Add support for Llama 3 rotary embeddings (#2286)

* Add support for Llama 3 rotary embeddings

* Update transformers to 4.43

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 }

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"

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"

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"

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)