mirror of https://github.com/google/gemma.cpp.git
104 lines
3.3 KiB
C++
104 lines
3.3 KiB
C++
// Copyright 2024 Google LLC
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// SPDX-License-Identifier: Apache-2.0
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef THIRD_PARTY_GEMMA_CPP_GEMMA_KV_CACHE_H_
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#define THIRD_PARTY_GEMMA_CPP_GEMMA_KV_CACHE_H_
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#include <stddef.h>
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#include <optional>
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#include <utility>
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#include <vector>
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#include "gemma/configs.h" // ModelConfig
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#include "gemma/gemma_args.h" // InferenceArgs
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#include "util/basics.h" // BF16
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#include "util/mat.h"
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#include "hwy/base.h"
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namespace gcpp {
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using KV_t = BF16;
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// A non-owning view of a KVCache.
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struct KVCachePtr {
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bool IsEmpty() const { return kv_cache.Rows() == 0; }
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size_t SeqLen() const;
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MatPtrT<KV_t> kv_cache;
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MatPtrT<KV_t> k_cache;
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MatPtrT<KV_t> v_cache;
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};
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struct KVCache {
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KVCache(const ModelConfig& config, const InferenceArgs& inference_args,
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const Allocator& allocator);
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// Returns a deep copy of the KVCache. Use explicit function instead of
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// copy ctor to make the cost explicit.
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KVCache Copy();
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size_t SeqLen() const {
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return kv_cache.Rows();
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}
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MatStorageT<KV_t> kv_cache; // [seq_len, layers * kv_heads * qkv_dim * 2]
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// The format of k_cache indicates that there are pairs of values from
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// qkv_dim in groups of 2x kFloatsPerVector(=NF) elements from the sequence,
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// in groups of qkv_dim/2 elements in groups of kv_heads elements.
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// This enables sequential loading of the data when filling 2 vectors with
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// NF sequence elements of pairs of BF16 qkv values. The next vector then
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// continues reading the rest of qkv.
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// [seq_len / 2NF, layers * kv_heads * qkv_dim/2 * 2NF * 2]
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MatStorageT<KV_t> k_cache;
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// v_cache is formatted to allow sequential access to V during scaling and
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// update of att_out.
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// Originally [seq_len, layers * kv_heads * qkv_dim]
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// v_cache is transposed to:
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// [layers, kv_heads, seq_len, qkv_dim], reshaped to:
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// [layers, kv_heads, seq_len/(2NF), 2NF, qkv_dim/(2NF), 2NF]
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// then transposed to:
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// [seq_len/(2NF), layers, kv_heads, qkv_dim/(2NF), 2NF, 2NF]
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// and finally packed in a 2D MatStorageT as:
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// [seq_len/(2NF), layers * kv_heads * qkv_dim/(2NF) * 2NF * 2NF]
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// This allows sequential reads of 2NF registers each of 2NF BF16 values,
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// repeatedly until all of qkv_dim is read.
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MatStorageT<KV_t> v_cache;
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KVCachePtr ToPtr() {
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return KVCachePtr{
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.kv_cache = kv_cache,
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.k_cache = k_cache,
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.v_cache = v_cache,
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};
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}
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private:
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const Allocator& allocator_;
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// For use by other ctor and Copy()
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KVCache(const Extents2D& kv_extents, const Allocator& allocator);
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};
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inline size_t KVCachePtr::SeqLen() const {
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return kv_cache.Rows();
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}
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// Convenience function to create views into KVCaches.
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std::vector<KVCachePtr> ToKVCachePtrs(const hwy::Span<KVCache>& kv_caches);
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} // namespace gcpp
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#endif // THIRD_PARTY_GEMMA_CPP_GEMMA_KV_CACHE_H_
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