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Quantized KV Cache (#1075)

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* add QuantizedKVCache

* simplify

* add tests

* single sdpa function

* fix sed

* in place

* fix tests

* support different k and v head dims
This commit is contained in:
Alex Barron
2024-10-31 16:59:52 -07:00
committed by GitHub
parent 9f34fdbda4
commit 85ffd2c96a
32 changed files with 411 additions and 85 deletions
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6
llms/mlx_lm/models/gpt2.py
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@@ -7,7 +7,7 @@ import mlx.core as mx
import mlx.nn as nn
import numpy as np
from .base import BaseModelArgs, create_attention_mask
from .base import BaseModelArgs, create_attention_mask, scaled_dot_product_attention
@dataclass
@@ -61,8 +61,8 @@ class Attention(nn.Module):
if cache is not None:
keys, values = cache.update_and_fetch(keys, values)
output = mx.fast.scaled_dot_product_attention(
queries, keys, values, scale=self.scale, mask=mask
output = scaled_dot_product_attention(
queries, keys, values, cache=cache, scale=self.scale, mask=mask
)
output = output.transpose(0, 2, 1, 3).reshape(B, L, -1)