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gemma.cpp/gemma/configs.h

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// Copyright 2024 Google LLC
// SPDX-License-Identifier: Apache-2.0
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef THIRD_PARTY_GEMMA_CPP_GEMMA_CONFIGS_H_
#define THIRD_PARTY_GEMMA_CPP_GEMMA_CONFIGS_H_
// Model configurations
#include <stddef.h>
#include <array>
#include "hwy/base.h" // hwy::bfloat16_t
namespace gcpp {
// Allow changing pre-allocated kv cache size as a compiler flag
#ifndef GEMMA_MAX_SEQLEN
#define GEMMA_MAX_SEQLEN 4096
#endif // !GEMMA_MAX_SEQLEN
// Allow changing k parameter of `SampleTopK` as a compiler flag
#ifndef GEMMA_TOPK
#define GEMMA_TOPK 1
#endif // !GEMMA_TOPK
// Allow changing upper bound on threads as a compiler flag
#ifndef GEMMA_MAX_THREADS
#define GEMMA_MAX_THREADS 128
#endif // !GEMMA_MAX_THREADS
static constexpr size_t kSeqLen = GEMMA_MAX_SEQLEN;
static constexpr size_t kTopK = GEMMA_TOPK;
static constexpr size_t kMaxThreads = GEMMA_MAX_THREADS;
using EmbedderInputT = hwy::bfloat16_t;
enum class LayerAttentionType {
kGemma,
kGriffinRecurrentBlock,
};
template <size_t kNum>
constexpr std::array<LayerAttentionType, kNum> FixedLayerConfig(
LayerAttentionType type) {
std::array<LayerAttentionType, kNum> config = {};
for (LayerAttentionType& l : config) {
l = type;
}
return config;
}
template <size_t kNum>
constexpr std::array<size_t, kNum> FixedAttentionWindowSizes(
size_t window_size) {
std::array<size_t, kNum> window_size_configs = {};
for (size_t& l : window_size_configs) {
l = window_size;
}
return window_size_configs;
}
template <size_t kNumLayers>
constexpr size_t NumLayersOfTypeBefore(
const std::array<LayerAttentionType, kNumLayers>& layers,
LayerAttentionType type, size_t num) {
size_t count = 0;
for (size_t i = 0; i < num; i++) {
if (layers[i] == type) count++;
}
return count;
}
template <class TConfig, typename = void>
struct CacheLayerSize {
constexpr size_t operator()() const {
return TConfig::kKVHeads * TConfig::kQKVDim * 2;
}
};
template <class TConfig, typename = void>
struct CachePosSize {
constexpr size_t operator()() const {
return TConfig::kGemmaLayers * CacheLayerSize<TConfig>()();
}
};
struct ConfigNoSSM {
static constexpr int kGriffinLayers = 0;
static constexpr int kConv1dWidth = 0;
static constexpr bool kFFBiases = false;
static constexpr bool kSoftmaxAttnOutputBiases = false;
static constexpr bool kUseHalfRope = false;
static constexpr bool kUseLocalAttention = false;
static constexpr bool kInterleaveQKV = true;
static constexpr int kNumTensorScales = 0;
};
struct ConfigNoCapNoSSM : ConfigNoSSM {
static constexpr float kAttCap = 0.0f;
static constexpr float kFinalCap = 0.0f;
};
// For Gemma2 with SoftCap
struct ConfigCapNoSSM : ConfigNoSSM {
static constexpr float kAttCap = 50.0f;
static constexpr float kFinalCap = 30.0f;
};
template <typename TWeight>
struct ConfigGemma27B : public ConfigCapNoSSM {
using Weight = TWeight; // make accessible where we only have a TConfig
static constexpr int kSeqLen = 8192;
static constexpr int kVocabSize = 256000;
static constexpr std::array<LayerAttentionType, 46> kLayerConfig =
FixedLayerConfig<46>(LayerAttentionType::kGemma);
static constexpr std::array<size_t, 46> kAttentionWindowSizes = {
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen,
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen,
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen,
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen,
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen};
static constexpr int kLayers = kLayerConfig.size();
static constexpr int kGemmaLayers = kLayers;
static constexpr int kModelDim = 4608;
static constexpr int kFFHiddenDim = 16 * 4608 / 2; // = 36864
static constexpr int kHeads = 32;
static constexpr int kKVHeads = 16;
static constexpr int kQKVDim = 128; // query size == key size == value size
static constexpr int kTopK = gcpp::kTopK;
static constexpr bool kAbsolutePE = false;
static constexpr bool kPostNormScale = true;
};
template <typename TWeight>
struct ConfigGemma9B : public ConfigCapNoSSM {
using Weight = TWeight; // make accessible where we only have a TConfig
static constexpr int kSeqLen = 8192;
static constexpr int kVocabSize = 256000;
static constexpr std::array<LayerAttentionType, 42> kLayerConfig =
FixedLayerConfig<42>(LayerAttentionType::kGemma);
static constexpr std::array<size_t, 42> kAttentionWindowSizes = {
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen,
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen,
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen,
4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen, 4096, kSeqLen,
4096, kSeqLen};
static constexpr int kLayers = kLayerConfig.size();
static constexpr int kGemmaLayers = kLayers;
static constexpr int kModelDim = 3584;
static constexpr int kFFHiddenDim = 8 * 3584 / 2; // = 14336
static constexpr int kHeads = 16;
static constexpr int kKVHeads = 8;
static constexpr int kQKVDim = 256; // query size == key size == value size
static constexpr int kTopK = gcpp::kTopK;
static constexpr bool kAbsolutePE = false;
static constexpr bool kPostNormScale = true;
};
template <typename TWeight>
struct ConfigGemma7B : public ConfigNoCapNoSSM {
using Weight = TWeight; // make accessible where we only have a TConfig
static constexpr int kSeqLen = gcpp::kSeqLen;
static constexpr int kVocabSize = 256000;
static constexpr std::array<LayerAttentionType, 28> kLayerConfig =
FixedLayerConfig<28>(LayerAttentionType::kGemma);
static constexpr std::array<size_t, 28> kAttentionWindowSizes =
FixedAttentionWindowSizes<28>(kSeqLen);
static constexpr int kLayers = kLayerConfig.size();
static constexpr int kGemmaLayers = kLayers;
static constexpr int kModelDim = 3072;
static constexpr int kFFHiddenDim = 16 * 3072 / 2; // = 24576
static constexpr int kHeads = 16;
static constexpr int kKVHeads = 16; // standard MHA
static constexpr int kQKVDim = 256; // query size == key size == value size
static constexpr int kTopK = gcpp::kTopK;
static constexpr bool kAbsolutePE = false;
static constexpr bool kPostNormScale = false;
};
template <typename TWeight>
struct ConfigGemma2B : public ConfigNoCapNoSSM {
using Weight = TWeight; // make accessible where we only have a TConfig
static constexpr int kSeqLen = gcpp::kSeqLen;
static constexpr int kVocabSize = 256000;
static constexpr std::array<LayerAttentionType, 18> kLayerConfig =
FixedLayerConfig<18>(LayerAttentionType::kGemma);
static constexpr std::array<size_t, 18> kAttentionWindowSizes =
FixedAttentionWindowSizes<18>(kSeqLen);
static constexpr int kLayers = kLayerConfig.size();
static constexpr int kGemmaLayers = kLayers;
static constexpr int kModelDim = 2048;
static constexpr int kFFHiddenDim = 16 * 2048 / 2; // = 16384
static constexpr int kHeads = 8;
static constexpr int kKVHeads = 1;
static constexpr int kQKVDim = 256; // query size == key size == value size
static constexpr int kTopK = gcpp::kTopK;
static constexpr bool kAbsolutePE = false;
static constexpr bool kPostNormScale = false;
};
template <typename TWeight>
struct ConfigGemmaTiny : public ConfigNoSSM {
using Weight = TWeight; // make accessible where we only have a TConfig
static constexpr int kSeqLen = 32;
static constexpr int kVocabSize = 64;
static constexpr std::array<LayerAttentionType, 3> kLayerConfig =
FixedLayerConfig<3>(LayerAttentionType::kGemma);
static constexpr std::array<size_t, 3> kAttentionWindowSizes =
FixedAttentionWindowSizes<3>(kSeqLen);
static constexpr int kLayers = kLayerConfig.size();
static constexpr int kGemmaLayers = kLayers;
static constexpr int kModelDim = 128;
static constexpr int kFFHiddenDim = 256;
static constexpr int kHeads = 4;
static constexpr int kKVHeads = 1;
static constexpr int kQKVDim = 16; // query size == key size == value size
static constexpr int kTopK = gcpp::kTopK;
static constexpr bool kAbsolutePE = false;
static constexpr bool kPostNormScale = false;
static constexpr float kAttCap = 0.0f;
// This is required for optimize_test to pass.
static constexpr float kFinalCap = 30.0f;
};
template <typename TWeight>
struct ConfigGriffin2B {
using Weight = TWeight; // make accessible where we only have a TConfig
// Griffin uses local attention, so kSeqLen is actually the local attention
// window.
static constexpr int kSeqLen = 2048;
static constexpr int kVocabSize = 256000;
static constexpr std::array<LayerAttentionType, 26> kLayerConfig = {
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGemma,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGemma,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGemma,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGemma,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGemma,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGemma,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGemma,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGemma,
LayerAttentionType::kGriffinRecurrentBlock,
LayerAttentionType::kGriffinRecurrentBlock,
};
static constexpr std::array<size_t, 26> kAttentionWindowSizes =
FixedAttentionWindowSizes<26>(kSeqLen);
static constexpr int kLayers = kLayerConfig.size();
static constexpr int kGemmaLayers =
NumLayersOfTypeBefore(kLayerConfig, LayerAttentionType::kGemma, kLayers);
static constexpr int kGriffinLayers =
NumLayersOfTypeBefore(kLayerConfig,
LayerAttentionType::kGriffinRecurrentBlock,
kLayers);
static constexpr int kModelDim = 2560;
static constexpr int kFFHiddenDim = 7680;
static constexpr int kHeads = 10;
static constexpr int kKVHeads = 1;
static constexpr int kQKVDim = 256; // query size == key size == value size
static constexpr int kTopK = gcpp::kTopK;
static constexpr bool kAbsolutePE = false;
static constexpr bool kPostNormScale = false;
// No SoftCap.
static constexpr float kAttCap = 0.0f;
static constexpr float kFinalCap = 0.0f;
// SSM config.
static constexpr int kConv1dWidth = 4;
static constexpr bool kFFBiases = true;
static constexpr bool kSoftmaxAttnOutputBiases = true;
static constexpr bool kUseHalfRope = true;
static constexpr bool kUseLocalAttention = true;
static constexpr bool kInterleaveQKV = false;
static constexpr int kNumTensorScales = 140;
};
} // namespace gcpp
#endif // THIRD_PARTY_GEMMA_CPP_GEMMA_CONFIGS_H_
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