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More cache improvements (#1015)

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* fix rotating kv cache for chat use case

* reorg + fixes to caching, unify prompt caching across types and use cases for e.g. caching during a chat

* nit in chat

* fix tests

* fix tests

* fix tests

* docs

* chat command

* comments + docs

* Define meta_state on all Cache implementations

* fixes + trim_prompt_cache api

* fix default model

---------

Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
This commit is contained in:
Awni Hannun
2024-10-07 20:45:51 -07:00
committed by GitHub
parent 9bc53fc210
commit fca087be49
43 changed files with 1151 additions and 691 deletions
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20
llms/mlx_lm/models/gemma2.py
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@@ -1,7 +1,7 @@
# Copyright © 2023-2024 Apple Inc.
from dataclasses import dataclass
from typing import Optional, Tuple
from typing import Any, Optional, Tuple
import mlx.core as mx
import mlx.nn as nn
@@ -64,7 +64,7 @@ class Attention(nn.Module):
self,
x: mx.array,
mask: Optional[mx.array] = None,
cache: Optional[Tuple[mx.array, mx.array]] = None,
cache: Optional[Any] = None,
) -> mx.array:
B, L, D = x.shape
queries, keys, values = self.q_proj(x), self.k_proj(x), self.v_proj(x)
@@ -135,13 +135,11 @@ class TransformerBlock(nn.Module):
self,
x: mx.array,
mask: Optional[mx.array] = None,
cache: Optional[Tuple[mx.array, mx.array]] = None,
cache: Optional[Any] = None,
) -> mx.array:
r = self.self_attn(self.input_layernorm(x.astype(mx.float32)), mask, cache)
r = self.self_attn(self.input_layernorm(x), mask, cache)
h = x + self.post_attention_layernorm(r)
r = self.mlp(self.pre_feedforward_layernorm(h).astype(mx.float16)).astype(
mx.float32
)
r = self.mlp(self.pre_feedforward_layernorm(h))
out = h + self.post_feedforward_layernorm(r)
return out
@@ -200,11 +198,3 @@ class Model(nn.Module):
@property
def layers(self):
return self.model.layers
@property
def head_dim(self):
return self.args.head_dim
@property
def n_kv_heads(self):
return self.args.num_key_value_heads