Read model weights

Package.swift

@@ -29,8 +29,8 @@ let package = Package(
         .testTarget(name: "TokenizersTests", dependencies: ["Tokenizers", "Models", "Hub"], resources: [.process("Resources"), .process("Vocabs")]),
         .testTarget(name: "HubTests", dependencies: ["Hub"]),
         .testTarget(name: "PreTokenizerTests", dependencies: ["Tokenizers", "Hub"]),
-        .testTarget(name: "TensorUtilsTests", dependencies: ["TensorUtils"]),
+        .testTarget(name: "TensorUtilsTests", dependencies: ["TensorUtils", "Models", "Hub"], resources: [.process("Resources")]),
         .testTarget(name: "NormalizerTests", dependencies: ["Tokenizers", "Hub"]),
-        .testTarget(name: "PostProcessorTests", dependencies: ["Tokenizers", "Hub"])
+        .testTarget(name: "PostProcessorTests", dependencies: ["Tokenizers", "Hub"]),
     ]
 )

Sources/Models/LanguageModel.swift

@@ -24,7 +24,7 @@ public class LanguageModel {
         var tokenizerConfig: Config?
         var tokenizerData: Config
     }
-    
+
     private var configuration: LanguageModelConfigurationFromHub? = nil
     private var _tokenizer: Tokenizer? = nil
 

Sources/TensorUtils/Weights.swift

@@ -0,0 +1,88 @@
+import CoreML
+
+
+struct Weights {
+
+    enum WeightsError: Error {
+        case notSupported(message: String)
+        case invalidFile
+    }
+
+    private let dictionary: [String: MLMultiArray]
+
+    init(_ dictionary: [String: MLMultiArray]) {
+        self.dictionary = dictionary
+    }
+
+    subscript(key: String) -> MLMultiArray { dictionary[key]! }
+
+    static func from(fileURL: URL) throws -> Weights {
+        guard ["safetensors", "gguf", "mlx"].contains(fileURL.pathExtension)
+        else { throw WeightsError.notSupported(message: "\(fileURL.pathExtension)") }
+
+        let data = try Data(contentsOf: fileURL, options: .mappedIfSafe)
+        switch ([UInt8](data.subdata(in: 0..<4)), [UInt8](data.subdata(in: 4..<6))) {
+        case ([0x47, 0x47, 0x55, 0x46], _): throw WeightsError.notSupported(message: ("gguf"))
+        case ([0x93, 0x4e, 0x55, 0x4d], [0x50, 0x59]): throw WeightsError.notSupported(message: "mlx")
+        default: return try Safetensor.from(data: data)
+        }
+    }
+}
+
+struct Safetensor {
+
+    typealias Error = Weights.WeightsError
+
+    struct Header {
+
+        struct Offset: Decodable {
+            let dataOffsets: [Int]?
+            let dtype: String?
+            let shape: [Int]?
+
+            /// Unsupported: "I8", "U8", "I16", "U16", "BF16"
+            var dataType: MLMultiArrayDataType? {
+                get throws {
+                    switch dtype {
+                    case "I32", "U32": .int32
+                    case "F16": .float16
+                    case "F32": .float32
+                    case "F64", "U64": .float64
+                    default: throw Error.notSupported(message: "\(dtype ?? "empty")")
+                    }
+                }
+            }
+        }
+
+        static func from(data: Data) throws -> [String: Offset?] {
+            let decoder = JSONDecoder()
+            decoder.keyDecodingStrategy = .convertFromSnakeCase
+            return try decoder.decode([String: Offset?].self, from: data)
+        }
+    }
+
+    static func from(data: Data) throws -> Weights {
+        let headerSize: Int = data.subdata(in: 0..<8).withUnsafeBytes({ $0.load(as: Int.self) })
+        guard headerSize < data.count else { throw Error.invalidFile }
+        let header = try Header.from(data: data.subdata(in: 8..<(headerSize + 8)))
+
+        var dict = [String: MLMultiArray]()
+        for (key, point) in header {
+            guard let offsets = point?.dataOffsets, offsets.count == 2,
+                  let shape = point?.shape as? [NSNumber],
+                  let dType = try point?.dataType
+            else { continue }
+
+            let strides = shape.dropFirst().reversed().reduce(into: [1]) { acc, a in
+                acc.insert(acc[0].intValue * a.intValue as NSNumber, at: 0)
+            }
+            let start = 8 + offsets[0] + headerSize
+            let end = 8 + offsets[1] + headerSize
+            let tensorData = data.subdata(in: start..<end) as NSData
+            let ptr = UnsafeMutableRawPointer(mutating: tensorData.bytes)
+            dict[key] = try MLMultiArray(dataPointer: ptr, shape: shape, dataType: dType, strides: strides)
+        }
+
+        return Weights(dict)
+    }
+}

Tests/TensorUtilsTests/WeightsTests.swift

@@ -0,0 +1,104 @@
+@testable import TensorUtils
+@testable import Hub
+import XCTest
+
+class WeightsTests: XCTestCase {
+
+    let downloadDestination: URL = {
+        FileManager.default.urls(for: .cachesDirectory, in: .userDomainMask).first!.appending(component: "huggingface-tests")
+    }()
+
+    var hubApi: HubApi { HubApi(downloadBase: downloadDestination) }
+
+    func testLoadWeightsFromFileURL() async throws {
+        let repo = "google/bert_uncased_L-2_H-128_A-2"
+        let modelDir = try await hubApi.snapshot(from: repo)
+
+        let files = try FileManager.default.contentsOfDirectory(at: modelDir, includingPropertiesForKeys: [.isReadableKey])
+        XCTAssertTrue(files.contains(where: { $0.lastPathComponent == "config.json" }))
+        XCTAssertTrue(files.contains(where: { $0.lastPathComponent == "model.safetensors" }))
+
+        let modelFile = modelDir.appending(path: "/model.safetensors")
+        let weights = try Weights.from(fileURL: modelFile)
+        XCTAssertEqual(weights["bert.embeddings.LayerNorm.bias"].dataType, .float32)
+        XCTAssertEqual(weights["bert.embeddings.LayerNorm.bias"].count, 128)
+        XCTAssertEqual(weights["bert.embeddings.LayerNorm.bias"].shape.count, 1)
+
+        XCTAssertEqual(weights["bert.embeddings.word_embeddings.weight"].dataType, .float32)
+        XCTAssertEqual(weights["bert.embeddings.word_embeddings.weight"].count, 3906816)
+        XCTAssertEqual(weights["bert.embeddings.word_embeddings.weight"].shape.count, 2)
+
+        XCTAssertEqual(weights["bert.embeddings.word_embeddings.weight"][[0, 0]].floatValue, -0.0041, accuracy: 1e-3)
+        XCTAssertEqual(weights["bert.embeddings.word_embeddings.weight"][[3, 4]].floatValue, 0.0037, accuracy: 1e-3)
+        XCTAssertEqual(weights["bert.embeddings.word_embeddings.weight"][[5, 3]].floatValue, -0.5371, accuracy: 1e-3)
+        XCTAssertEqual(weights["bert.embeddings.word_embeddings.weight"][[7, 8]].floatValue, 0.0460, accuracy: 1e-3)
+        XCTAssertEqual(weights["bert.embeddings.word_embeddings.weight"][[11, 7]].floatValue, -0.0058, accuracy: 1e-3)
+    }
+
+    func testSafetensorReadTensor1D() throws {
+        let modelFile = Bundle.module.url(forResource: "tensor-1d-int32", withExtension: "safetensors")!
+        let weights: Weights = try Weights.from(fileURL: modelFile)
+        let tensor = weights["embedding"]
+        XCTAssertEqual(tensor.dataType, .int32)
+        XCTAssertEqual(tensor[[0]], 1)
+        XCTAssertEqual(tensor[[1]], 2)
+        XCTAssertEqual(tensor[[2]], 3)
+    }
+
+    func testSafetensorReadTensor2D() throws {
+        let modelFile = Bundle.module.url(forResource: "tensor-2d-float64", withExtension: "safetensors")!
+        let weights: Weights = try Weights.from(fileURL: modelFile)
+        let tensor = weights["embedding"]
+        XCTAssertEqual(tensor.dataType, .float64)
+        XCTAssertEqual(tensor[[0, 0]], 1)
+        XCTAssertEqual(tensor[[0, 1]], 2)
+        XCTAssertEqual(tensor[[0, 2]], 3)
+        XCTAssertEqual(tensor[[1, 0]], 24)
+        XCTAssertEqual(tensor[[1, 1]], 25)
+        XCTAssertEqual(tensor[[1, 2]], 26)
+    }
+
+    func testSafetensorReadTensor3D() throws {
+        let modelFile = Bundle.module.url(forResource: "tensor-3d-float32", withExtension: "safetensors")!
+        let weights: Weights = try Weights.from(fileURL: modelFile)
+        let tensor = weights["embedding"]
+        XCTAssertEqual(tensor.dataType, .float32)
+        XCTAssertEqual(tensor[[0, 0, 0]], 22)
+        XCTAssertEqual(tensor[[0, 0, 1]], 23)
+        XCTAssertEqual(tensor[[0, 0, 2]], 24)
+        XCTAssertEqual(tensor[[0, 1, 0]], 11)
+        XCTAssertEqual(tensor[[0, 1, 1]], 12)
+        XCTAssertEqual(tensor[[0, 1, 2]], 13)
+        XCTAssertEqual(tensor[[1, 0, 0]], 2)
+        XCTAssertEqual(tensor[[1, 0, 1]], 3)
+        XCTAssertEqual(tensor[[1, 0, 2]], 4)
+        XCTAssertEqual(tensor[[1, 1, 0]], 1)
+        XCTAssertEqual(tensor[[1, 1, 1]], 2)
+        XCTAssertEqual(tensor[[1, 1, 2]], 3)
+    }
+
+    func testSafetensorReadTensor4D() throws {
+        let modelFile = Bundle.module.url(forResource: "tensor-4d-float32", withExtension: "safetensors")!
+        let weights: Weights = try Weights.from(fileURL: modelFile)
+        let tensor = weights["embedding"]
+        XCTAssertEqual(tensor.dataType, .float32)
+        XCTAssertEqual(tensor[[0, 0, 0, 0]], 11)
+        XCTAssertEqual(tensor[[0, 0, 0, 1]], 12)
+        XCTAssertEqual(tensor[[0, 0, 0, 2]], 13)
+        XCTAssertEqual(tensor[[0, 0, 1, 0]], 1)
+        XCTAssertEqual(tensor[[0, 0, 1, 1]], 2)
+        XCTAssertEqual(tensor[[0, 0, 1, 2]], 3)
+        XCTAssertEqual(tensor[[0, 0, 2, 0]], 4)
+        XCTAssertEqual(tensor[[0, 0, 2, 1]], 5)
+        XCTAssertEqual(tensor[[0, 0, 2, 2]], 6)
+        XCTAssertEqual(tensor[[1, 0, 0, 0]], 22)
+        XCTAssertEqual(tensor[[1, 0, 0, 1]], 23)
+        XCTAssertEqual(tensor[[1, 0, 0, 2]], 24)
+        XCTAssertEqual(tensor[[1, 0, 1, 0]], 15)
+        XCTAssertEqual(tensor[[1, 0, 1, 1]], 16)
+        XCTAssertEqual(tensor[[1, 0, 1, 2]], 17)
+        XCTAssertEqual(tensor[[1, 0, 2, 0]], 17)
+        XCTAssertEqual(tensor[[1, 0, 2, 1]], 18)
+        XCTAssertEqual(tensor[[1, 0, 2, 2]], 19)
+    }
+}