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swift : fix llama-vocab api usage (#11645)

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* swiftui : fix vocab api usage

* batched.swift : fix vocab api usage
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Jhen-Jie Hong 2025-02-04 19:15:24 +08:00 committed by GitHub
parent 534c46b53c
commit f117d84b48
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2 changed files with 17 additions and 10 deletions
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15
examples/batched.swift/Sources/main.swift
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@ -31,6 +31,11 @@ defer {
llama_model_free(model) llama_model_free(model)
} }
guard let vocab = llama_model_get_vocab(model) else {
print("Failed to get vocab")
exit(1)
}
var tokens = tokenize(text: prompt, add_bos: true) var tokens = tokenize(text: prompt, add_bos: true)
let n_kv_req = UInt32(tokens.count) + UInt32((n_len - Int(tokens.count)) * n_parallel) let n_kv_req = UInt32(tokens.count) + UInt32((n_len - Int(tokens.count)) * n_parallel)
@ -41,7 +46,7 @@ context_params.n_batch = UInt32(max(n_len, n_parallel))
context_params.n_threads = 8 context_params.n_threads = 8
context_params.n_threads_batch = 8 context_params.n_threads_batch = 8
let context = llama_new_context_with_model(model, context_params) let context = llama_init_from_model(model, context_params)
guard context != nil else { guard context != nil else {
print("Failed to initialize context") print("Failed to initialize context")
exit(1) exit(1)
@ -141,7 +146,7 @@ while n_cur <= n_len {
let new_token_id = llama_sampler_sample(smpl, context, i_batch[i]) let new_token_id = llama_sampler_sample(smpl, context, i_batch[i])
// is it an end of stream? -> mark the stream as finished // is it an end of stream? -> mark the stream as finished
if llama_vocab_is_eog(model, new_token_id) || n_cur == n_len { if llama_vocab_is_eog(vocab, new_token_id) || n_cur == n_len {
i_batch[i] = -1 i_batch[i] = -1
// print("") // print("")
if n_parallel > 1 { if n_parallel > 1 {
@ -207,7 +212,7 @@ private func tokenize(text: String, add_bos: Bool) -> [llama_token] {
let utf8Count = text.utf8.count let utf8Count = text.utf8.count
let n_tokens = utf8Count + (add_bos ? 1 : 0) let n_tokens = utf8Count + (add_bos ? 1 : 0)
let tokens = UnsafeMutablePointer<llama_token>.allocate(capacity: n_tokens) let tokens = UnsafeMutablePointer<llama_token>.allocate(capacity: n_tokens)
let tokenCount = llama_tokenize(model, text, Int32(utf8Count), tokens, Int32(n_tokens), add_bos, /*special tokens*/ false) let tokenCount = llama_tokenize(vocab, text, Int32(utf8Count), tokens, Int32(n_tokens), add_bos, /*special tokens*/ false)
var swiftTokens: [llama_token] = [] var swiftTokens: [llama_token] = []
for i in 0 ..< tokenCount { for i in 0 ..< tokenCount {
swiftTokens.append(tokens[Int(i)]) swiftTokens.append(tokens[Int(i)])
@ -218,12 +223,12 @@ private func tokenize(text: String, add_bos: Bool) -> [llama_token] {
private func token_to_piece(token: llama_token, buffer: inout [CChar]) -> String? { private func token_to_piece(token: llama_token, buffer: inout [CChar]) -> String? {
var result = [CChar](repeating: 0, count: 8) var result = [CChar](repeating: 0, count: 8)
let nTokens = llama_token_to_piece(model, token, &result, Int32(result.count), 0, false) let nTokens = llama_token_to_piece(vocab, token, &result, Int32(result.count), 0, false)
if nTokens < 0 { if nTokens < 0 {
let actualTokensCount = -Int(nTokens) let actualTokensCount = -Int(nTokens)
result = .init(repeating: 0, count: actualTokensCount) result = .init(repeating: 0, count: actualTokensCount)
let check = llama_token_to_piece( let check = llama_token_to_piece(
model, vocab,
token, token,
&result, &result,
Int32(result.count), Int32(result.count),

12
examples/llama.swiftui/llama.cpp.swift/LibLlama.swift
View File

@ -24,6 +24,7 @@ func llama_batch_add(_ batch: inout llama_batch, _ id: llama_token, _ pos: llama
actor LlamaContext { actor LlamaContext {
private var model: OpaquePointer private var model: OpaquePointer
private var context: OpaquePointer private var context: OpaquePointer
private var vocab: OpaquePointer
private var sampling: UnsafeMutablePointer<llama_sampler> private var sampling: UnsafeMutablePointer<llama_sampler>
private var batch: llama_batch private var batch: llama_batch
private var tokens_list: [llama_token] private var tokens_list: [llama_token]
@ -47,6 +48,7 @@ actor LlamaContext {
self.sampling = llama_sampler_chain_init(sparams) self.sampling = llama_sampler_chain_init(sparams)
llama_sampler_chain_add(self.sampling, llama_sampler_init_temp(0.4)) llama_sampler_chain_add(self.sampling, llama_sampler_init_temp(0.4))
llama_sampler_chain_add(self.sampling, llama_sampler_init_dist(1234)) llama_sampler_chain_add(self.sampling, llama_sampler_init_dist(1234))
vocab = llama_model_get_vocab(model)
} }
deinit { deinit {
@ -79,7 +81,7 @@ actor LlamaContext {
ctx_params.n_threads = Int32(n_threads) ctx_params.n_threads = Int32(n_threads)
ctx_params.n_threads_batch = Int32(n_threads) ctx_params.n_threads_batch = Int32(n_threads)
let context = llama_new_context_with_model(model, ctx_params) let context = llama_init_from_model(model, ctx_params)
guard let context else { guard let context else {
print("Could not load context!") print("Could not load context!")
throw LlamaError.couldNotInitializeContext throw LlamaError.couldNotInitializeContext
@ -151,7 +153,7 @@ actor LlamaContext {
new_token_id = llama_sampler_sample(sampling, context, batch.n_tokens - 1) new_token_id = llama_sampler_sample(sampling, context, batch.n_tokens - 1)
if llama_vocab_is_eog(model, new_token_id) || n_cur == n_len { if llama_vocab_is_eog(vocab, new_token_id) || n_cur == n_len {
print("\n") print("\n")
is_done = true is_done = true
let new_token_str = String(cString: temporary_invalid_cchars + [0]) let new_token_str = String(cString: temporary_invalid_cchars + [0])
@ -297,7 +299,7 @@ actor LlamaContext {
let utf8Count = text.utf8.count let utf8Count = text.utf8.count
let n_tokens = utf8Count + (add_bos ? 1 : 0) + 1 let n_tokens = utf8Count + (add_bos ? 1 : 0) + 1
let tokens = UnsafeMutablePointer<llama_token>.allocate(capacity: n_tokens) let tokens = UnsafeMutablePointer<llama_token>.allocate(capacity: n_tokens)
let tokenCount = llama_tokenize(model, text, Int32(utf8Count), tokens, Int32(n_tokens), add_bos, false) let tokenCount = llama_tokenize(vocab, text, Int32(utf8Count), tokens, Int32(n_tokens), add_bos, false)
var swiftTokens: [llama_token] = [] var swiftTokens: [llama_token] = []
for i in 0..<tokenCount { for i in 0..<tokenCount {
@ -316,7 +318,7 @@ actor LlamaContext {
defer { defer {
result.deallocate() result.deallocate()
} }
let nTokens = llama_token_to_piece(model, token, result, 8, 0, false) let nTokens = llama_token_to_piece(vocab, token, result, 8, 0, false)
if nTokens < 0 { if nTokens < 0 {
let newResult = UnsafeMutablePointer<Int8>.allocate(capacity: Int(-nTokens)) let newResult = UnsafeMutablePointer<Int8>.allocate(capacity: Int(-nTokens))
@ -324,7 +326,7 @@ actor LlamaContext {
defer { defer {
newResult.deallocate() newResult.deallocate()
} }
let nNewTokens = llama_token_to_piece(model, token, newResult, -nTokens, 0, false) let nNewTokens = llama_token_to_piece(vocab, token, newResult, -nTokens, 0, false)
let bufferPointer = UnsafeBufferPointer(start: newResult, count: Int(nNewTokens)) let bufferPointer = UnsafeBufferPointer(start: newResult, count: Int(nNewTokens))
return Array(bufferPointer) return Array(bufferPointer)
} else { } else {