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feat: Qwen2 support

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This commit is contained in:
John Mai
2024-03-03 22:26:28 +08:00
parent 7b746cb89c
commit 66d9202360
7 changed files with 291 additions and 2 deletions
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5
Libraries/LLM/Configuration.swift
View File

@@ -31,6 +31,7 @@ public enum ModelType: String, Codable {
case llama
case phi
case gemma
case qwen2
func createModel(configuration: URL) throws -> LLMModel {
switch self {
@@ -46,6 +47,10 @@ public enum ModelType: String, Codable {
let configuration = try JSONDecoder().decode(
GemmaConfiguration.self, from: Data(contentsOf: configuration))
return GemmaModel(configuration)
case .qwen2:
let configuration = try JSONDecoder().decode(
Qwen2Configuration.self, from: Data(contentsOf: configuration))
return Qwen2Model(configuration)
}
}
}

8
Libraries/LLM/Models.swift
View File

@@ -85,6 +85,13 @@ extension ModelConfiguration {
"<start_of_turn>user \(prompt)<end_of_turn><start_of_turn>model"
}
public static let qwen205b4bit = ModelConfiguration(
id: "mlx-community/Qwen1.5-0.5B-Chat-4bit",
overrideTokenizer: "PreTrainedTokenizer"
) { prompt in
"<|im_start|>user \(prompt)<|im_end|><|im_start|>assistant"
}
private enum BootstrapState {
case idle
case bootstrapping
@@ -102,6 +109,7 @@ extension ModelConfiguration {
codeLlama13b4bit,
phi4bit,
gemma2bQuantized,
qwen205b4bit,
])
bootstrapState = .bootstrapped

263
Libraries/LLM/Qwen2.swift Normal file
View File

@@ -0,0 +1,263 @@
//
// Qwen2.swift
// LLM
//
// Created by John Mai on 2024/3/3.
//
import Foundation
import MLX
import MLXNN
// port of https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/models/qwen2.py
private class Attention: Module {
let args: Qwen2Configuration
let repeats: Int
let scale: Float
@ModuleInfo(key: "q_proj") var wq: Linear
@ModuleInfo(key: "k_proj") var wk: Linear
@ModuleInfo(key: "v_proj") var wv: Linear
@ModuleInfo(key: "o_proj") var wo: Linear
let rope: RoPE
public init(_ args: Qwen2Configuration) {
self.args = args
let dim = args.hiddenSize
let heads = args.attentionHeads
let kvHeads = args.kvHeads
self.repeats = heads / kvHeads
let headDim = args.hiddenSize / heads
self.scale = pow(Float(headDim), -0.5)
_wq.wrappedValue = Linear(dim, heads * headDim, bias: true)
_wk.wrappedValue = Linear(dim, kvHeads * headDim, bias: true)
_wv.wrappedValue = Linear(dim, kvHeads * headDim, bias: true)
_wo.wrappedValue = Linear(heads * headDim, dim, bias: false)
let ropeScale: Float
if let ropeScaling = args.ropeScaling, ropeScaling["type"] == .string("linear"),
let factor = ropeScaling["factor"]
{
switch factor {
case .string:
fatalError("ropeScaling.factor must be a float")
case .float(let v):
ropeScale = 1 / v
}
} else {
ropeScale = 1
}
self.rope = RoPE(
dimensions: headDim, traditional: args.ropeTraditional, base: args.ropeTheta,
scale: ropeScale)
}
public func callAsFunction(
_ x: MLXArray, mask: MLXArray? = nil, cache: (MLXArray, MLXArray)? = nil) -> (MLXArray, (MLXArray, MLXArray))
{
let (B, L) = (x.dim(0), x.dim(1))
var queries = wq(x)
var keys = wk(x)
var values = wv(x)
// prepare the queries, keys and values for the attention computation
queries = queries.reshaped(B, L, args.attentionHeads, -1).transposed(0, 2, 1, 3)
keys = keys.reshaped(B, L, args.kvHeads, -1).transposed(0, 2, 1, 3)
values = values.reshaped(B, L, args.kvHeads, -1).transposed(0, 2, 1, 3)
if repeats > 1 {
keys = MLXArray.repeat(keys, count: repeats, axis: 1)
values = MLXArray.repeat(values, count: repeats, axis: 1)
}
if let (keyCache, valueCache) = cache {
queries = rope(queries, offset: keyCache.dim(2))
keys = rope(keys, offset: keyCache.dim(2))
keys = concatenated([keyCache, keys], axis: 2)
values = concatenated([valueCache, values], axis: 2)
} else {
queries = rope(queries)
keys = rope(keys)
}
var scores = (queries * scale).matmul(keys.transposed(0, 1, 3, 2))
if let mask {
scores = scores + mask
}
scores = softMax(scores.asType(.float32), axis: -1).asType(scores.dtype)
let output = matmul(scores, values).transposed(0, 2, 1, 3).reshaped(B, L, -1)
return (wo(output), (keys, values))
}
}
private class MLP: Module, UnaryLayer {
@ModuleInfo(key: "gate_proj") var gate: Linear
@ModuleInfo(key: "down_proj") var down: Linear
@ModuleInfo(key: "up_proj") var up: Linear
public init(dimensions: Int, hiddenDimensions: Int) {
_gate.wrappedValue = Linear(dimensions, hiddenDimensions, bias: false)
_down.wrappedValue = Linear(hiddenDimensions, dimensions, bias: false)
_up.wrappedValue = Linear(dimensions, hiddenDimensions, bias: false)
}
public func callAsFunction(_ x: MLXArray) -> MLXArray {
down(silu(gate(x)) * up(x))
}
}
private class TransformerBlock: Module {
@ModuleInfo(key: "self_attn") var attention: Attention
let mlp: MLP
@ModuleInfo(key: "input_layernorm") var inputLayerNorm: RMSNorm
@ModuleInfo(key: "post_attention_layernorm") var postAttentionLayerNorm: RMSNorm
public init(_ args: Qwen2Configuration) {
_attention.wrappedValue = Attention(args)
self.mlp = MLP(dimensions: args.hiddenSize, hiddenDimensions: args.intermediateSize)
_inputLayerNorm.wrappedValue = RMSNorm(
dimensions: args.hiddenSize, eps: args.rmsNormEps)
_postAttentionLayerNorm.wrappedValue = RMSNorm(
dimensions: args.hiddenSize, eps: args.rmsNormEps)
}
public func callAsFunction(
_ x: MLXArray, mask: MLXArray? = nil, cache: (MLXArray, MLXArray)? = nil) -> (MLXArray, (MLXArray, MLXArray))
{
var (r, cache) = attention(inputLayerNorm(x), mask: mask, cache: cache)
let h = x + r
r = mlp(postAttentionLayerNorm(h))
let out = h + r
return (out, cache)
}
}
public class Qwen2ModelInner: Module {
@ModuleInfo(key: "embed_tokens") var embedTokens: Embedding
fileprivate let layers: [TransformerBlock]
let norm: RMSNorm
public init(_ args: Qwen2Configuration) {
precondition(args.vocabularySize > 0)
_embedTokens.wrappedValue = Embedding(
embeddingCount: args.vocabularySize, dimensions: args.hiddenSize)
self.layers = (0 ..< args.hiddenLayers)
.map { _ in
TransformerBlock(args)
}
self.norm = RMSNorm(dimensions: args.hiddenSize, eps: args.rmsNormEps)
}
public func callAsFunction(_ inputs: MLXArray, cache: [(MLXArray, MLXArray)]? = nil) -> (
MLXArray, [(MLXArray, MLXArray)])
{
var h = embedTokens(inputs)
var mask: MLXArray? = nil
if h.dim(1) > 1 {
mask = MultiHeadAttention.createAdditiveCausalMask(h.dim(1))
mask = mask?.asType(h.dtype)
}
var newCache = [(MLXArray, MLXArray)]()
for (i, layer) in layers.enumerated() {
var cacheUpdate: (MLXArray, MLXArray)
(h, cacheUpdate) = layer(h, mask: mask, cache: cache?[i])
newCache.append(cacheUpdate)
}
return (norm(h), newCache)
}
}
public class Qwen2Model: Module, LLMModel {
public let vocabularySize: Int
let model: Qwen2ModelInner
@ModuleInfo(key: "lm_head") var lmHead: Linear
public init(_ args: Qwen2Configuration) {
self.vocabularySize = args.vocabularySize
self.model = Qwen2ModelInner(args)
_lmHead.wrappedValue = Linear(args.hiddenSize, args.vocabularySize, bias: false)
}
public func callAsFunction(_ inputs: MLXArray, cache: [(MLXArray, MLXArray)]?) -> (
MLXArray, [(MLXArray, MLXArray)])
{
let (out, cache) = model(inputs, cache: cache)
return (lmHead(out), cache)
}
}
public struct Qwen2Configuration: Codable {
var hiddenSize: Int
var hiddenLayers: Int
var intermediateSize: Int
var attentionHeads: Int
var rmsNormEps: Float
var vocabularySize: Int
var kvHeads: Int
var ropeTheta: Float = 1_000_000
var ropeTraditional: Bool = false
var ropeScaling: [String: StringOrNumber]? = nil
enum CodingKeys: String, CodingKey {
case hiddenSize = "hidden_size"
case hiddenLayers = "num_hidden_layers"
case intermediateSize = "intermediate_size"
case attentionHeads = "num_attention_heads"
case rmsNormEps = "rms_norm_eps"
case vocabularySize = "vocab_size"
case kvHeads = "num_key_value_heads"
case ropeTheta = "rope_theta"
case ropeTraditional = "rope_traditional"
case ropeScaling = "rope_scaling"
}
public init(from decoder: Decoder) throws {
// custom implementation to handle optional keys with required values
let container: KeyedDecodingContainer<Qwen2Configuration.CodingKeys> =
try decoder.container(
keyedBy: Qwen2Configuration.CodingKeys.self)
self.hiddenSize = try container.decode(
Int.self, forKey: Qwen2Configuration.CodingKeys.hiddenSize)
self.hiddenLayers = try container.decode(
Int.self, forKey: Qwen2Configuration.CodingKeys.hiddenLayers)
self.intermediateSize = try container.decode(
Int.self, forKey: Qwen2Configuration.CodingKeys.intermediateSize)
self.attentionHeads = try container.decode(
Int.self, forKey: Qwen2Configuration.CodingKeys.attentionHeads)
self.rmsNormEps = try container.decode(
Float.self, forKey: Qwen2Configuration.CodingKeys.rmsNormEps)
self.vocabularySize = try container.decode(
Int.self, forKey: Qwen2Configuration.CodingKeys.vocabularySize)
self.kvHeads = try container.decode(Int.self, forKey: Qwen2Configuration.CodingKeys.kvHeads)
self.ropeTheta =
try container.decodeIfPresent(
Float.self, forKey: Qwen2Configuration.CodingKeys.ropeTheta)
?? 1_000_000
self.ropeTraditional =
try container.decodeIfPresent(
Bool.self, forKey: Qwen2Configuration.CodingKeys.ropeTraditional) ?? false
self.ropeScaling = try container.decodeIfPresent(
[String: StringOrNumber].self, forKey: Qwen2Configuration.CodingKeys.ropeScaling)
}
}

1
Libraries/LLM/Tokenizer.swift
View File

@@ -116,4 +116,5 @@ public func discardUnhandledMerges(tokenizerData: Config) -> Config {
let replacementTokenizers = [
"CodeLlamaTokenizer": "LlamaTokenizer",
"GemmaTokenizer": "PreTrainedTokenizer",
"Qwen2Tokenizer": "PreTrainedTokenizer",
]

4
Tools/llm-tool/LLMTool.swift
View File

@@ -43,6 +43,8 @@ struct SyncGenerator: AsyncParsableCommand {
let modelConfiguration = ModelConfiguration.configuration(id: model)
let (model, tokenizer) = try await load(configuration: modelConfiguration)
print("Model loaded -> \(self.model)")
let prompt = modelConfiguration.prepare(prompt: self.prompt)
let promptTokens = tokenizer.encode(text: prompt)
@@ -132,6 +134,8 @@ struct AsyncGenerator: AsyncParsableCommand {
let modelConfiguration = ModelConfiguration.configuration(id: model)
let (model, tokenizer) = try await load(configuration: modelConfiguration)
print("Model loaded -> \(self.model)")
let prompt = modelConfiguration.prepare(prompt: self.prompt)
let promptTokens = tokenizer.encode(text: prompt)

4
mlx-swift-examples.xcodeproj/project.pbxproj
View File

@@ -7,6 +7,7 @@
objects = {
/* Begin PBXBuildFile section */
52A776182B94B5EE00AA6E80 /* Qwen2.swift in Sources */ = {isa = PBXBuildFile; fileRef = 52A776172B94B5EE00AA6E80 /* Qwen2.swift */; };
C3288D762B6D9313009FF608 /* LinearModelTraining.swift in Sources */ = {isa = PBXBuildFile; fileRef = C3288D752B6D9313009FF608 /* LinearModelTraining.swift */; };
C3288D7B2B6D9339009FF608 /* ArgumentParser in Frameworks */ = {isa = PBXBuildFile; productRef = C3288D7A2B6D9339009FF608 /* ArgumentParser */; };
C34E48F52B696F0B00FCB841 /* LLMTool.swift in Sources */ = {isa = PBXBuildFile; fileRef = C34E48F42B696F0B00FCB841 /* LLMTool.swift */; };
@@ -180,6 +181,7 @@
/* End PBXCopyFilesBuildPhase section */
/* Begin PBXFileReference section */
52A776172B94B5EE00AA6E80 /* Qwen2.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Qwen2.swift; sourceTree = "<group>"; };
C325DE3F2B648CDB00628871 /* README.md */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = net.daringfireball.markdown; path = README.md; sourceTree = "<group>"; };
C3288D732B6D9313009FF608 /* LinearModelTraining */ = {isa = PBXFileReference; explicitFileType = "compiled.mach-o.executable"; includeInIndex = 0; path = LinearModelTraining; sourceTree = BUILT_PRODUCTS_DIR; };
C3288D752B6D9313009FF608 /* LinearModelTraining.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = LinearModelTraining.swift; sourceTree = "<group>"; };
@@ -363,6 +365,7 @@
C34E48ED2B696E6500FCB841 /* Load.swift */,
C3E786AA2B8D1AEC0004D037 /* Evaluate.swift */,
C3E786AC2B8D4AF50004D037 /* Tokenizer.swift */,
52A776172B94B5EE00AA6E80 /* Qwen2.swift */,
);
path = LLM;
sourceTree = "<group>";
@@ -829,6 +832,7 @@
C3A8B3AC2B9283150002EFB8 /* Models.swift in Sources */,
C3E786AB2B8D1AEC0004D037 /* Evaluate.swift in Sources */,
C38935CC2B869C870037B833 /* Llama.swift in Sources */,
52A776182B94B5EE00AA6E80 /* Qwen2.swift in Sources */,
);
runOnlyForDeploymentPostprocessing = 0;
};

6
mlx-swift-examples.xcodeproj/xcshareddata/xcschemes/llm-tool.xcscheme
View File

@@ -55,6 +55,10 @@
argument = "--model mlx-community/CodeLlama-13b-Instruct-hf-4bit-MLX"
isEnabled = "NO">
</CommandLineArgument>
<CommandLineArgument
argument = "--model mlx-community/Qwen1.5-0.5B-Chat-4bit"
isEnabled = "YES">
</CommandLineArgument>
<CommandLineArgument
argument = "--prompt &apos;func sortArray(_ array: [Int]) -&gt; String { &lt;FILL_ME&gt; }&apos;"
isEnabled = "NO">
@@ -69,7 +73,7 @@
</CommandLineArgument>
<CommandLineArgument
argument = "--model mlx-community/phi-2-hf-4bit-mlx"
isEnabled = "YES">
isEnabled = "NO">
</CommandLineArgument>
</CommandLineArguments>
</LaunchAction>