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Update rope_scaling to rope_parameters in preparation for Transformers v5 (#28542)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-11-19 18:06:36 +01:00
committed by GitHub
parent d44e9df7d4
commit a8b70304d6
104 changed files with 542 additions and 910 deletions
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17
vllm/model_executor/models/granite.py
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@@ -26,7 +26,6 @@
from collections.abc import Iterable
from itertools import islice
from typing import Any
import torch
from torch import nn
@@ -112,8 +111,6 @@ class GraniteAttention(nn.Module):
hidden_size: int,
num_heads: int,
num_kv_heads: int,
rope_theta: float = 10000,
rope_scaling: dict[str, Any] | None = None,
max_position_embeddings: int = 8192,
quant_config: QuantizationConfig | None = None,
bias: bool = False,
@@ -143,7 +140,6 @@ class GraniteAttention(nn.Module):
self.q_size = self.num_heads * self.head_dim
self.kv_size = self.num_kv_heads * self.head_dim
self.scaling = config.attention_multiplier
self.rope_theta = rope_theta
self.max_position_embeddings = max_position_embeddings
self.qkv_proj = QKVParallelLinear(
@@ -167,8 +163,7 @@ class GraniteAttention(nn.Module):
self.head_dim,
rotary_dim=self.head_dim,
max_position=max_position_embeddings,
base=rope_theta,
rope_scaling=rope_scaling,
rope_parameters=config.rope_parameters,
)
self.attn = Attention(
self.num_heads,
@@ -204,14 +199,6 @@ class GraniteDecoderLayer(nn.Module):
super().__init__()
self.hidden_size = config.hidden_size
self.residual_multiplier = config.residual_multiplier
rope_theta = getattr(config, "rope_theta", 10000)
rope_scaling = getattr(config, "rope_scaling", None)
if rope_scaling is not None and getattr(
config, "original_max_position_embeddings", None
):
rope_scaling["original_max_position_embeddings"] = (
config.original_max_position_embeddings
)
max_position_embeddings = getattr(config, "max_position_embeddings", 8192)
# Support abacusai/Smaug-72B-v0.1 with attention_bias
# Support internlm/internlm-7b with bias
@@ -225,8 +212,6 @@ class GraniteDecoderLayer(nn.Module):
num_kv_heads=getattr(
config, "num_key_value_heads", config.num_attention_heads
),
rope_theta=rope_theta,
rope_scaling=rope_scaling,
max_position_embeddings=max_position_embeddings,
quant_config=quant_config,
bias=attention_bias,