feat: add command r model support (#35)

* feat: add command r model support

Libraries/LLM/Cohere.swift

@@ -0,0 +1,238 @@
+import Foundation
+import MLX
+import MLXFast
+import MLXNN
+
+// port of https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/models/cohere.py
+
+private class Attention: Module {
+
+    let args: CohereConfiguration
+    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: CohereConfiguration) {
+        self.args = args
+
+        let dim = args.hiddenSize
+        let heads = args.attentionHeads
+        let kvHeads = args.kvHeads
+
+        let headDim = args.hiddenSize / heads
+        self.scale = pow(Float(headDim), -0.5)
+
+        self._wq.wrappedValue = Linear(dim, heads * headDim, bias: false)
+        self._wk.wrappedValue = Linear(dim, kvHeads * headDim, bias: false)
+        self._wv.wrappedValue = Linear(dim, kvHeads * headDim, bias: false)
+        self._wo.wrappedValue = Linear(heads * headDim, dim, bias: false)
+
+        self.rope = RoPE(
+            dimensions: headDim, traditional: args.ropeTraditional, base: args.ropeTheta)
+    }
+
+    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 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)
+        }
+
+        let output = MLXFast.scaledDotProductAttention(
+            queries: queries, keys: keys, values: values, scale: scale, mask: mask
+        )
+        .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) {
+        self._gate.wrappedValue = Linear(dimensions, hiddenDimensions, bias: false)
+        self._up.wrappedValue = Linear(dimensions, hiddenDimensions, bias: false)
+        self._down.wrappedValue = Linear(hiddenDimensions, dimensions, 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: LayerNorm
+
+    public init(_ args: CohereConfiguration) {
+        self._attention.wrappedValue = Attention(args)
+        self.mlp = MLP(dimensions: args.hiddenSize, hiddenDimensions: args.intermediateSize)
+        self._inputLayerNorm.wrappedValue = LayerNorm(
+            dimensions: args.hiddenSize, eps: args.layerNormEps)
+
+    }
+
+    public func callAsFunction(
+        _ x: MLXArray, mask: MLXArray? = nil, cache: (MLXArray, MLXArray)? = nil
+    ) -> (MLXArray, (MLXArray, MLXArray)) {
+        let h = inputLayerNorm(x)
+        let (attnH, cache) = attention(h, mask: mask, cache: cache)
+        let ffH = mlp(h)
+        return (attnH + ffH + x, cache)
+    }
+}
+
+public class CohereModelInner: Module {
+
+    @ModuleInfo(key: "embed_tokens") var embedTokens: Embedding
+
+    fileprivate let layers: [TransformerBlock]
+    let norm: LayerNorm
+
+    public init(_ args: CohereConfiguration) {
+        precondition(args.vocabularySize > 0)
+
+        self._embedTokens.wrappedValue = Embedding(
+            embeddingCount: args.vocabularySize, dimensions: args.hiddenSize)
+
+        self.layers = (0 ..< args.hiddenLayers)
+            .map { _ in
+                TransformerBlock(args)
+            }
+        self.norm = LayerNorm(dimensions: args.hiddenSize, eps: args.layerNormEps)
+    }
+
+    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 CohereModel: Module, LLMModel {
+
+    public let vocabularySize: Int
+    let model: CohereModelInner
+    let logitScale: Float
+
+    public init(_ args: CohereConfiguration) {
+        self.vocabularySize = args.vocabularySize
+        self.model = CohereModelInner(args)
+        self.logitScale = args.logitScale
+    }
+
+    public func callAsFunction(_ inputs: MLXArray, cache: [(MLXArray, MLXArray)]?) -> (
+        MLXArray, [(MLXArray, MLXArray)]
+    ) {
+        var (out, cache) = model(inputs, cache: cache)
+        out = matmul(out, model.embedTokens.weight.T)
+        out = out * self.logitScale
+        return (out, cache)
+    }
+}
+
+public struct CohereConfiguration: Codable {
+
+    var hiddenSize: Int
+    var hiddenLayers: Int
+    var intermediateSize: Int
+    var attentionHeads: Int
+    var layerNormEps: Float
+    var vocabularySize: Int
+    var kvHeads: Int
+    var ropeTheta: Float = 8000000.0
+    var ropeTraditional: Bool = true
+    var ropeScaling: [String: StringOrNumber]? = nil
+    var logitScale: Float
+
+    enum CodingKeys: String, CodingKey {
+        case hiddenSize = "hidden_size"
+        case hiddenLayers = "num_hidden_layers"
+        case intermediateSize = "intermediate_size"
+        case attentionHeads = "num_attention_heads"
+        case kvHeads = "num_key_value_heads"
+        case ropeTheta = "rope_theta"
+        case vocabularySize = "vocab_size"
+        case layerNormEps = "layer_norm_eps"
+        case logitScale = "logit_scale"
+        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<CohereConfiguration.CodingKeys> =
+            try decoder.container(
+                keyedBy: CohereConfiguration.CodingKeys.self)
+
+        self.hiddenSize = try container.decode(
+            Int.self, forKey: CohereConfiguration.CodingKeys.hiddenSize)
+        self.hiddenLayers = try container.decode(
+            Int.self, forKey: CohereConfiguration.CodingKeys.hiddenLayers)
+        self.intermediateSize = try container.decode(
+            Int.self, forKey: CohereConfiguration.CodingKeys.intermediateSize)
+        self.attentionHeads = try container.decode(
+            Int.self, forKey: CohereConfiguration.CodingKeys.attentionHeads)
+        self.layerNormEps = try container.decode(
+            Float.self, forKey: CohereConfiguration.CodingKeys.layerNormEps)
+        self.vocabularySize = try container.decode(
+            Int.self, forKey: CohereConfiguration.CodingKeys.vocabularySize)
+        self.kvHeads = try container.decode(
+            Int.self, forKey: CohereConfiguration.CodingKeys.kvHeads)
+        self.ropeTheta =
+            try container.decodeIfPresent(
+                Float.self, forKey: CohereConfiguration.CodingKeys.ropeTheta)
+            ?? 8000000.0
+        self.ropeScaling = try container.decodeIfPresent(
+            [String: StringOrNumber].self, forKey: CohereConfiguration.CodingKeys.ropeScaling)
+        self.logitScale = try container.decode(
+            Float.self, forKey: CohereConfiguration.CodingKeys.logitScale)
+    }
+}

Libraries/LLM/Configuration.swift

@@ -33,6 +33,7 @@ public enum ModelType: String, Codable {
     case gemma
     case qwen2
     case starcoder2
+    case cohere
 
     func createModel(configuration: URL) throws -> LLMModel {
         switch self {
@@ -56,6 +57,10 @@ public enum ModelType: String, Codable {
             let configuration = try JSONDecoder().decode(
                 Starcoder2Configuration.self, from: Data(contentsOf: configuration))
             return Starcoder2Model(configuration)
+        case .cohere:
+            let configuration = try JSONDecoder().decode(
+                CohereConfiguration.self, from: Data(contentsOf: configuration))
+            return CohereModel(configuration)
         }
     }
 }

Libraries/LLM/Tokenizer.swift

@@ -28,5 +28,6 @@ public func loadTokenizer(configuration: ModelConfiguration) async throws -> Tok
 
 /// overrides for TokenizerModel/knownTokenizers
 let replacementTokenizers = [
-    "Qwen2Tokenizer": "PreTrainedTokenizer"
+    "Qwen2Tokenizer": "PreTrainedTokenizer",
+    "CohereTokenizer": "PreTrainedTokenizer",
 ]

mlx-swift-examples.xcodeproj/project.pbxproj

@@ -68,6 +68,7 @@
 		C3FBCB312B8520F20007E490 /* MLXNN in Frameworks */ = {isa = PBXBuildFile; productRef = C3FBCB302B8520F20007E490 /* MLXNN */; };
 		C3FBCB332B8520F20007E490 /* MLXOptimizers in Frameworks */ = {isa = PBXBuildFile; productRef = C3FBCB322B8520F20007E490 /* MLXOptimizers */; };
 		C3FBCB352B8520F20007E490 /* MLXRandom in Frameworks */ = {isa = PBXBuildFile; productRef = C3FBCB342B8520F20007E490 /* MLXRandom */; };
+		F24B083A2BAF1A65008C8D19 /* Cohere.swift in Sources */ = {isa = PBXBuildFile; fileRef = F24B08392BAF1A65008C8D19 /* Cohere.swift */; };
 /* End PBXBuildFile section */
 
 /* Begin PBXContainerItemProxy section */
@@ -234,6 +235,7 @@
 		C3C3240C2B6CA792007D2D9A /* README.md */ = {isa = PBXFileReference; lastKnownFileType = net.daringfireball.markdown; path = README.md; sourceTree = "<group>"; };
 		C3E786AA2B8D1AEC0004D037 /* Evaluate.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Evaluate.swift; sourceTree = "<group>"; };
 		C3E786AC2B8D4AF50004D037 /* Tokenizer.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Tokenizer.swift; sourceTree = "<group>"; };
+		F24B08392BAF1A65008C8D19 /* Cohere.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Cohere.swift; sourceTree = "<group>"; };
 /* End PBXFileReference section */
 
 /* Begin PBXFrameworksBuildPhase section */
@@ -383,6 +385,7 @@
 				C3E786AA2B8D1AEC0004D037 /* Evaluate.swift */,
 				C3E786AC2B8D4AF50004D037 /* Tokenizer.swift */,
 				52A776172B94B5EE00AA6E80 /* Qwen2.swift */,
+				F24B08392BAF1A65008C8D19 /* Cohere.swift */,
 			);
 			path = LLM;
 			sourceTree = "<group>";
@@ -847,6 +850,7 @@
 			buildActionMask = 2147483647;
 			files = (
 				C38935E12B869F420037B833 /* LLMModel.swift in Sources */,
+				F24B083A2BAF1A65008C8D19 /* Cohere.swift in Sources */,
 				C38935E32B86C0FE0037B833 /* Gemma.swift in Sources */,
 				C38935CD2B869C870037B833 /* Configuration.swift in Sources */,
 				525C1E9D2B9A011000B5C356 /* Starcoder2.swift in Sources */,

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

@@ -56,9 +56,13 @@
             isEnabled = "NO">
          </CommandLineArgument>
          <CommandLineArgument
-            argument = "--model mlx-community/starcoder2-3b-4bit"
+            argument = "--model mlx-community/c4ai-command-r-v01-4bit"
             isEnabled = "YES">
          </CommandLineArgument>
+         <CommandLineArgument
+            argument = "--model mlx-community/starcoder2-3b-4bit"
+            isEnabled = "NO">
+         </CommandLineArgument>
          <CommandLineArgument
             argument = "--model mlx-community/Qwen1.5-0.5B-Chat-4bit"
             isEnabled = "NO">