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"jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"] flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] @@ -3131,15 +3132,15 @@ sigopt = ["sigopt"] sklearn = ["scikit-learn"] speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"] -tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"] -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 = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "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)"] timm = ["timm (<=0.9.16)"] tokenizers = ["tokenizers (>=0.19,<0.20)"] torch = ["accelerate (>=0.21.0)", "torch"] torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] 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)"] vision = ["Pillow (>=10.0.1,<=15.0)"] @@ -3564,4 +3565,4 @@ torch = ["torch"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<3.13" -content-hash = "877137815e7080bf0f021c1a6c137b2d02042fc9340c862347aa07fde53b5f93" +content-hash = "ca4bcd76fba70266e0945883398a0ab5e38e751ea5e6776264cb6c5979cc2e40" diff --git a/server/pyproject.toml b/server/pyproject.toml index a8b5d601873..26b41abeb05 100644 --- a/server/pyproject.toml +++ b/server/pyproject.toml @@ -26,7 +26,7 @@ hf-transfer = "^0.1.2" sentencepiece = "^0.1.97" tokenizers = "^0.19.1" huggingface-hub = "^0.23" -transformers = "^4.42" +transformers = "^4.43" einops = "^0.6.1" texttable = { version = "^1.6.7", optional = true } datasets = { version = "^2.14.0", optional = true } diff --git a/server/requirements_cuda.txt b/server/requirements_cuda.txt index d074e406168..478760687a4 100644 --- a/server/requirements_cuda.txt +++ b/server/requirements_cuda.txt @@ -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-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" -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" 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" 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-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" @@ -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" 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" -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" 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" diff --git a/server/requirements_intel.txt b/server/requirements_intel.txt index d074e406168..478760687a4 100644 --- a/server/requirements_intel.txt +++ b/server/requirements_intel.txt @@ -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-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" -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" 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" 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-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" @@ -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" 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" -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" 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" diff --git a/server/requirements_rocm.txt b/server/requirements_rocm.txt index d074e406168..478760687a4 100644 --- a/server/requirements_rocm.txt +++ b/server/requirements_rocm.txt @@ -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-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" -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" 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" 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-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" @@ -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" 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" -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" 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" diff --git a/server/text_generation_server/layers/rotary.py b/server/text_generation_server/layers/rotary.py index db78ee1cc94..e6e96abb3b8 100644 --- a/server/text_generation_server/layers/rotary.py +++ b/server/text_generation_server/layers/rotary.py @@ -1,4 +1,5 @@ import os +import math import torch from torch import nn from loguru import logger @@ -85,9 +86,13 @@ def static(cls, config, dim, base, device): scaling_factor = None rope_scaling = _get_rope_config(config) 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 - elif rope_scaling["type"] == "dynamic": + elif rope_type == "dynamic": scaling_factor = rope_scaling["factor"] return DynamicPositionRotaryEmbedding( dim=dim, @@ -96,7 +101,20 @@ def static(cls, config, dim, base, device): device=inv_freq.device, 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"] mscale = rope_scaling.get("mscale", 1.0) mscale_all_dim = rope_scaling.get("mscale_all_dim", 0.0) @@ -115,7 +133,7 @@ def static(cls, config, dim, base, device): mscale=mscale, mscale_all_dim=mscale_all_dim, ) - elif rope_scaling["type"] in ["su", "longrope"]: + elif rope_type in ["su", "longrope"]: short_factor = torch.tensor( rope_scaling["short_factor"], dtype=torch.float32, device=device ) @@ -327,10 +345,6 @@ def _update_cos_sin_cache(self, dtype, device, seqlen): 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): return (dim * math.log(max_position_embeddings / (num_rotations * 2 * math.pi))) / ( 2 * math.log(base) @@ -434,3 +448,33 @@ def _update_cos_sin_cache(self, dtype, device, seqlen): freqs = torch.outer(t, self.inv_freq.to(device=t.device)) self._cos_cached = (torch.cos(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)