all_dim,
) )
elif rope_scaling["type"] in ["su", "longrope"]: elif rope_type in ["su", "longrope"]:
short_factor = torch.tensor( short_factor = torch.tensor(
rope_scaling["short_factor"], dtype=torch.float32, device=device rope_scaling["short_factor"], dtype=torch.float32, device=device
) )
@ -327,10 +345,6 @@ class DynamicPositionRotaryEmbedding(PositionRotaryEmbedding):
self._sin_cached = torch.sin(freqs).to(dtype) self._sin_cached = torch.sin(freqs).to(dtype)
# Inverse dim formula to find dim based on number of rotations
import math
def find_correction_dim(num_rotations, dim, base=10000, max_position_embeddings=2048): def find_correction_dim(num_rotations, dim, base=10000, max_position_embeddings=2048):
return (dim * math.log(max_position_embeddings / (num_rotations * 2 * math.pi))) / ( return (dim * math.log(max_position_embeddings / (num_rotations * 2 * math.pi))) / (
2 * math.log(base) 2 * math.log(base)
@ -434,3 +448,33 @@ class YarnPositionRotaryEmbedding(PositionRotaryEmbedding):
freqs = torch.outer(t, self.inv_freq.to(device=t.device)) freqs = torch.outer(t, self.inv_freq.to(device=t.device))
self._cos_cached = (torch.cos(freqs) * self.mscale).to(dtype) self._cos_cached = (torch.cos(freqs) * self.mscale).to(dtype)
self._sin_cached = (torch.sin(freqs) * self.mscale).to(dtype) self._sin_cached = (torch.sin(freqs) * self.mscale).to(dtype)
def apply_llama3_scaling(
freqs: torch.Tensor,
*,
scaling_factor: int,
low_freq_factor: int,
high_freq_factor: int,
original_max_position_embeddings: int,
):
low_freq_wavelen = original_max_position_embeddings / low_freq_factor
high_freq_wavelen = original_max_position_embeddings / high_freq_factor
new_freqs = []
for freq in freqs:
wavelen = 2 * math.pi / freq
if wavelen < high_freq_wavelen:
new_freqs.append(freq)
elif wavelen > low_freq_wavelen:
new_freqs.append(freq / scaling_factor)
else:
assert low_freq_wavelen != high_freq_wavelen
smooth = (original_max_position_embeddings / wavelen - low_freq_factor) / (
high_freq_factor - low_freq_factor
)
new_freqs.append((1 - smooth) * freq / scaling_factor + smooth * freq)
return torch.tensor(new_freqs, dtype=freqs.dtype, device=freqs.device)