name: "whisper",
path: ".",
exclude: [
+ "build",
"bindings",
"cmake",
- "coreml",
"examples",
- "extra",
+ "scripts",
"models",
"samples",
"tests",
"CMakeLists.txt",
- "Makefile"
+ "Makefile",
+ "ggml/src/ggml-metal-embed.metal"
],
sources: [
"ggml/src/ggml.c",
"ggml/src/ggml-quants.c",
"ggml/src/ggml-metal.m"
],
- resources: [.process("ggml-metal.metal")],
+ resources: [.process("ggml/src/ggml-metal.metal")],
publicHeadersPath: "spm-headers",
cSettings: [
.unsafeFlags(["-Wno-shorten-64-to-32", "-O3", "-DNDEBUG"]),
import Foundation
+import UIKit
import whisper
enum WhisperError: Error {
return transcription
}
+ static func benchMemcpy(nThreads: Int32) async -> String {
+ return String.init(cString: whisper_bench_memcpy_str(nThreads))
+ }
+
+ static func benchGgmlMulMat(nThreads: Int32) async -> String {
+ return String.init(cString: whisper_bench_ggml_mul_mat_str(nThreads))
+ }
+
+ private func systemInfo() -> String {
+ var info = ""
+ if (ggml_cpu_has_neon() != 0) { info += "NEON " }
+ if (ggml_cpu_has_metal() != 0) { info += "METAL " }
+ if (ggml_cpu_has_blas() != 0) { info += "BLAS " }
+ return String(info.dropLast())
+ }
+
+ func benchFull(modelName: String, nThreads: Int32) async -> String {
+ let nMels = whisper_model_n_mels(context)
+ if (whisper_set_mel(context, nil, 0, nMels) != 0) {
+ return "error: failed to set mel"
+ }
+
+ // heat encoder
+ if (whisper_encode(context, 0, nThreads) != 0) {
+ return "error: failed to encode"
+ }
+
+ var tokens = [whisper_token](repeating: 0, count: 512)
+
+ // prompt heat
+ if (whisper_decode(context, &tokens, 256, 0, nThreads) != 0) {
+ return "error: failed to decode"
+ }
+
+ // text-generation heat
+ if (whisper_decode(context, &tokens, 1, 256, nThreads) != 0) {
+ return "error: failed to decode"
+ }
+
+ whisper_reset_timings(context)
+
+ // actual run
+ if (whisper_encode(context, 0, nThreads) != 0) {
+ return "error: failed to encode"
+ }
+
+ // text-generation
+ for i in 0..<256 {
+ if (whisper_decode(context, &tokens, 1, Int32(i), nThreads) != 0) {
+ return "error: failed to decode"
+ }
+ }
+
+ // batched decoding
+ for _ in 0..<64 {
+ if (whisper_decode(context, &tokens, 5, 0, nThreads) != 0) {
+ return "error: failed to decode"
+ }
+ }
+
+ // prompt processing
+ for _ in 0..<16 {
+ if (whisper_decode(context, &tokens, 256, 0, nThreads) != 0) {
+ return "error: failed to decode"
+ }
+ }
+
+ whisper_print_timings(context)
+
+ let deviceModel = await UIDevice.current.model
+ let systemName = await UIDevice.current.systemName
+ let systemInfo = self.systemInfo()
+ let timings: whisper_timings = whisper_get_timings(context).pointee
+ let encodeMs = String(format: "%.2f", timings.encode_ms)
+ let decodeMs = String(format: "%.2f", timings.decode_ms)
+ let batchdMs = String(format: "%.2f", timings.batchd_ms)
+ let promptMs = String(format: "%.2f", timings.prompt_ms)
+ return "| \(deviceModel) | \(systemName) | \(systemInfo) | \(modelName) | \(nThreads) | 1 | \(encodeMs) | \(decodeMs) | \(batchdMs) | \(promptMs) | <todo> |"
+ }
+
static func createContext(path: String) throws -> WhisperContext {
var params = whisper_context_default_params()
#if targetEnvironment(simulator)
params.use_gpu = false
print("Running on the simulator, using CPU")
+#else
+ params.flash_attn = true // Enabled by default for Metal
#endif
let context = whisper_init_from_file_with_params(path, params)
if let context {
--- /dev/null
+import Foundation
+
+struct Model: Identifiable {
+ var id = UUID()
+ var name: String
+ var info: String
+ var url: String
+
+ var filename: String
+ var fileURL: URL {
+ FileManager.default.urls(for: .documentDirectory, in: .userDomainMask)[0].appendingPathComponent(filename)
+ }
+
+ func fileExists() -> Bool {
+ FileManager.default.fileExists(atPath: fileURL.path)
+ }
+}
private var recordedFile: URL? = nil
private var audioPlayer: AVAudioPlayer?
- private var modelUrl: URL? {
+ private var builtInModelUrl: URL? {
Bundle.main.url(forResource: "ggml-base.en", withExtension: "bin", subdirectory: "models")
}
override init() {
super.init()
+ loadModel()
+ }
+
+ func loadModel(path: URL? = nil, log: Bool = true) {
do {
- try loadModel()
+ whisperContext = nil
+ if (log) { messageLog += "Loading model...\n" }
+ let modelUrl = path ?? builtInModelUrl
+ if let modelUrl {
+ whisperContext = try WhisperContext.createContext(path: modelUrl.path())
+ if (log) { messageLog += "Loaded model \(modelUrl.lastPathComponent)\n" }
+ } else {
+ if (log) { messageLog += "Could not locate model\n" }
+ }
canTranscribe = true
} catch {
print(error.localizedDescription)
- messageLog += "\(error.localizedDescription)\n"
+ if (log) { messageLog += "\(error.localizedDescription)\n" }
}
}
-
- private func loadModel() throws {
- messageLog += "Loading model...\n"
- if let modelUrl {
- whisperContext = try WhisperContext.createContext(path: modelUrl.path())
- messageLog += "Loaded model \(modelUrl.lastPathComponent)\n"
- } else {
- messageLog += "Could not locate model\n"
+
+ func benchCurrentModel() async {
+ if whisperContext == nil {
+ messageLog += "Cannot bench without loaded model\n"
+ return
}
+ messageLog += "Running benchmark for loaded model\n"
+ let result = await whisperContext?.benchFull(modelName: "<current>", nThreads: Int32(min(4, cpuCount())))
+ if (result != nil) { messageLog += result! + "\n" }
+ }
+
+ func bench(models: [Model]) async {
+ let nThreads = Int32(min(4, cpuCount()))
+
+// messageLog += "Running memcpy benchmark\n"
+// messageLog += await WhisperContext.benchMemcpy(nThreads: nThreads) + "\n"
+//
+// messageLog += "Running ggml_mul_mat benchmark with \(nThreads) threads\n"
+// messageLog += await WhisperContext.benchGgmlMulMat(nThreads: nThreads) + "\n"
+
+ messageLog += "Running benchmark for all downloaded models\n"
+ messageLog += "| CPU | OS | Config | Model | Th | FA | Enc. | Dec. | Bch5 | PP | Commit |\n"
+ messageLog += "| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n"
+ for model in models {
+ loadModel(path: model.fileURL, log: false)
+ if whisperContext == nil {
+ messageLog += "Cannot bench without loaded model\n"
+ break
+ }
+ let result = await whisperContext?.benchFull(modelName: model.name, nThreads: nThreads)
+ if (result != nil) { messageLog += result! + "\n" }
+ }
+ messageLog += "Benchmarking completed\n"
}
func transcribeSample() async {
isRecording = false
}
}
+
+
+fileprivate func cpuCount() -> Int {
+ ProcessInfo.processInfo.processorCount
+}
import SwiftUI
import AVFoundation
+import Foundation
struct ContentView: View {
@StateObject var whisperState = WhisperState()
Text(verbatim: whisperState.messageLog)
.frame(maxWidth: .infinity, alignment: .leading)
}
+ .font(.footnote)
+ .padding()
+ .background(Color.gray.opacity(0.1))
+ .cornerRadius(10)
+
+ HStack {
+ Button("Clear Logs", action: {
+ whisperState.messageLog = ""
+ })
+ .font(.footnote)
+ .buttonStyle(.bordered)
+
+ Button("Copy Logs", action: {
+ UIPasteboard.general.string = whisperState.messageLog
+ })
+ .font(.footnote)
+ .buttonStyle(.bordered)
+
+ Button("Bench", action: {
+ Task {
+ await whisperState.benchCurrentModel()
+ }
+ })
+ .font(.footnote)
+ .buttonStyle(.bordered)
+ .disabled(!whisperState.canTranscribe)
+
+ Button("Bench All", action: {
+ Task {
+ await whisperState.bench(models: ModelsView.getDownloadedModels())
+ }
+ })
+ .font(.footnote)
+ .buttonStyle(.bordered)
+ .disabled(!whisperState.canTranscribe)
+ }
+
+ NavigationLink(destination: ModelsView(whisperState: whisperState)) {
+ Text("View Models")
+ }
+ .font(.footnote)
+ .padding()
}
.navigationTitle("Whisper SwiftUI Demo")
.padding()
}
}
-}
-struct ContentView_Previews: PreviewProvider {
- static var previews: some View {
- ContentView()
+ struct ModelsView: View {
+ @ObservedObject var whisperState: WhisperState
+ @Environment(\.dismiss) var dismiss
+
+ private static let models: [Model] = [
+ Model(name: "tiny", info: "(F16, 75 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.bin", filename: "tiny.bin"),
+ Model(name: "tiny-q5_1", info: "(31 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny-q5_1.bin", filename: "tiny-q5_1.bin"),
+ Model(name: "tiny-q8_0", info: "(42 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny-q8_0.bin", filename: "tiny-q8_0.bin"),
+ Model(name: "tiny.en", info: "(F16, 75 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en.bin", filename: "tiny.en.bin"),
+ Model(name: "tiny.en-q5_1", info: "(31 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en-q5_1.bin", filename: "tiny.en-q5_1.bin"),
+ Model(name: "tiny.en-q8_0", info: "(42 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en-q8_0.bin", filename: "tiny.en-q8_0.bin"),
+ Model(name: "base", info: "(F16, 142 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin", filename: "base.bin"),
+ Model(name: "base-q5_1", info: "(57 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base-q5_1.bin", filename: "base-q5_1.bin"),
+ Model(name: "base-q8_0", info: "(78 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base-q8_0.bin", filename: "base-q8_0.bin"),
+ Model(name: "base.en", info: "(F16, 142 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin", filename: "base.en.bin"),
+ Model(name: "base.en-q5_1", info: "(57 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en-q5_1.bin", filename: "base.en-q5_1.bin"),
+ Model(name: "base.en-q8_0", info: "(78 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en-q8_0.bin", filename: "base.en-q8_0.bin"),
+ Model(name: "small", info: "(F16, 466 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.bin", filename: "small.bin"),
+ Model(name: "small-q5_1", info: "(181 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small-q5_1.bin", filename: "small-q5_1.bin"),
+ Model(name: "small-q8_0", info: "(252 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small-q8_0.bin", filename: "small-q8_0.bin"),
+ Model(name: "small.en", info: "(F16, 466 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.en.bin", filename: "small.en.bin"),
+ Model(name: "small.en-q5_1", info: "(181 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.en-q5_1.bin", filename: "small.en-q5_1.bin"),
+ Model(name: "small.en-q8_0", info: "(252 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.en-q8_0.bin", filename: "small.en-q8_0.bin"),
+ Model(name: "medium", info: "(F16, 1.5 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.bin", filename: "medium.bin"),
+ Model(name: "medium-q5_0", info: "(514 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium-q5_0.bin", filename: "medium-q5_0.bin"),
+ Model(name: "medium-q8_0", info: "(785 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium-q8_0.bin", filename: "medium-q8_0.bin"),
+ Model(name: "medium.en", info: "(F16, 1.5 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.en.bin", filename: "medium.en.bin"),
+ Model(name: "medium.en-q5_0", info: "(514 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.en-q5_0.bin", filename: "medium.en-q5_0.bin"),
+ Model(name: "medium.en-q8_0", info: "(785 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.en-q8_0.bin", filename: "medium.en-q8_0.bin"),
+ Model(name: "large-v1", info: "(F16, 2.9 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large.bin", filename: "large.bin"),
+ Model(name: "large-v2", info: "(F16, 2.9 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v2.bin", filename: "large-v2.bin"),
+ Model(name: "large-v2-q5_0", info: "(1.1 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v2-q5_0.bin", filename: "large-v2-q5_0.bin"),
+ Model(name: "large-v2-q8_0", info: "(1.5 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v2-q8_0.bin", filename: "large-v2-q8_0.bin"),
+ Model(name: "large-v3", info: "(F16, 2.9 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3.bin", filename: "large-v3.bin"),
+ Model(name: "large-v3-q5_0", info: "(1.1 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-q5_0.bin", filename: "large-v3-q5_0.bin"),
+ Model(name: "large-v3-turbo", info: "(F16, 1.5 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo.bin", filename: "large-v3-turbo.bin"),
+ Model(name: "large-v3-turbo-q5_0", info: "(547 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo-q5_0.bin", filename: "large-v3-turbo-q5_0.bin"),
+ Model(name: "large-v3-turbo-q8_0", info: "(834 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo-q8_0.bin", filename: "large-v3-turbo-q8_0.bin"),
+ ]
+
+ static func getDownloadedModels() -> [Model] {
+ // Filter models that have been downloaded
+ return models.filter {
+ FileManager.default.fileExists(atPath: $0.fileURL.path())
+ }
+ }
+
+ func loadModel(model: Model) {
+ Task {
+ dismiss()
+ whisperState.loadModel(path: model.fileURL)
+ }
+ }
+
+ var body: some View {
+ List {
+ Section(header: Text("Models")) {
+ ForEach(ModelsView.models) { model in
+ DownloadButton(model: model)
+ .onLoad(perform: loadModel)
+ }
+ }
+ }
+ .listStyle(GroupedListStyle())
+ .navigationBarTitle("Models", displayMode: .inline).toolbar {}
+ }
}
}
+
+//struct ContentView_Previews: PreviewProvider {
+// static var previews: some View {
+// ContentView()
+// }
+//}
--- /dev/null
+import SwiftUI
+
+struct DownloadButton: View {
+ private var model: Model
+
+ @State private var status: String
+
+ @State private var downloadTask: URLSessionDownloadTask?
+ @State private var progress = 0.0
+ @State private var observation: NSKeyValueObservation?
+
+ private var onLoad: ((_ model: Model) -> Void)?
+
+ init(model: Model) {
+ self.model = model
+ status = model.fileExists() ? "downloaded" : "download"
+ }
+
+ func onLoad(perform action: @escaping (_ model: Model) -> Void) -> DownloadButton {
+ var button = self
+ button.onLoad = action
+ return button
+ }
+
+ private func download() {
+ status = "downloading"
+ print("Downloading model \(model.name) from \(model.url)")
+ guard let url = URL(string: model.url) else { return }
+
+ downloadTask = URLSession.shared.downloadTask(with: url) { temporaryURL, response, error in
+ if let error = error {
+ print("Error: \(error.localizedDescription)")
+ return
+ }
+
+ guard let response = response as? HTTPURLResponse, (200...299).contains(response.statusCode) else {
+ print("Server error!")
+ return
+ }
+
+ do {
+ if let temporaryURL = temporaryURL {
+ try FileManager.default.copyItem(at: temporaryURL, to: model.fileURL)
+ print("Writing to \(model.filename) completed")
+ status = "downloaded"
+ }
+ } catch let err {
+ print("Error: \(err.localizedDescription)")
+ }
+ }
+
+ observation = downloadTask?.progress.observe(\.fractionCompleted) { progress, _ in
+ self.progress = progress.fractionCompleted
+ }
+
+ downloadTask?.resume()
+ }
+
+ var body: some View {
+ VStack {
+ Button(action: {
+ if (status == "download") {
+ download()
+ } else if (status == "downloading") {
+ downloadTask?.cancel()
+ status = "download"
+ } else if (status == "downloaded") {
+ if !model.fileExists() {
+ download()
+ }
+ onLoad?(model)
+ }
+ }) {
+ let title = "\(model.name) \(model.info)"
+ if (status == "download") {
+ Text("Download \(title)")
+ } else if (status == "downloading") {
+ Text("\(title) (Downloading \(Int(progress * 100))%)")
+ } else if (status == "downloaded") {
+ Text("Load \(title)")
+ } else {
+ Text("Unknown status")
+ }
+ }.swipeActions {
+ if (status == "downloaded") {
+ Button("Delete") {
+ do {
+ try FileManager.default.removeItem(at: model.fileURL)
+ } catch {
+ print("Error deleting file: \(error)")
+ }
+ status = "download"
+ }
+ .tint(.red)
+ }
+ }
+ }
+ .onDisappear() {
+ downloadTask?.cancel()
+ }
+ }
+}
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children = (
0AAC5DCD2953A05C003032C3 /* WhisperState.swift */,
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);
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0AAC5D9C29539CCF003032C3 /* ContentView.swift */,
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);
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0AAC5DD12953A394003032C3 /* LibWhisper.swift in Sources */,
0AA7514C2953B569001EE061 /* RiffWaveUtils.swift in Sources */,
+ 7F79E0EE2CE0A78000ACD7BF /* DownloadButton.swift in Sources */,
0AA7514E2953D958001EE061 /* Recorder.swift in Sources */,
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);
runOnlyForDeploymentPostprocessing = 0;
};
WHISPER_API whisper_token whisper_token_transcribe(struct whisper_context * ctx);
// Performance information from the default state.
+ struct whisper_timings {
+ float sample_ms;
+ float encode_ms;
+ float decode_ms;
+ float batchd_ms;
+ float prompt_ms;
+ };
+ WHISPER_API struct whisper_timings * whisper_get_timings(struct whisper_context * ctx);
WHISPER_API void whisper_print_timings(struct whisper_context * ctx);
WHISPER_API void whisper_reset_timings(struct whisper_context * ctx);
return ctx->vocab.token_transcribe;
}
+struct whisper_timings * whisper_get_timings(struct whisper_context * ctx) {
+ if (ctx->state == nullptr) {
+ return nullptr;
+ }
+ whisper_timings * timings = new whisper_timings;
+ timings->sample_ms = 1e-3f * ctx->state->t_sample_us / std::max(1, ctx->state->n_sample);
+ timings->encode_ms = 1e-3f * ctx->state->t_encode_us / std::max(1, ctx->state->n_encode);
+ timings->decode_ms = 1e-3f * ctx->state->t_decode_us / std::max(1, ctx->state->n_decode);
+ timings->batchd_ms = 1e-3f * ctx->state->t_batchd_us / std::max(1, ctx->state->n_batchd);
+ timings->prompt_ms = 1e-3f * ctx->state->t_prompt_us / std::max(1, ctx->state->n_prompt);
+ return timings;
+}
+
void whisper_print_timings(struct whisper_context * ctx) {
const int64_t t_end_us = ggml_time_us();
overview / pkg / ggml / sources / whisper.cpp / commitdiff