Qualify scoped MiniCPM-o Radeon hybrid path

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tzhouam committed 2026-09-23 22:43:20 +08:00
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@@ -0,0 +1,86 @@
#!/usr/bin/env python3
"""Verify the same prompted MiniCPM-o request across CPU and Radeon runs."""
from __future__ import annotations
import argparse
import json
import re
from pathlib import Path
def read_json(path: Path) -> dict:
return json.loads(path.read_text(encoding="utf-8"))
def language_tokens(path: Path) -> list[int]:
matches = re.findall(r"LLM->TTS:.*?token_ids=\[([^]]+)\]", path.read_text(
encoding="utf-8", errors="replace"
))
if len(matches) != 1:
raise RuntimeError(f"expected exactly one logged text chunk: {path}")
return [int(value) for value in matches[0].split()]
def main() -> None:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--cpu-dir", type=Path, required=True)
parser.add_argument("--radeon-dir", type=Path, required=True)
parser.add_argument("--output", type=Path, required=True)
args = parser.parse_args()
cpu, gpu = (read_json(path / "full_report.json") for path in
(args.cpu_dir, args.radeon_dir))
if (cpu["expected_placement"], gpu["expected_placement"]) != (
"cpu", "radeon-hybrid"
):
raise RuntimeError("incorrect device placement")
if any(item["status"] != "scoped_complete_path_pass" for item in (cpu, gpu)):
raise RuntimeError("one complete path failed")
for key in ("artifacts", "model_revision", "input_image_sha256",
"input_audio_sha256", "response_text"):
if cpu[key] != gpu[key]:
raise RuntimeError(f"cross-device mismatch: {key}")
cpu_tokens = language_tokens(args.cpu_dir / "full.stdout.log")
gpu_tokens = language_tokens(args.radeon_dir / "full.stdout.log")
if cpu_tokens != gpu_tokens:
raise RuntimeError("language token IDs differ")
input_asr = read_json(args.radeon_dir / "input_asr.json")
cpu_asr = read_json(args.cpu_dir / "output_asr.json")
gpu_asr = read_json(args.radeon_dir / "output_asr.json")
if input_asr["word_error_rate"] != 0 or any(
item["word_error_rate"] != 0 for item in (cpu_asr, gpu_asr)
):
raise RuntimeError("input or output speech failed the ASR proxy")
if cpu["response_text"] != "The square in the image is red.":
raise RuntimeError("visual question was not answered correctly")
report = {
"scope": "one synthetic spoken visual question; standalone CPU vs Radeon hybrid",
"status": "scoped_prompted_path_pass",
"checkpoint_revision": cpu["model_revision"],
"same_artifact_set": True,
"same_input_image_audio": True,
"spoken_input": input_asr["reference_text"],
"input_asr_wer": input_asr["word_error_rate"],
"response_text": cpu["response_text"],
"language_token_ids": cpu_tokens,
"cpu": {
"cold_wall_s": cpu["sampled_process_profile"]["wall_s"],
"audio_duration_s": cpu["audio_duration_s"],
"pcm_sha256": cpu["pcm_sha256"],
"output_asr_wer": cpu_asr["word_error_rate"],
},
"radeon_hybrid": {
"cold_wall_s": gpu["sampled_process_profile"]["wall_s"],
"audio_duration_s": gpu["audio_duration_s"],
"pcm_sha256": gpu["pcm_sha256"],
"output_asr_wer": gpu_asr["word_error_rate"],
},
"quality_limit": "one synthetic red square and one spoken question",
}
args.output.parent.mkdir(parents=True, exist_ok=True)
args.output.write_text(json.dumps(report, indent=2) + "\n", encoding="utf-8")
print(json.dumps(report, indent=2))
if __name__ == "__main__":
main()
@@ -52,6 +52,9 @@ def main() -> None:
parser.add_argument("--merged-wav", type=Path, required=True)
parser.add_argument("--report", type=Path, required=True)
parser.add_argument("--platform-label", default="WSL CPU")
parser.add_argument(
"--expected-placement", choices=("cpu", "radeon-hybrid"), default="cpu"
)
parser.add_argument("--process-profile", type=Path)
args = parser.parse_args()
@@ -59,15 +62,27 @@ def main() -> None:
log = args.run_log.read_text(encoding="utf-8", errors="replace")
required_log = (
"Media type: 2 (omni: audio+vision)",
"GPU layers: 0",
"Token2Wav device: cpu",
"vision_ctx: vision using CPU backend",
"Token2Wav: initialized successfully",
"stream_prefill(index=1): processing user audio:",
"stream_prefill(index=1): user audio embedding:",
"stream_prefill: prefilled 1 vision chunks",
)
missing_log = [item for item in required_log if item not in log]
placement_log = {
"cpu": (
"GPU layers: 0",
"vision_ctx: vision using CPU backend",
),
"radeon-hybrid": (
"GPU layers: 99",
"using device Vulkan0 (AMD Radeon(TM) 890M Graphics)",
"offloaded 37/37 layers to GPU",
"vision_ctx: vision using Vulkan0 backend",
"TTS model: loading with n_gpu_layers=0",
"Token2Wav: non-CUDA backend, vocoder using CPU",
),
}[args.expected_placement]
missing_log = [item for item in required_log + placement_log if item not in log]
if missing_log:
raise RuntimeError(f"missing complete-path/placement evidence: {missing_log}")
process_profile = None
@@ -138,6 +153,7 @@ def main() -> None:
report = {
"scope": f"standalone MiniCPM-o 4.5 GGUF audio+image input to text+speech on {args.platform_label}",
"status": "scoped_complete_path_pass",
"expected_placement": args.expected_placement,
"quality": "synthetic red-square/tone response not established as semantically correct",
"model_revision": args.model_revision,
"artifacts": artifacts,
@@ -1,6 +1,6 @@
# 2026-09-23 WSL CPU and native Windows expansion
This extends the [60-cell device × model matrix](../e2e_profiling_20260922/evidence/summary/README.md) with previously unrun WSL CPU and native Windows paths. The September 22 timing tables remain historical. MiniCPM-o now has separate 20-request serial text-to-speech timing runs on WSL CPU and native Windows GPU, plus one synthetic image and one synthetic audio input on each platform. A separate pinned GGUF route ran one **combined** image+audio to text+speech request on WSL CPU and native Windows CPU; these C++ runs are standalone, with unqualified input-grounded quality. Each InternVLA timing remains one observation. Spark has a 20-request Omni output-head component profile on the HX370 AMD NPU and separate 20-request **complete text** profiles through standalone llama.cpp on native Windows CPU and Radeon 890M. The latter now also run as bounded whole-session Omni stages, with public AsyncOmni requests checked separately. Qwen3-TTS has separate 20-request standalone and bounded Omni whole-session text-to-WAV profiles on native Windows CPU; the CPU+Radeon 890M hybrid route likewise has standalone and Omni profiles. None is a sustained or full-modality profile. The [checkpoint manifests](../e2e_recovery_20260923/README.md) pin the earlier real weights; the [Spark NPU component record](evidence/spark_amd_npu_output_head/README.md), [standalone CPU/Radeon whole-model record](evidence/spark_radeon890m_llamacpp/README.md), [Omni CPU/Radeon whole-session record](evidence/spark_omni_llamacpp/README.md), [standalone CPU Qwen TTS record](evidence/qwen_tts_native_cpu/README.md), [Omni CPU Qwen TTS record](evidence/qwen_tts_omni_cpu/README.md), [standalone joint CPU+Radeon TTS record](evidence/qwen_tts_radeon890m_joint/README.md), and [Omni joint TTS record](evidence/qwen_tts_omni_hybrid/README.md) pin their respective artifacts. No model, precision or context was silently substituted.
This extends the [60-cell device × model matrix](../e2e_profiling_20260922/evidence/summary/README.md) with previously unrun WSL CPU and native Windows paths. The September 22 timing tables remain historical. MiniCPM-o now has separate 20-request serial text-to-speech timing runs on WSL CPU and native Windows GPU, plus one synthetic image and one synthetic audio input on each platform. A separate pinned GGUF route ran combined image+audio to text+speech requests on WSL CPU, native Windows CPU and native Windows Radeon 890M+CPU. The two Windows routes answered one spoken red-square question correctly with matching language token IDs; these C++ runs remain standalone, with broader input-grounded quality unqualified. Each InternVLA timing remains one observation. Spark has a 20-request Omni output-head component profile on the HX370 AMD NPU and separate 20-request **complete text** profiles through standalone llama.cpp on native Windows CPU and Radeon 890M. The latter now also run as bounded whole-session Omni stages, with public AsyncOmni requests checked separately. Qwen3-TTS has separate 20-request standalone and bounded Omni whole-session text-to-WAV profiles on native Windows CPU; the CPU+Radeon 890M hybrid route likewise has standalone and Omni profiles. None is a sustained or full-modality profile. The [checkpoint manifests](../e2e_recovery_20260923/README.md) pin the earlier real weights; the [Spark NPU component record](evidence/spark_amd_npu_output_head/README.md), [standalone CPU/Radeon whole-model record](evidence/spark_radeon890m_llamacpp/README.md), [Omni CPU/Radeon whole-session record](evidence/spark_omni_llamacpp/README.md), [standalone CPU Qwen TTS record](evidence/qwen_tts_native_cpu/README.md), [Omni CPU Qwen TTS record](evidence/qwen_tts_omni_cpu/README.md), [standalone joint CPU+Radeon TTS record](evidence/qwen_tts_radeon890m_joint/README.md), and [Omni joint TTS record](evidence/qwen_tts_omni_hybrid/README.md) pin their respective artifacts. No model, precision or context was silently substituted.
| Device / model | Verified depth | Observed output and time | Remaining gate |
|---|---|---|---|
@@ -18,6 +18,9 @@ This extends the [60-cell device × model matrix](../e2e_profiling_20260922/evid
| WSL CPU / MiniCPM-o 4.5, same revision | Scoped three-stage **audio**-to-text+speech path (P for one synthetic clip) | For the 2 s, 440 Hz tone, answered “A loud and high pitched beep” and produced a nonzero 2.16 s WAV. Startup 101.22 s; one request 17.30 s. Text and token IDs differed from WSL GPU. | Real-audio and transcription suites, speech meaning, repeated latency, memory admission and clean shutdown. |
| WSL CPU / MiniCPM-o 4.5, separate pinned Q4_K_M/F16 GGUF set | Standalone C++ whole-chain **combined synthetic image+audio** input to text+speech (P for this request; not an Omni stage or a semantic-quality pass) | The vision and audio encoders, language model, TTS and CPU Token2Wav ran in one process. One cold 40.70 s run returned generic text and ten nonempty 24 kHz chunks, assembled into a 9.24 s WAV; peak RSS from `/usr/bin/time` was 13,369,604 KiB (~12.75 GiB). Whisper tiny ASR gave 9.30% script-normalized character error against the generated text as an intelligibility proxy. The text did not describe the red square or tone. | Compare task quality against a prompted input/reference, fix upstream WAV merge naming, bind Omni placement, repeat latency, cancellation and sustained use; [C++ raw evidence](evidence/minicpmo_cpp_cpu/README.md). |
| Native Windows HX370 CPU / MiniCPM-o 4.5, same pinned Q4_K_M/F16 GGUF set | Standalone C++ whole-chain **combined synthetic image+audio** input to text+speech (P for this request; outside Omni) | The corrected x86-64-v3 build and bounded audio wait completed a cold run in 137.34 s, with 50 nonempty 24 kHz WAV chunks/49.16 s and sampled peak RSS/private bytes 13.10/13.31 GB. Whisper tiny ASR gave 13.59% script-normalized character error against the generated text. The response was generic and input-grounded quality remains unqualified. The first generic cross-build exited 0 with only 15 chunks and no completion flag, preserved as a failed attempt. | Bind an Omni whole-session stage and admission/state contract, prompt and qualify image/audio quality, fix live WAV merge/streaming, repeat latency, cancellation and sustained thermal behavior; [complete raw evidence](evidence/minicpmo_cpp_windows_cpu/README.md), [failed run](evidence/minicpmo_cpp_windows_cpu_attempt1/README.md). |
| Native Windows HX370 CPU / MiniCPM-o 4.5, same GGUF set; spoken visual question | Standalone combined JPEG+speech → text+speech (P for one prompted synthetic input) | The 16 kHz user speech independently transcribed as “What color is the square in the image?” (WER 0). CPU returned the correct “The square in the image is red.” with the same eight language token IDs as the Radeon hybrid; three nonzero 24 kHz WAV chunks made 2.32 s of speech, independently transcribed exactly (WER 0). One cold request took 24.66 s; maximum sampled RSS 13.11 GB. Waveform PCM differed from Radeon. | Omni whole-session binding and admission, real multimodal quality, playable stream, repeated latency and sustained power/thermal behavior; [prompted CPU raw evidence](evidence/minicpmo_cpp_windows_cpu_prompted/README.md), [cross-device check](evidence/minicpmo_cpp_radeon890m_prompted/cpu_radeon_parity.json). |
| Native Windows HX370 Radeon 890M+CPU / MiniCPM-o 4.5, same GGUF set; tone fixture | Standalone combined JPEG+tone → text+speech with Radeon language/vision and CPU vocoder (P for this unprompted input) | With only Radeon visible to Vulkan, logs show 37/37 language layers and vision on Vulkan0; TTS weights 0/21 GPU layers and CPU Token2Wav. One cold 113.43 s run yielded generic text and 42 nonzero 24 kHz WAV chunks/41.96 s, with sampled RSS 15.57 GB. The fixture lacked a spoken question, so this does not establish grounded quality. | See the prompted run below; Omni binding, live merge/streaming, loading/shared-RAM peak, repeated requests and sustained behavior remain open; [raw hybrid evidence](evidence/minicpmo_cpp_radeon890m/README.md). |
| Native Windows HX370 Radeon 890M+CPU / MiniCPM-o 4.5, same GGUF set; spoken visual question | Standalone combined JPEG+speech → text+speech with placement verified (P for one prompted synthetic input) | Spoken input ASR WER 0; the model answered “The square in the image is red.” with the same eight language token IDs as CPU. Three nonzero 24 kHz WAV chunks made 2.56 s of speech, output ASR WER 0. One cold process took 18.63 s, sampled RSS 15.57 GB. It is not an all-Radeon, NPU or Omni run. | Real image/audio suites, Omni admission/state/cancel binding, playable streaming, loading peak, repeated/concurrent latency and sustained thermal/power behavior; [prompted hybrid evidence](evidence/minicpmo_cpp_radeon890m_prompted/README.md). |
| Native Windows RTX 5090 Laptop / MiniCPM-o 4.5, same revision | Scoped complete three-stage text-to-text+speech path (P for this input only) | Coherent text with the same 32 thinker token IDs as WSL CUDA, and a nonzero 5.2 s mono 24 kHz WAV. First engine startup 297.20 s and request 78.75 s, including first-use graph/JIT work; separate 1-warmup/20-measured serial run: startup 239.05 s, request wall p50 18.38 s/p95 18.73 s. | Speech intelligibility/alignment, real image/audio quality, video input, concurrency, interruption, loading peak and sustained behavior. |
| WSL RTX 5090 Laptop / MiniCPM-o 4.5, same revision | Scoped three-stage **image**-to-text+speech path (P for one synthetic image) | For a 448×448 red square on white, returned the correct visual description and a nonzero 5.2 s WAV. Engine startup 101.96 s; one request 17.49 s. | Broader visual quality, real images, audio/video inputs, speech intelligibility, repeated latency and cleanup reliability. |
| WSL RTX 5090 Laptop / MiniCPM-o 4.5, same revision | Scoped three-stage **audio**-to-text+speech path (P for one synthetic clip) | For a 2 s, 440 Hz tone at 16 kHz, answered “A loud whistling sound” and produced a nonzero 2.16 s WAV. Engine startup 105.94 s; one request 7.78 s. | Speech transcription/real audio quality, video input, speech intelligibility, repeated latency and shared-memory cleanup. |
@@ -0,0 +1,25 @@
# MiniCPM-o 4.5 on native Windows Radeon 890M + CPU
The Ryzen AI 9 HX 370/Radeon 890M completed a **standalone scoped full request** with the pinned ten-file Q4_K_M/F16 [MiniCPM-o GGUF set](https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf/tree/db25077c33951fe163b42986fba0132e279872a2). One synthetic red-square JPEG plus 2 s/440 Hz tone traversed vision, audio, language, TTS and vocoder to text and speech. A second [spoken visual question](../minicpmo_cpp_radeon890m_prompted/README.md) returned the correct answer, “The square in the image is red.” The corresponding [native Windows CPU request](../minicpmo_cpp_windows_cpu_prompted/README.md) produced identical language token IDs. This is a CPU+iGPU hybrid, outside Omni StageRuntime/StagePool; it is not an all-Radeon or AMD NPU result.
The C++ source is [tc-mb/llama.cpp-omni](https://github.com/tc-mb/llama.cpp-omni/tree/5202b7b2f4d11f50b9f996161e7a2f8b8571b890) at `5202b7b2f4d11f50b9f996161e7a2f8b8571b890`, with the [CPU selection, Windows and bounded-completion patch](../minicpmo_cpp_cpu/llama_cpp_omni_cpu.patch). It was cross-built from Ubuntu with MinGW-w64 GCC 13-posix, x86-64-v3, Vulkan headers 1.4.341, glslc 2026.1-1, CMake/Ninja Release, and `GGML_CUDA=OFF`, `GGML_VULKAN=ON`, `GGML_OPENMP=OFF`. The initial build failed because pointing the Windows compiler at all of `/usr/include` picked up Linux `stdint.h`; [the failed log](build_failed_linux_include.log) is retained. Restricting the include path to Vulkan headers alone succeeded; see [configure](configure.log) and [build](build_success.log) logs. The Windows Vulkan loader was linked from `vulkan-1.dll` with the native driver. The exact executable and all ten Windows GGUF hashes are in the [report](full_report.json); weights and binaries remain outside Git.
The host was Windows 11 build 26200. [Vulkan enumeration](vulkaninfo_summary.log) lists RTX 5090 as GPU0 and Radeon 890M (driver `25.20.18.06 (LLPC)`) as GPU1. The run set `GGML_VK_VISIBLE_DEVICES=1`, making Radeon the only visible Vulkan device. The [runtime log](full.combined.log) then named `Vulkan0 (AMD Radeon(TM) 890M Graphics)`, offloaded all 37/37 language layers to it, placed vision on Vulkan0, and recorded CPU Token2Wav/vocoder. TTS weights used 0/21 offloaded layers, although a Vulkan compute buffer was logged; the audio encoder was CPU. The log is the placement evidence, not just requested flags.
| One cold combined tone+image request | Observation |
|---|---|
| Input path | Index 0 supplied reference/system audio; index 1 encoded the [JPEG](fixture_0001.jpg) and [16 kHz tone](fixture_0001.wav). The verifier checked both in the log. |
| Output | Nonempty [text](response_text.txt) and a completion marker; 42 contiguous, nonzero mono 24 kHz PCM16 [WAV chunks](round_000/tts_wav/) totaling 41.96 s. The [merged WAV](full_merged.wav) preserves their PCM exactly. The generic response to a tone and square without an explicit question is not a grounded-quality result. |
| Time and memory | 113.43 s cold process wall; 15.57 GB sampled maximum RSS and 15.45 GB sampled maximum private bytes at 100 ms intervals. These are one-run observations, not p50/p95, guaranteed loading peaks or sustained thermal results. [Process profile](full.profile.json). |
| Speech proxy | Local pinned `openai/whisper-tiny` on CPU transcribed the Mandarin output with 8.79% character error against the model's own text after OpenCC script normalization. This does not measure whether the text answered the input. [ASR report](speech_asr_proxy.json). |
The verifier checked the pinned artifacts, exact logged placement, index-1 image+audio prefill, completion marker, contiguous WAV sequence, audio format/bounds and nonempty text. The upstream optional WAV merger still looks for the wrong chunk names and runs before vocoder completion; [the verifier](../../../../experiments/verify_minicpm_cpp_output.py) joined original PCM afterward. The correctly prompted result provides a stronger one-case quality check, but real image/audio suites, video, playable streaming, Omni admission/state/cancellation, repeated latency, shared-RAM/GPU loading peak and sustained power/thermal behavior remain open.
Reproduce after applying the patch and obtaining the pinned GGUF set. Cross-configure with `-DCMAKE_SYSTEM_NAME=Windows -DCMAKE_SYSTEM_PROCESSOR=x86_64`, MinGW-w64 `gcc-posix/g++-posix`, `-DCMAKE_C_FLAGS=-march=x86-64-v3 -DCMAKE_CXX_FLAGS=-march=x86-64-v3`, `-DGGML_VULKAN=ON`, `-DVulkan_INCLUDE_DIR=/path/to/isolated/vulkan-headers`, `-DVulkan_LIBRARY=/path/to/vulkan-1.dll` and `-DVulkan_GLSLC_EXECUTABLE=/usr/bin/glslc`. Build `llama-omni-cli`, then on native Windows:
```powershell
$env:GGML_VK_VISIBLE_DEVICES = '1'
llama-omni-cli.exe -m C:\path\to\MiniCPM-o-4_5-Q4_K_M.gguf `
-ngl 99 -c 2048 --omni --t2w-device cpu --t2w-wait-seconds 900 `
--ref-audio C:\path\to\default_ref_audio.wav --test C:\path\to\fixture_ 2
```
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/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c: In function ‘validate_float’:
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5004:76: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5004 | fprintf(stderr, "ggml_validate_row_data: found inf value at block %zu\n", i);
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5004:25: warning: too many arguments for format [-Wformat-extra-args]
5004 | fprintf(stderr, "ggml_validate_row_data: found inf value at block %zu\n", i);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5009:76: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5009 | fprintf(stderr, "ggml_validate_row_data: found nan value at block %zu\n", i);
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5009:25: warning: too many arguments for format [-Wformat-extra-args]
5009 | fprintf(stderr, "ggml_validate_row_data: found nan value at block %zu\n", i);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c: In function ‘validate_fp16’:
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5026:76: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5026 | fprintf(stderr, "ggml_validate_row_data: found inf value at block %zu\n", i);
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5026:25: warning: too many arguments for format [-Wformat-extra-args]
5026 | fprintf(stderr, "ggml_validate_row_data: found inf value at block %zu\n", i);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5031:76: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5031 | fprintf(stderr, "ggml_validate_row_data: found nan value at block %zu\n", i);
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5031:25: warning: too many arguments for format [-Wformat-extra-args]
5031 | fprintf(stderr, "ggml_validate_row_data: found nan value at block %zu\n", i);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c: In function ‘validate_e_e8m0’:
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5040:85: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5040 | fprintf(stderr, "ggml_validate_row_data: found invalid e value %d at block %zu\n", e, i);
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5040:25: warning: too many arguments for format [-Wformat-extra-args]
5040 | fprintf(stderr, "ggml_validate_row_data: found invalid e value %d at block %zu\n", e, i);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c: In function ‘ggml_validate_row_data’:
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5088:44: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5088 | fprintf(stderr, "%s: invalid size %zu for type %s (type size = %zu)\n", __func__, nbytes, ggml_type_name(type), ggml_type_size(type));
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5088:57: warning: format ‘%s’ expects argument of type ‘char *’, but argument 4 has type ‘size_t’ {aka ‘long long unsigned int’} [-Wformat=]
5088 | fprintf(stderr, "%s: invalid size %zu for type %s (type size = %zu)\n", __func__, nbytes, ggml_type_name(type), ggml_type_size(type));
| ~^ ~~~~~~
| | |
| char * size_t {aka long long unsigned int}
| %lld
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5088:73: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5088 | fprintf(stderr, "%s: invalid size %zu for type %s (type size = %zu)\n", __func__, nbytes, ggml_type_name(type), ggml_type_size(type));
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5088:25: warning: too many arguments for format [-Wformat-extra-args]
5088 | fprintf(stderr, "%s: invalid size %zu for type %s (type size = %zu)\n", __func__, nbytes, ggml_type_name(type), ggml_type_size(type));
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5105:67: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5105 | fprintf(stderr, "%s: found %d NaNs in row of %zu BF16 values\n", __func__, nans, nb);
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5105:37: warning: too many arguments for format [-Wformat-extra-args]
5105 | fprintf(stderr, "%s: found %d NaNs in row of %zu BF16 values\n", __func__, nans, nb);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5109:73: warning: unknown conversion type character ‘z’ in format [-Wformat=]
5109 | fprintf(stderr, "%s: found %d infinities in row of %zu BF16 values\n", __func__, infs, nb);
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-quants.c:5109:37: warning: too many arguments for format [-Wformat-extra-args]
5109 | fprintf(stderr, "%s: found %d infinities in row of %zu BF16 values\n", __func__, infs, nb);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
[27/323] Linking CXX static library ggml/src/ggml-base.a
[28/323] Building CXX object ggml/src/CMakeFiles/ggml-cpu.dir/ggml-cpu/arch/x86/repack.cpp.obj
[29/323] Building CXX object ggml/src/CMakeFiles/ggml-cpu.dir/ggml-cpu/llamafile/sgemm.cpp.obj
[30/323] Building CXX object ggml/src/CMakeFiles/ggml-cpu.dir/ggml-cpu/ops.cpp.obj
[31/323] Linking CXX static library ggml/src/ggml-cpu.a
[32/323] Performing build step for 'vulkan-shaders-gen'
[1/2] Building CXX object CMakeFiles/vulkan-shaders-gen.dir/vulkan-shaders-gen.cpp.o
[2/2] Linking CXX executable /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/bin/vulkan-shaders-gen
[33/323] Performing install step for 'vulkan-shaders-gen'
-- Installing: /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/Release/./vulkan-shaders-gen
[34/323] Completed 'vulkan-shaders-gen'
[35/323] Generate vulkan shaders header
[36/323] Generate vulkan shaders for argmax.comp
[37/323] Generate vulkan shaders for concat.comp
[38/323] Generate vulkan shaders for argsort.comp
[39/323] Generate vulkan shaders for acc.comp
[40/323] Generate vulkan shaders for add_id.comp
[41/323] Generate vulkan shaders for clamp.comp
[42/323] Generate vulkan shaders for contig_copy.comp
[43/323] Generate vulkan shaders for conv2d_dw.comp
[44/323] Generate vulkan shaders for cos.comp
[45/323] Generate vulkan shaders for conv_transpose_1d.comp
[46/323] Generate vulkan shaders for add.comp
[47/323] Generate vulkan shaders for copy.comp
[48/323] Generate vulkan shaders for conv2d_mm.comp
[49/323] Generate vulkan shaders for copy_from_quant.comp
[50/323] Generate vulkan shaders for count_equal.comp
[51/323] Generate vulkan shaders for dequant_f32.comp
[52/323] Generate vulkan shaders for dequant_iq1_m.comp
[53/323] Generate vulkan shaders for dequant_iq1_s.comp
[54/323] Generate vulkan shaders for dequant_iq2_s.comp
[55/323] Generate vulkan shaders for dequant_iq2_xs.comp
[56/323] Generate vulkan shaders for dequant_iq2_xxs.comp
[57/323] Generate vulkan shaders for dequant_iq3_xxs.comp
[58/323] Generate vulkan shaders for dequant_iq3_s.comp
[59/323] Generate vulkan shaders for dequant_mxfp4.comp
[60/323] Generate vulkan shaders for dequant_iq4_nl.comp
[61/323] Generate vulkan shaders for dequant_q2_k.comp
[62/323] Generate vulkan shaders for dequant_iq4_xs.comp
[63/323] Generate vulkan shaders for copy_to_quant.comp
[64/323] Generate vulkan shaders for dequant_q3_k.comp
[65/323] Generate vulkan shaders for dequant_q4_0.comp
[66/323] Generate vulkan shaders for dequant_q4_1.comp
[67/323] Generate vulkan shaders for dequant_q4_k.comp
[68/323] Generate vulkan shaders for dequant_q5_0.comp
[69/323] Generate vulkan shaders for dequant_q8_0.comp
[70/323] Generate vulkan shaders for dequant_q5_1.comp
[71/323] Generate vulkan shaders for dequant_q5_k.comp
[72/323] Generate vulkan shaders for dequant_q6_k.comp
[73/323] Generate vulkan shaders for diag_mask_inf.comp
[74/323] Generate vulkan shaders for exp.comp
[75/323] Generate vulkan shaders for div.comp
[76/323] Generate vulkan shaders for geglu.comp
[77/323] Generate vulkan shaders for flash_attn_split_k_reduce.comp
[78/323] Generate vulkan shaders for flash_attn_cm1.comp
[79/323] Generate vulkan shaders for geglu_erf.comp
[80/323] Generate vulkan shaders for geglu_quick.comp
[81/323] Generate vulkan shaders for flash_attn.comp
[82/323] Generate vulkan shaders for gelu.comp
[83/323] Generate vulkan shaders for gelu_erf.comp
[84/323] Generate vulkan shaders for gelu_quick.comp
[85/323] Generate vulkan shaders for group_norm.comp
[86/323] Generate vulkan shaders for get_rows.comp
[87/323] Generate vulkan shaders for hardsigmoid.comp
[88/323] Generate vulkan shaders for hardswish.comp
[89/323] Generate vulkan shaders for l2_norm.comp
[90/323] Generate vulkan shaders for im2col.comp
[91/323] Generate vulkan shaders for im2col_3d.comp
[92/323] Generate vulkan shaders for leaky_relu.comp
[93/323] Generate vulkan shaders for mul_mat_split_k_reduce.comp
[94/323] Generate vulkan shaders for flash_attn_cm2.comp
[95/323] Generate vulkan shaders for get_rows_quant.comp
[96/323] Generate vulkan shaders for mul.comp
[97/323] Generate vulkan shaders for mul_mat_vec_iq1_m.comp
[98/323] Generate vulkan shaders for mul_mat_vec_nc.comp
[99/323] Generate vulkan shaders for mul_mat_vec_iq1_s.comp
[100/323] Generate vulkan shaders for mul_mat_vec_iq2_xxs.comp
[101/323] Generate vulkan shaders for mul_mat_vec_iq2_s.comp
[102/323] Generate vulkan shaders for mul_mat_vec_iq2_xs.comp
[103/323] Generate vulkan shaders for mul_mat_vec_iq3_xxs.comp
[104/323] Generate vulkan shaders for mul_mat_vec_iq3_s.comp
[105/323] Generate vulkan shaders for mul_mat_vec_p021.comp
[106/323] Generate vulkan shaders for mul_mat_vec_q4_k.comp
[107/323] Generate vulkan shaders for mul_mat_vec_q5_k.comp
[108/323] Generate vulkan shaders for mul_mat_vec_q2_k.comp
[109/323] Generate vulkan shaders for mul_mat_vec_q3_k.comp
[110/323] Generate vulkan shaders for mul_mat_vec_q6_k.comp
[111/323] Generate vulkan shaders for mul_mat_vecq.comp
[112/323] Generate vulkan shaders for opt_step_adamw.comp
[113/323] Generate vulkan shaders for multi_add.comp
[114/323] Generate vulkan shaders for opt_step_sgd.comp
[115/323] Generate vulkan shaders for norm.comp
[116/323] Generate vulkan shaders for mul_mmq.comp
[117/323] Generate vulkan shaders for pad.comp
[118/323] Generate vulkan shaders for pool2d.comp
[119/323] Generate vulkan shaders for reglu.comp
[120/323] Generate vulkan shaders for relu.comp
[121/323] Generate vulkan shaders for repeat.comp
[122/323] Generate vulkan shaders for quantize_q8_1.comp
[123/323] Generate vulkan shaders for mul_mat_vec.comp
[124/323] Generate vulkan shaders for repeat_back.comp
[125/323] Generate vulkan shaders for rms_norm_back.comp
[126/323] Generate vulkan shaders for rms_norm_partials.comp
[127/323] Generate vulkan shaders for roll.comp
[128/323] Generate vulkan shaders for rope_multi.comp
[129/323] Generate vulkan shaders for rope_neox.comp
[130/323] Generate vulkan shaders for rope_norm.comp
[131/323] Generate vulkan shaders for rms_norm.comp
[132/323] Generate vulkan shaders for rope_vision.comp
[133/323] Generate vulkan shaders for scale.comp
[134/323] Generate vulkan shaders for silu.comp
[135/323] Generate vulkan shaders for silu_back.comp
[136/323] Generate vulkan shaders for sigmoid.comp
[137/323] Generate vulkan shaders for sin.comp
[138/323] Generate vulkan shaders for soft_max_back.comp
[139/323] Generate vulkan shaders for sqrt.comp
[140/323] Generate vulkan shaders for square.comp
[141/323] Generate vulkan shaders for sum_rows.comp
[142/323] Generate vulkan shaders for sub.comp
[143/323] Generate vulkan shaders for tanh.comp
[144/323] Generate vulkan shaders for swiglu_oai.comp
[145/323] Generate vulkan shaders for swiglu.comp
[146/323] Generate vulkan shaders for timestep_embedding.comp
[147/323] Generate vulkan shaders for upscale.comp
[148/323] Generate vulkan shaders for soft_max.comp
[149/323] Generate vulkan shaders for wkv6.comp
[150/323] Generate vulkan shaders for wkv7.comp
[151/323] Generate vulkan shaders for mul_mm_cm2.comp
[152/323] Generate vulkan shaders for mul_mm.comp
[153/323] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/clamp.comp.cpp.obj
FAILED: [code=1] ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/clamp.comp.cpp.obj
/usr/bin/x86_64-w64-mingw32-g++-posix -DGGML_SCHED_MAX_COPIES=4 -DGGML_VULKAN_BFLOAT16_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT2_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT_GLSLC_SUPPORT -DGGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT -D_CRT_SECURE_NO_WARNINGS -D_WIN32_WINNT=0xA00 -D_XOPEN_SOURCE=600 -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/.. -I/home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include -isystem /usr/include -march=x86-64-v3 -O3 -DNDEBUG -std=gnu++17 -Wmissing-declarations -Wmissing-noreturn -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-array-bounds -Wextra-semi -MD -MT ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/clamp.comp.cpp.obj -MF ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/clamp.comp.cpp.obj.d -o ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/clamp.comp.cpp.obj -c /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/clamp.comp.cpp
In file included from /usr/lib/gcc/x86_64-w64-mingw32/13-posix/include/c++/cstdint:45,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/ggml-vulkan-shaders.hpp:1,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/clamp.comp.cpp:1:
/usr/include/stdint.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
26 | #include <bits/libc-header-start.h>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
[154/323] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argsort.comp.cpp.obj
FAILED: [code=1] ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argsort.comp.cpp.obj
/usr/bin/x86_64-w64-mingw32-g++-posix -DGGML_SCHED_MAX_COPIES=4 -DGGML_VULKAN_BFLOAT16_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT2_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT_GLSLC_SUPPORT -DGGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT -D_CRT_SECURE_NO_WARNINGS -D_WIN32_WINNT=0xA00 -D_XOPEN_SOURCE=600 -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/.. -I/home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include -isystem /usr/include -march=x86-64-v3 -O3 -DNDEBUG -std=gnu++17 -Wmissing-declarations -Wmissing-noreturn -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-array-bounds -Wextra-semi -MD -MT ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argsort.comp.cpp.obj -MF ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argsort.comp.cpp.obj.d -o ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argsort.comp.cpp.obj -c /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/argsort.comp.cpp
In file included from /usr/lib/gcc/x86_64-w64-mingw32/13-posix/include/c++/cstdint:45,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/ggml-vulkan-shaders.hpp:1,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/argsort.comp.cpp:1:
/usr/include/stdint.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
26 | #include <bits/libc-header-start.h>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
[155/323] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/acc.comp.cpp.obj
FAILED: [code=1] ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/acc.comp.cpp.obj
/usr/bin/x86_64-w64-mingw32-g++-posix -DGGML_SCHED_MAX_COPIES=4 -DGGML_VULKAN_BFLOAT16_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT2_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT_GLSLC_SUPPORT -DGGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT -D_CRT_SECURE_NO_WARNINGS -D_WIN32_WINNT=0xA00 -D_XOPEN_SOURCE=600 -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/.. -I/home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include -isystem /usr/include -march=x86-64-v3 -O3 -DNDEBUG -std=gnu++17 -Wmissing-declarations -Wmissing-noreturn -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-array-bounds -Wextra-semi -MD -MT ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/acc.comp.cpp.obj -MF ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/acc.comp.cpp.obj.d -o ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/acc.comp.cpp.obj -c /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/acc.comp.cpp
In file included from /usr/lib/gcc/x86_64-w64-mingw32/13-posix/include/c++/cstdint:45,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/ggml-vulkan-shaders.hpp:1,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/acc.comp.cpp:1:
/usr/include/stdint.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
26 | #include <bits/libc-header-start.h>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
[156/323] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add.comp.cpp.obj
FAILED: [code=1] ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add.comp.cpp.obj
/usr/bin/x86_64-w64-mingw32-g++-posix -DGGML_SCHED_MAX_COPIES=4 -DGGML_VULKAN_BFLOAT16_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT2_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT_GLSLC_SUPPORT -DGGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT -D_CRT_SECURE_NO_WARNINGS -D_WIN32_WINNT=0xA00 -D_XOPEN_SOURCE=600 -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/.. -I/home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include -isystem /usr/include -march=x86-64-v3 -O3 -DNDEBUG -std=gnu++17 -Wmissing-declarations -Wmissing-noreturn -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-array-bounds -Wextra-semi -MD -MT ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add.comp.cpp.obj -MF ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add.comp.cpp.obj.d -o ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add.comp.cpp.obj -c /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/add.comp.cpp
In file included from /usr/lib/gcc/x86_64-w64-mingw32/13-posix/include/c++/cstdint:45,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/ggml-vulkan-shaders.hpp:1,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/add.comp.cpp:1:
/usr/include/stdint.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
26 | #include <bits/libc-header-start.h>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
[157/323] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add_id.comp.cpp.obj
FAILED: [code=1] ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add_id.comp.cpp.obj
/usr/bin/x86_64-w64-mingw32-g++-posix -DGGML_SCHED_MAX_COPIES=4 -DGGML_VULKAN_BFLOAT16_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT2_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT_GLSLC_SUPPORT -DGGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT -D_CRT_SECURE_NO_WARNINGS -D_WIN32_WINNT=0xA00 -D_XOPEN_SOURCE=600 -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/.. -I/home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include -isystem /usr/include -march=x86-64-v3 -O3 -DNDEBUG -std=gnu++17 -Wmissing-declarations -Wmissing-noreturn -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-array-bounds -Wextra-semi -MD -MT ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add_id.comp.cpp.obj -MF ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add_id.comp.cpp.obj.d -o ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add_id.comp.cpp.obj -c /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/add_id.comp.cpp
In file included from /usr/lib/gcc/x86_64-w64-mingw32/13-posix/include/c++/cstdint:45,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/ggml-vulkan-shaders.hpp:1,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/add_id.comp.cpp:1:
/usr/include/stdint.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
26 | #include <bits/libc-header-start.h>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
[158/323] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argmax.comp.cpp.obj
FAILED: [code=1] ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argmax.comp.cpp.obj
/usr/bin/x86_64-w64-mingw32-g++-posix -DGGML_SCHED_MAX_COPIES=4 -DGGML_VULKAN_BFLOAT16_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT2_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT_GLSLC_SUPPORT -DGGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT -D_CRT_SECURE_NO_WARNINGS -D_WIN32_WINNT=0xA00 -D_XOPEN_SOURCE=600 -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/.. -I/home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include -isystem /usr/include -march=x86-64-v3 -O3 -DNDEBUG -std=gnu++17 -Wmissing-declarations -Wmissing-noreturn -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-array-bounds -Wextra-semi -MD -MT ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argmax.comp.cpp.obj -MF ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argmax.comp.cpp.obj.d -o ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argmax.comp.cpp.obj -c /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/argmax.comp.cpp
In file included from /usr/lib/gcc/x86_64-w64-mingw32/13-posix/include/c++/cstdint:45,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/ggml-vulkan-shaders.hpp:1,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/argmax.comp.cpp:1:
/usr/include/stdint.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
26 | #include <bits/libc-header-start.h>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
[159/323] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/ggml-vulkan.cpp.obj
FAILED: [code=1] ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/ggml-vulkan.cpp.obj
/usr/bin/x86_64-w64-mingw32-g++-posix -DGGML_SCHED_MAX_COPIES=4 -DGGML_VULKAN_BFLOAT16_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT2_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT_GLSLC_SUPPORT -DGGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT -D_CRT_SECURE_NO_WARNINGS -D_WIN32_WINNT=0xA00 -D_XOPEN_SOURCE=600 -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/.. -I/home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include -isystem /usr/include -march=x86-64-v3 -O3 -DNDEBUG -std=gnu++17 -Wmissing-declarations -Wmissing-noreturn -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-array-bounds -Wextra-semi -MD -MT ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/ggml-vulkan.cpp.obj -MF ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/ggml-vulkan.cpp.obj.d -o ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/ggml-vulkan.cpp.obj -c /home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/ggml-vulkan.cpp
In file included from /home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include/ggml.h:209,
from /home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include/ggml-vulkan.h:3,
from /home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/ggml-vulkan.cpp:1:
/usr/include/stdint.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
26 | #include <bits/libc-header-start.h>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
[160/323] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/concat.comp.cpp.obj
FAILED: [code=1] ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/concat.comp.cpp.obj
/usr/bin/x86_64-w64-mingw32-g++-posix -DGGML_SCHED_MAX_COPIES=4 -DGGML_VULKAN_BFLOAT16_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT2_GLSLC_SUPPORT -DGGML_VULKAN_COOPMAT_GLSLC_SUPPORT -DGGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT -D_CRT_SECURE_NO_WARNINGS -D_WIN32_WINNT=0xA00 -D_XOPEN_SOURCE=600 -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/ggml-vulkan/.. -I/home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan -I/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include -isystem /usr/include -march=x86-64-v3 -O3 -DNDEBUG -std=gnu++17 -Wmissing-declarations -Wmissing-noreturn -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-array-bounds -Wextra-semi -MD -MT ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/concat.comp.cpp.obj -MF ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/concat.comp.cpp.obj.d -o ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/concat.comp.cpp.obj -c /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/concat.comp.cpp
In file included from /usr/lib/gcc/x86_64-w64-mingw32/13-posix/include/c++/cstdint:45,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/ggml-vulkan-shaders.hpp:1,
from /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/ggml/src/ggml-vulkan/concat.comp.cpp:1:
/usr/include/stdint.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory
26 | #include <bits/libc-header-start.h>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
ninja: build stopped: subcommand failed.
@@ -0,0 +1,930 @@
[0/2] Re-checking globbed directories...
[1/174] Performing build step for 'vulkan-shaders-gen'
ninja: no work to do.
[2/174] Performing install step for 'vulkan-shaders-gen'
-- Up-to-date: /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/Release/./vulkan-shaders-gen
[3/174] Completed 'vulkan-shaders-gen'
[4/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/clamp.comp.cpp.obj
[5/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/concat.comp.cpp.obj
[6/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add_id.comp.cpp.obj
[7/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argmax.comp.cpp.obj
[8/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/acc.comp.cpp.obj
[9/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/argsort.comp.cpp.obj
[10/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/conv_transpose_1d.comp.cpp.obj
[11/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/contig_copy.comp.cpp.obj
[12/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/conv2d_dw.comp.cpp.obj
[13/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/copy.comp.cpp.obj
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[16/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/count_equal.comp.cpp.obj
[17/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/copy_from_quant.comp.cpp.obj
[18/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_iq1_m.comp.cpp.obj
[19/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_iq1_s.comp.cpp.obj
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[22/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/add.comp.cpp.obj
[23/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/conv2d_mm.comp.cpp.obj
[24/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_iq2_xxs.comp.cpp.obj
[25/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_iq3_xxs.comp.cpp.obj
[26/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_iq3_s.comp.cpp.obj
[27/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_iq4_nl.comp.cpp.obj
[28/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_iq4_xs.comp.cpp.obj
[29/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_mxfp4.comp.cpp.obj
[30/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_q4_0.comp.cpp.obj
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[35/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_q5_0.comp.cpp.obj
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[39/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/dequant_q8_0.comp.cpp.obj
[40/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/diag_mask_inf.comp.cpp.obj
[41/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/exp.comp.cpp.obj
[42/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/flash_attn_split_k_reduce.comp.cpp.obj
[43/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/geglu.comp.cpp.obj
[44/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/geglu_erf.comp.cpp.obj
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[156/174] Building CXX object common/CMakeFiles/common.dir/json-schema-to-grammar.cpp.obj
[157/174] Building CXX object common/CMakeFiles/common.dir/regex-partial.cpp.obj
[158/174] Building CXX object tools/omni/CMakeFiles/omni.dir/vision.cpp.obj
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/vision.cpp: In function ‘bool vision_image_batch_encode(vision_ctx*, int, const vision_image_f32_batch*, float*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/vision.cpp:1882:15: warning: unused variable ‘n_pos’ [-Wunused-variable]
1882 | const int n_pos = num_patches;
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/vision.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/vision.cpp:2056:6: warning: no previous declaration for ‘void vision_set_max_slice_nums(vision_ctx*, int)’ [-Wmissing-declarations]
2056 | void vision_set_max_slice_nums(struct vision_ctx * ctx, int max_slice_nums) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~
[159/174] Building CXX object tools/omni/CMakeFiles/omni.dir/token2wav/token2wav.cpp.obj
[160/174] Building CXX object tools/omni/CMakeFiles/llama-omni-cli.dir/omni-cli.cpp.obj
In file included from /home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-cli.cpp:5:
/home/zhout/project/edge_infer/llama.cpp-omni/common/./log.h:89: warning: "LOG_TMPL" redefined
89 | #define LOG_TMPL(level, verbosity, ...) \
|
In file included from /home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-cli.cpp:1:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-impl.h:174: note: this is the location of the previous definition
174 | #define LOG_TMPL(level, ...) \
|
/home/zhout/project/edge_infer/llama.cpp-omni/common/./log.h:99: warning: "LOG_INF" redefined
99 | #define LOG_INF(...) LOG_TMPL(GGML_LOG_LEVEL_INFO, 0, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-impl.h:180: note: this is the location of the previous definition
180 | #define LOG_INF(...) LOG_TMPL(GGML_LOG_LEVEL_INFO, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/common/./log.h:100: warning: "LOG_WRN" redefined
100 | #define LOG_WRN(...) LOG_TMPL(GGML_LOG_LEVEL_WARN, 0, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-impl.h:181: note: this is the location of the previous definition
181 | #define LOG_WRN(...) LOG_TMPL(GGML_LOG_LEVEL_WARN, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/common/./log.h:101: warning: "LOG_ERR" redefined
101 | #define LOG_ERR(...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, 0, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-impl.h:182: note: this is the location of the previous definition
182 | #define LOG_ERR(...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/common/./log.h:102: warning: "LOG_DBG" redefined
102 | #define LOG_DBG(...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, LOG_DEFAULT_DEBUG, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-impl.h:183: note: this is the location of the previous definition
183 | #define LOG_DBG(...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/common/./log.h:103: warning: "LOG_CNT" redefined
103 | #define LOG_CNT(...) LOG_TMPL(GGML_LOG_LEVEL_CONT, 0, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-impl.h:184: note: this is the location of the previous definition
184 | #define LOG_CNT(...) LOG_TMPL(GGML_LOG_LEVEL_CONT, __VA_ARGS__)
|
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-cli.cpp:161:6: warning: no previous declaration for ‘void test_case(omni_context*, common_params&, std::string, int)’ [-Wmissing-declarations]
161 | void test_case(struct omni_context *ctx_omni, common_params& params, std::string data_path_prefix, int cnt){
| ^~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-cli.cpp: In function ‘void test_case(omni_context*, common_params&, std::string, int)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-cli.cpp:161:62: warning: unused parameter ‘params’ [-Wunused-parameter]
161 | void test_case(struct omni_context *ctx_omni, common_params& params, std::string data_path_prefix, int cnt){
| ~~~~~~~~~~~~~~~^~~~~~
[161/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/mul_mm.comp.cpp.obj
[162/174] Building CXX object tools/omni/CMakeFiles/omni.dir/token2wav/token2wav-impl.cpp.obj
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_tensor* omni::flow::{anonymous}::flow_build_l2_normalize_cb(ggml_context*, ggml_tensor*, float)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:76:19: warning: unused variable ‘C’ [-Wunused-variable]
76 | const int64_t C = x_cb->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:77:19: warning: unused variable ‘B’ [-Wunused-variable]
77 | const int64_t B = x_cb->ne[1];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_tensor* omni::flow_matching::{anonymous}::fm_attn_mul_mat_checked(ggml_context*, ggml_tensor*, ggml_tensor*, const char*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:349:106: warning: unused parameter ‘label’ [-Wunused-parameter]
349 | ggml_tensor * fm_attn_mul_mat_checked(ggml_context * ctx, ggml_tensor * a, ggml_tensor * b, const char * label) {
| ~~~~~~~~~~~~~^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::flow_matching::fmAttention::build_forward_graph(ggml_context*, ggml_tensor*, ggml_tensor*) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:410:19: warning: unused variable ‘C’ [-Wunused-variable]
410 | const int64_t C = x->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::flow_matching::fmAttention::build_forward_chunk_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor**) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:451:19: warning: unused variable ‘C’ [-Wunused-variable]
451 | const int64_t C = x->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In static member function ‘static ggml_tensor* omni::flow_matching::fmCausalConditionalCFM::deterministic_noise(ggml_context*, int64_t, int64_t, int64_t, float, int64_t)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:573:74: warning: unused parameter ‘offset_ct’ [-Wunused-parameter]
573 | int64_t offset_ct) {
| ~~~~~~~~~~~~~~~^~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::flow_matching::fmCausalConditionalCFM::build_forward_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor*, int, float) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:636:27: warning: unused variable ‘B_spk’ [-Wunused-variable]
636 | const int64_t B_spk = spks->ne[1];
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:640:27: warning: unused variable ‘one’ [-Wunused-variable]
640 | const int64_t one = spks->ne[1];
| ^~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:641:27: warning: unused variable ‘B_spk’ [-Wunused-variable]
641 | const int64_t B_spk = spks->ne[2];
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::flow_matching::fmCausalConditionalCFM::build_forward_chunk_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*, int, float, const omni::flow_matching::fmCFMCache*, omni::flow_matching::fmCFMCache*) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:716:23: warning: unused variable ‘n_time_in’ [-Wunused-variable]
716 | const int64_t n_time_in = att_cache_packed->ne[2] / (int64_t) (H * depth);
| ^~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:720:23: warning: unused variable ‘n_time_in’ [-Wunused-variable]
720 | const int64_t n_time_in = cnn_cache_packed->ne[2] / (int64_t) depth;
| ^~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:739:27: warning: unused variable ‘B_spk’ [-Wunused-variable]
739 | const int64_t B_spk = spks->ne[1];
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:743:27: warning: unused variable ‘one’ [-Wunused-variable]
743 | const int64_t one = spks->ne[1];
| ^~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:744:27: warning: unused variable ‘B_spk’ [-Wunused-variable]
744 | const int64_t B_spk = spks->ne[2];
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::flow_matching::fmCausalConv1d::build_forward_graph(ggml_context*, ggml_tensor*) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:898:19: warning: unused variable ‘Cin’ [-Wunused-variable]
898 | const int64_t Cin = x->ne[0];
| ^~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:901:19: warning: unused variable ‘Cin_w’ [-Wunused-variable]
901 | const int64_t Cin_w = weight_->ne[1];
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::flow_matching::fmCausalConv1d::build_forward_chunk_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor**) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:938:19: warning: unused variable ‘K’ [-Wunused-variable]
938 | const int64_t K = weight_->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:939:19: warning: unused variable ‘Cin_w’ [-Wunused-variable]
939 | const int64_t Cin_w = weight_->ne[1];
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::flow_matching::fmDiT::build_blocks_forward_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:1247:19: warning: unused variable ‘T’ [-Wunused-variable]
1247 | const int64_t T = x->ne[1];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::flow_matching::fmDiT::build_blocks_forward_chunk_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*, const std::vector<ggml_tensor*>&, const std::vector<ggml_tensor*>&, std::vector<ggml_tensor*>&, std::vector<ggml_tensor*>&) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:1296:19: warning: unused variable ‘T’ [-Wunused-variable]
1296 | const int64_t T = x->ne[1];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘bool omni::flow_matching::fmFlowMatchingModelLoaderGGUF::load_from_file(const std::string&, ggml_backend_t)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:1699:23: warning: the address of ‘ggml_tensor::name’ will never be NULL [-Waddress]
1699 | if (!t || !t->name) {
| ~~~^~~~
In file included from /home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.h:5,
from /home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3:
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include/ggml.h:653:14: note: ‘ggml_tensor::name’ declared here
653 | char name[GGML_MAX_NAME];
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_backend* omni::flow_matching::{anonymous}::fm_loader_init_backend_gpu_idx(int, std::string&)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:1903:51: warning: unused parameter ‘gpu_idx’ [-Wunused-parameter]
1903 | ggml_backend_t fm_loader_init_backend_gpu_idx(int gpu_idx, std::string & backend_name_out) {
| ~~~~^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In static member function ‘static void omni::flow_matching::fmFlowMatchingGGUFModelLoader::fill_noise_ctb(std::vector<float>&, int64_t, int64_t, int64_t, float, int64_t)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:2029:73: warning: unused parameter ‘offset_ct’ [-Wunused-parameter]
2029 | int64_t offset_ct) {
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_backend* omni::upsample_encoder_v2::{anonymous}::ue_loader_init_backend_gpu_idx(int, std::string&)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:2882:51: warning: unused parameter ‘gpu_idx’ [-Wunused-parameter]
2882 | ggml_backend_t ue_loader_init_backend_gpu_idx(int gpu_idx, std::string & backend_name_out) {
| ~~~~^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_tensor* omni::upsample_encoder_v2::{anonymous}::ue_mha_mul_mat_checked(ggml_context*, ggml_tensor*, ggml_tensor*, const char*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3318:105: warning: unused parameter ‘label’ [-Wunused-parameter]
3318 | ggml_tensor * ue_mha_mul_mat_checked(ggml_context * ctx, ggml_tensor * a, ggml_tensor * b, const char * label) {
| ~~~~~~~~~~~~~^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘void omni::upsample_encoder_v2::ueMultiHeadedAttention::build_forward_qkv(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor**, ggml_tensor**, ggml_tensor**) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3418:19: warning: unused variable ‘Cq’ [-Wunused-variable]
3418 | const int64_t Cq = query_ctb->ne[0];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3419:19: warning: unused variable ‘Bk’ [-Wunused-variable]
3419 | const int64_t Bk = key_ctb->ne[2];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3421:19: warning: unused variable ‘Ck’ [-Wunused-variable]
3421 | const int64_t Ck = key_ctb->ne[0];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3422:19: warning: unused variable ‘Bv’ [-Wunused-variable]
3422 | const int64_t Bv = value_ctb->ne[2];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3423:19: warning: unused variable ‘Tv’ [-Wunused-variable]
3423 | const int64_t Tv = value_ctb->ne[1];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3424:19: warning: unused variable ‘Cv’ [-Wunused-variable]
3424 | const int64_t Cv = value_ctb->ne[0];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::upsample_encoder_v2::ueMultiHeadedAttention::build_forward_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor**) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3494:19: warning: unused variable ‘C’ [-Wunused-variable]
3494 | const int64_t C = query_ctb->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3501:19: warning: variable ‘t_cache’ set but not used [-Wunused-but-set-variable]
3501 | int64_t t_cache = 0;
| ^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::upsample_encoder_v2::uePositionwiseFeedForward::build_forward_graph(ggml_context*, ggml_tensor*) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3553:19: warning: unused variable ‘C’ [-Wunused-variable]
3553 | const int64_t C = xs_ctb->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_tensor* omni::upsample_encoder_v2::{anonymous}::ue_prelook_build_conv1d_f32_ctb(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3602:19: warning: unused variable ‘Cin’ [-Wunused-variable]
3602 | const int64_t Cin = x_ctb->ne[0];
| ^~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3604:19: warning: unused variable ‘K’ [-Wunused-variable]
3604 | const int64_t K = w_kic_oc->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3605:19: warning: unused variable ‘Cinw’ [-Wunused-variable]
3605 | const int64_t Cinw = w_kic_oc->ne[1];
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::upsample_encoder_v2::uePreLookaheadLayer::build_forward_graph(ggml_context*, ggml_tensor*) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3653:19: warning: unused variable ‘T’ [-Wunused-variable]
3653 | const int64_t T = inputs_ctb->ne[1];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3655:19: warning: unused variable ‘K1’ [-Wunused-variable]
3655 | const int64_t K1 = conv1_weight_->ne[0];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3662:19: warning: unused variable ‘K2’ [-Wunused-variable]
3662 | const int64_t K2 = conv2_weight_->ne[0];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::upsample_encoder_v2::uePreLookaheadLayer::build_forward_chunk_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor**) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3682:19: warning: unused variable ‘dt’ [-Wunused-variable]
3682 | const int64_t dt = inputs_ctb->ne[1];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3684:19: warning: unused variable ‘K1’ [-Wunused-variable]
3684 | const int64_t K1 = conv1_weight_->ne[0];
| ^~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_tensor* omni::upsample_encoder_v2::{anonymous}::ue_rel_mha_mul_mat_checked(ggml_context*, ggml_tensor*, ggml_tensor*, const char*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3791:109: warning: unused parameter ‘label’ [-Wunused-parameter]
3791 | ggml_tensor * ue_rel_mha_mul_mat_checked(ggml_context * ctx, ggml_tensor * a, ggml_tensor * b, const char * label) {
| ~~~~~~~~~~~~~^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::upsample_encoder_v2::ueRelPositionMultiHeadedAttention::build_forward_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor*, ggml_tensor**) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:3859:19: warning: variable ‘t_cache’ set but not used [-Wunused-but-set-variable]
3859 | int64_t t_cache = 0;
| ^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_tensor* omni::upsample_encoder_v2::{anonymous}::ue_up1d_build_conv1d_f32_ctb(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:4015:19: warning: unused variable ‘Cin’ [-Wunused-variable]
4015 | const int64_t Cin = x_ctb->ne[0];
| ^~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:4017:19: warning: unused variable ‘K’ [-Wunused-variable]
4017 | const int64_t K = w_kic_oc->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:4018:19: warning: unused variable ‘Cinw’ [-Wunused-variable]
4018 | const int64_t Cinw = w_kic_oc->ne[1];
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::upsample_encoder_v2::ueUpsample1D::build_forward_graph(ggml_context*, ggml_tensor*) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:4062:19: warning: unused variable ‘K’ [-Wunused-variable]
4062 | const int64_t K = conv_weight_->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::upsample_encoder_v2::ueUpsample1D::build_forward_chunk_graph(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor**) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:4083:19: warning: unused variable ‘K’ [-Wunused-variable]
4083 | const int64_t K = conv_weight_->ne[0];
| ^
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘ggml_tensor* omni::upsample_encoder_v2::ueUpsampleConformerEncoderV2::build_forward_chunk_graph(ggml_context*, ggml_tensor*, bool, ggml_tensor*, ggml_tensor*, ggml_tensor**, ggml_tensor**) const’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:4362:19: warning: variable ‘Tk1’ set but not used [-Wunused-but-set-variable]
4362 | int64_t Tk1 = 0;
| ^~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:4400:19: warning: variable ‘Tk2’ set but not used [-Wunused-but-set-variable]
4400 | int64_t Tk2 = 0;
| ^~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘bool omni::vocoder::hifigan2::hg2_gguf_model_loader::hg_gguf_model_loader_load_from_file(const std::string&, ggml_backend_t)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:4851:23: warning: the address of ‘ggml_tensor::name’ will never be NULL [-Waddress]
4851 | if (!t || !t->name) {
| ~~~^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include/ggml.h:653:14: note: ‘ggml_tensor::name’ declared here
653 | char name[GGML_MAX_NAME];
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘ggml_tensor* omni::vocoder::hifigan2::hg_istft16_repeat_checked(ggml_context*, ggml_tensor*, ggml_tensor*, const char*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:5292:64: warning: unused parameter ‘what’ [-Wunused-parameter]
5292 | const char * what) {
| ~~~~~~~~~~~~~~~^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In member function ‘bool omni::flow::flowExtraModelLoaderGGUF::load_from_file(const std::string&, ggml_backend_t)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:6806:23: warning: the address of ‘ggml_tensor::name’ will never be NULL [-Waddress]
6806 | if (!t || !t->name) {
| ~~~^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/ggml/src/../include/ggml.h:653:14: note: ‘ggml_tensor::name’ declared here
653 | char name[GGML_MAX_NAME];
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In function ‘void omni::flow::{anonymous}::runner_fill_noise_ctb(std::vector<float>&, int64_t, int64_t, int64_t, float, int64_t)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:7083:42: warning: unused parameter ‘offset_ct’ [-Wunused-parameter]
7083 | int64_t offset_ct) {
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp: In static member function ‘static ggml_tensor* omni::flow_matching::fmModulateUtils::build_modulate(ggml_context*, ggml_tensor*, ggml_tensor*, ggml_tensor*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:2421:15: warning: infinite recursion detected [-Winfinite-recursion]
2421 | ggml_tensor * fmModulateUtils::build_modulate(ggml_context * ctx,
| ^~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:2425:26: note: recursive call
2425 | return build_modulate(ctx, x, shift, scale);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/token2wav/token2wav-impl.cpp:2421:15: warning: function might be candidate for attribute ‘noreturn’ [-Wsuggest-attribute=noreturn]
2421 | ggml_tensor * fmModulateUtils::build_modulate(ggml_context * ctx,
| ^~~~~~~~~~~~~~~
[163/174] Building CXX object common/CMakeFiles/common.dir/arg.cpp.obj
[164/174] Building CXX object tools/omni/CMakeFiles/omni.dir/omni.cpp.obj
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool omni_eval_embed(llama_context*, const omni_embed*, int, int*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:291:31: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
291 | int n_embd = llama_n_embd(llama_get_model(ctx_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
In file included from /home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.h:2,
from /home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4:
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool prefill_with_emb(omni_context*, common_params*, float*, int, int, int*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:319:31: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
319 | int n_embd = llama_n_embd(llama_get_model(ctx_omni->ctx_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool prefill_emb_with_hidden(omni_context*, common_params*, float*, int, int, int*, float*&)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:353:30: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
353 | int n_embd = llama_n_embd(llama_get_model(ctx_omni->ctx_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:518:6: warning: no previous declaration for ‘bool vision_image_load_from_bytes(const unsigned char*, size_t, vision_image_u8*)’ [-Wmissing-declarations]
518 | bool vision_image_load_from_bytes(const unsigned char * bytes, size_t bytes_length, struct vision_image_u8 * img) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:579:6: warning: no previous declaration for ‘bool omni_image_embed_make_chunks_with_filename(vision_ctx*, int, std::string, std::vector<std::vector<float> >&)’ [-Wmissing-declarations]
579 | bool omni_image_embed_make_chunks_with_filename(struct vision_ctx * ctx_vision, int n_threads,
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:608:6: warning: no previous declaration for ‘bool audition_read_binary_file(const char*, std::vector<unsigned char>*)’ [-Wmissing-declarations]
608 | bool audition_read_binary_file(const char * fname, std::vector<uint8_t> * buf_res) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:629:21: warning: no previous declaration for ‘omni_embed* omni_audio_embed_make_with_bytes(audition_ctx*, int, audition_audio_u8*)’ [-Wmissing-declarations]
629 | struct omni_embed * omni_audio_embed_make_with_bytes(audition_ctx * ctx_audio, int n_threads, audition_audio_u8 * audio) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool eval_tokens_with_hidden(omni_context*, common_params*, std::vector<int>, int, int*, float*&)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:930:36: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
930 | const int n_embd = llama_n_embd(llama_get_model(ctx_omni->ctx_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool load_tts_weights_from_gguf(omni_context*, const char*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:1761:18: warning: variable ‘need_transpose’ set but not used [-Wunused-but-set-variable]
1761 | bool need_transpose = false;
| ^~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:1810:21: warning: unused variable ‘total_elements’ [-Wunused-variable]
1810 | int64_t total_elements = expected_hidden_size * expected_num_audio_tokens;
| ^~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool eval_tokens_tts(omni_context*, common_params*, std::vector<int>, int, int*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:2087:75: warning: unused parameter ‘params’ [-Wunused-parameter]
2087 | static bool eval_tokens_tts(struct omni_context* ctx_omni, common_params* params, std::vector<llama_token> tokens, int n_batch, int * n_past_tts) {
| ~~~~~~~~~~~~~~~^~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool prefill_with_emb_tts(omni_context*, common_params*, float*, int, int, int*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:2167:30: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
2167 | int n_embd = llama_n_embd(llama_get_model(ctx_omni->ctx_tts_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:2152:73: warning: unused parameter ‘params’ [-Wunused-parameter]
2152 | bool prefill_with_emb_tts(struct omni_context* ctx_omni, common_params* params, float* embed, int n_pos, int n_batch, int* n_past_tts) {
| ~~~~~~~~~~~~~~~^~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘llama_token sample_tts_token_simplex(common_sampler*, omni_context*, common_params*, int*, const std::vector<int>*, int, bool, bool)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:2561:17: warning: unused variable ‘logits_debug_dir’ [-Wunused-variable]
2561 | const char* logits_debug_dir = getenv("TTS_LOGITS_DEBUG_DIR");
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:2762:13: warning: no previous declaration for ‘llama_token sample_tts_token(common_sampler*, omni_context*, common_params*, int*, const std::vector<int>*, const std::vector<int>*, int, bool, bool)’ [-Wmissing-declarations]
2762 | llama_token sample_tts_token(struct common_sampler * smpl, struct omni_context * ctx_omni, common_params* params, int * n_past_tts, const std::vector<llama_token> * all_generated_tokens, const std::vector<llama_token> * chunk_generated_tokens, int token_index_in_chunk, bool force_no_eos, bool is_final_text_chunk = false) {
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘llama_token sample_tts_token(common_sampler*, omni_context*, common_params*, int*, const std::vector<int>*, const std::vector<int>*, int, bool, bool)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:2860:39: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
2860 | int hidden_size = llama_n_embd(llama_get_model(ctx_omni->ctx_tts_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:2894:9: warning: unused variable ‘eos_relative_idx’ [-Wunused-variable]
2894 | int eos_relative_idx = num_audio_tokens - 1; // EOS token relative index: 6561
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:2972:11: warning: unused variable ‘tau_r’ [-Wunused-variable]
2972 | float tau_r = 0.1f; // TTSSamplingParams.tau_r = 0.1
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘llama_model* llama_init(common_params*, std::string)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3525:53: warning: ‘llama_model* llama_load_model_from_file(const char*, llama_model_params)’ is deprecated: use llama_model_load_from_file instead [-Wdeprecated-declarations]
3525 | llama_model * model = llama_load_model_from_file(model_path.c_str(), model_params);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:413:47: note: declared here
413 | DEPRECATED(LLAMA_API struct llama_model * llama_load_model_from_file(
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘llama_model* llama_init_tts(common_params*, std::string, int)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3546:53: warning: ‘llama_model* llama_load_model_from_file(const char*, llama_model_params)’ is deprecated: use llama_model_load_from_file instead [-Wdeprecated-declarations]
3546 | llama_model * model = llama_load_model_from_file(model_path.c_str(), model_params);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:413:47: note: declared here
413 | DEPRECATED(LLAMA_API struct llama_model * llama_load_model_from_file(
| ^~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘omni_context* omni_init(common_params*, int, bool, std::string, int, const std::string&, bool, llama_model*, llama_context*, const std::string&)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3649:49: warning: ‘llama_context* llama_new_context_with_model(llama_model*, llama_context_params)’ is deprecated: use llama_init_from_model instead [-Wdeprecated-declarations]
3649 | ctx_llama = llama_new_context_with_model(model, ctx_params);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:445:49: note: declared here
445 | DEPRECATED(LLAMA_API struct llama_context * llama_new_context_with_model(
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3671:29: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3671 | llama_free_model(model);
| ~~~~~~~~~~~~~~~~^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3684:69: warning: ‘llama_context* llama_new_context_with_model(llama_model*, llama_context_params)’ is deprecated: use llama_init_from_model instead [-Wdeprecated-declarations]
3684 | llama_context * ctx_tts_llama = llama_new_context_with_model(tts_model, tts_ctx_params);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:445:49: note: declared here
445 | DEPRECATED(LLAMA_API struct llama_context * llama_new_context_with_model(
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3687:29: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3687 | llama_free_model(tts_model);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3690:29: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3690 | llama_free_model(model);
| ~~~~~~~~~~~~~~~~^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3720:29: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3720 | llama_free_model(tts_model);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3723:29: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3723 | llama_free_model(model);
| ~~~~~~~~~~~~~~~~^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3748:29: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3748 | llama_free_model(ctx_omni->model_tts);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3752:25: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3752 | llama_free_model(model);
| ~~~~~~~~~~~~~~~~^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3764:29: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3764 | llama_free_model(ctx_omni->model_tts);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:3768:25: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
3768 | llama_free_model(model);
| ~~~~~~~~~~~~~~~~^~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘void omni_free(omni_context*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4165:5: warning: possible problem detected in invocation of ‘operator delete’ [-Wdelete-incomplete]
4165 | delete ctx_omni->ctx_vision;
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4165:22: warning: invalid use of incomplete type ‘struct vision_ctx’
4165 | delete ctx_omni->ctx_vision;
| ~~~~~~~~~~^~~~~~~~~~
In file included from /home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni-impl.h:5,
from /home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:1:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/vision.h:10:8: note: forward declaration of ‘struct vision_ctx’
10 | struct vision_ctx;
| ^~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4165:5: note: neither the destructor nor the class-specific ‘operator delete’ will be called, even if they are declared when the class is defined
4165 | delete ctx_omni->ctx_vision;
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4170:25: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
4170 | llama_free_model(ctx_omni->model_tts);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4225:25: warning: ‘void llama_free_model(llama_model*)’ is deprecated: use llama_model_free instead [-Wdeprecated-declarations]
4225 | llama_free_model(ctx_omni->model);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:436:31: note: declared here
436 | DEPRECATED(LLAMA_API void llama_free_model(struct llama_model * model),
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4230:5: warning: possible problem detected in invocation of ‘operator delete’ [-Wdelete-incomplete]
4230 | delete ctx_omni->audio_input_manager;
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4230:22: warning: invalid use of incomplete type ‘class AudioInputManager’
4230 | delete ctx_omni->audio_input_manager;
| ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.h:267:11: note: forward declaration of ‘class AudioInputManager’
267 | class AudioInputManager * audio_input_manager = NULL;
| ^~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4230:5: note: neither the destructor nor the class-specific ‘operator delete’ will be called, even if they are declared when the class is defined
4230 | delete ctx_omni->audio_input_manager;
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4255:6: warning: no previous declaration for ‘void omni_set_language(omni_context*, const std::string&)’ [-Wmissing-declarations]
4255 | void omni_set_language(struct omni_context * ctx_omni, const std::string & lang) {
| ^~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘void process_audio(omni_context*, omni_embed*, common_params*, bool)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4295:116: warning: unused parameter ‘save_spk_emb’ [-Wunused-parameter]
4295 | static void process_audio(struct omni_context * ctx_omni, struct omni_embed * embeds, common_params * params, bool save_spk_emb=false) {
| ~~~~~^~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4301:6: warning: no previous declaration for ‘void eval_prefix(omni_context*, common_params*)’ [-Wmissing-declarations]
4301 | void eval_prefix(struct omni_context* ctx_omni, common_params* params){
| ^~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4307:6: warning: no previous declaration for ‘void eval_prefix_with_hidden(omni_context*, common_params*, float*&)’ [-Wmissing-declarations]
4307 | void eval_prefix_with_hidden(struct omni_context* ctx_omni, common_params* params, float *& hidden_states){
| ^~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4329:6: warning: no previous declaration for ‘void llm_thread_func(omni_context*, common_params*)’ [-Wmissing-declarations]
4329 | void llm_thread_func(omni_context* ctx_omni, common_params* params){
| ^~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘void llm_thread_func(omni_context*, common_params*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:4332:41: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
4332 | const int hidden_size = llama_n_embd(llama_get_model(ctx_omni->ctx_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘void play_wav_file(const std::string&)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5361:46: warning: unused parameter ‘wav_file_path’ [-Wunused-parameter]
5361 | static void play_wav_file(const std::string& wav_file_path) {
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5606:6: warning: no previous declaration for ‘void tts_thread_func_duplex(omni_context*, common_params*)’ [-Wmissing-declarations]
5606 | void tts_thread_func_duplex(struct omni_context * ctx_omni, common_params *params) {
| ^~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘void tts_thread_func_duplex(omni_context*, common_params*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5942:48: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
5942 | const int tts_n_embd = llama_n_embd(llama_get_model(ctx_omni->ctx_tts_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5931:17: warning: unused variable ‘n_tokens_orig’ [-Wunused-variable]
5931 | int n_tokens_orig = (int)(current_chunk_hidden_states.size() / current_chunk_n_embd);
| ^~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6163:52: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
6163 | const int tts_n_embd = llama_n_embd(llama_get_model(ctx_omni->ctx_tts_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5608:9: warning: variable ‘tts_n_past’ set but not used [-Wunused-but-set-variable]
5608 | int tts_n_past = 0;
| ^~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5612:10: warning: variable ‘tts_finish’ set but not used [-Wunused-but-set-variable]
5612 | bool tts_finish = false;
| ^~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5640:15: warning: unused variable ‘audio_eos_token_id’ [-Wunused-variable]
5640 | const int audio_eos_token_id = audio_bos_token_id + 6561;
| ^~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5641:15: warning: unused variable ‘text_eos_token_id’ [-Wunused-variable]
5641 | const int text_eos_token_id = 151692;
| ^~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:5642:15: warning: unused variable ‘num_audio_tokens’ [-Wunused-variable]
5642 | const int num_audio_tokens = 6562;
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6224:6: warning: no previous declaration for ‘void tts_thread_func(omni_context*, common_params*)’ [-Wmissing-declarations]
6224 | void tts_thread_func(struct omni_context * ctx_omni, common_params *params) {
| ^~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘void tts_thread_func(omni_context*, common_params*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6694:48: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
6694 | const int tts_n_embd = llama_n_embd(llama_get_model(ctx_omni->ctx_tts_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6881:37: warning: unused variable ‘llm_emb_check’ [-Wunused-variable]
6881 | float * llm_emb_check = llm_embeds.data() + 0 * tts_n_embd;
| ^~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6882:37: warning: unused variable ‘proj_hidden_check’ [-Wunused-variable]
6882 | float * proj_hidden_check = projected_hidden.data() + 0 * tts_n_embd;
| ^~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6883:37: warning: unused variable ‘merged_check’ [-Wunused-variable]
6883 | float * merged_check = merged_embeddings.data() + 0 * tts_n_embd;
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6986:18: warning: unused variable ‘is_final_chunk’ [-Wunused-variable]
6986 | bool is_final_chunk = llm_finish;
| ^~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6987:18: warning: variable ‘tts_success’ set but not used [-Wunused-but-set-variable]
6987 | bool tts_success = false;
| ^~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6226:9: warning: variable ‘tts_n_past’ set but not used [-Wunused-but-set-variable]
6226 | int tts_n_past = 0; // TTS model's n_past counter
| ^~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6230:10: warning: variable ‘tts_finish’ set but not used [-Wunused-but-set-variable]
6230 | bool tts_finish = false;
| ^~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6239:17: warning: unused variable ‘info’ [-Wunused-variable]
6239 | struct stat info;
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6305:15: warning: unused variable ‘audio_eos_token_id’ [-Wunused-variable]
6305 | const int audio_eos_token_id = audio_bos_token_id + 6561; // 158248
| ^~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6306:15: warning: unused variable ‘text_eos_token_id’ [-Wunused-variable]
6306 | const int text_eos_token_id = 151692; // 用于文本结束检测
| ^~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6307:15: warning: unused variable ‘spk_emb_token_id’ [-Wunused-variable]
6307 | const int spk_emb_token_id = 21143;
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6308:15: warning: unused variable ‘num_audio_tokens’ [-Wunused-variable]
6308 | const int num_audio_tokens = 6562;
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:6309:15: warning: unused variable ‘max_audio_tokens’ [-Wunused-variable]
6309 | const int max_audio_tokens = 1000; // Maximum audio tokens to generate per text chunk
| ^~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8144:6: warning: no previous declaration for ‘void t2w_thread_func_python(omni_context*, common_params*)’ [-Wmissing-declarations]
8144 | void t2w_thread_func_python(struct omni_context * ctx_omni, common_params *params) {
| ^~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘void t2w_thread_func_python(omni_context*, common_params*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8178:15: warning: unused variable ‘sample_rate’ [-Wunused-variable]
8178 | const int sample_rate = 24000; // Python Token2Wav 输出采样率
| ^~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8144:76: warning: unused parameter ‘params’ [-Wunused-parameter]
8144 | void t2w_thread_func_python(struct omni_context * ctx_omni, common_params *params) {
| ~~~~~~~~~~~~~~~^~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8415:6: warning: no previous declaration for ‘void t2w_thread_func_cpp(omni_context*, common_params*)’ [-Wmissing-declarations]
8415 | void t2w_thread_func_cpp(struct omni_context * ctx_omni, common_params *params) {
| ^~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘void t2w_thread_func_cpp(omni_context*, common_params*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8673:20: warning: unused variable ‘buffer_before_slide’ [-Wunused-variable]
8673 | size_t buffer_before_slide = token_buffer.size();
| ^~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8558:16: warning: unused variable ‘buffer_before’ [-Wunused-variable]
8558 | size_t buffer_before = token_buffer.size();
| ^~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8415:73: warning: unused parameter ‘params’ [-Wunused-parameter]
8415 | void t2w_thread_func_cpp(struct omni_context * ctx_omni, common_params *params) {
| ~~~~~~~~~~~~~~~^~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: At global scope:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8763:6: warning: no previous declaration for ‘void t2w_thread_func(omni_context*, common_params*)’ [-Wmissing-declarations]
8763 | void t2w_thread_func(struct omni_context * ctx_omni, common_params *params) {
| ^~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool stream_prefill(omni_context*, std::string, std::string, int, int, std::string)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:8823:41: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
8823 | const int hidden_size = llama_n_embd(llama_get_model(ctx_omni->ctx_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:9037:49: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
9037 | const int hidden_size = llama_n_embd(llama_get_model(ctx_omni->ctx_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In lambda function:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:9085:107: warning: comparison of integer expressions of different signedness: ‘std::queue<omni_embeds*>::size_type’ {aka ‘long long unsigned int’} and ‘int’ [-Wsign-compare]
9085 | ctx_omni->llm_thread_info->cv.wait(lock, [&] { return ctx_omni->llm_thread_info->queue.size() < ctx_omni->llm_thread_info->MAX_QUEUE_SIZE; });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool stream_decode(omni_context*, std::string, int)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:9355:38: warning: ‘int32_t llama_n_embd(const llama_model*)’ is deprecated: use llama_model_n_embd instead [-Wdeprecated-declarations]
9355 | int llm_n_embd = llama_n_embd(llama_get_model(ctx_omni->ctx_llama));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:469:34: note: declared here
469 | DEPRECATED(LLAMA_API int32_t llama_n_embd (const struct llama_model * model), "use llama_model_n_embd instead");
| ^~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/src/../include/llama.h:29:36: note: in definition of macro ‘DEPRECATED’
29 | # define DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
| ^~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In lambda function:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:9650:111: warning: comparison of integer expressions of different signedness: ‘std::queue<LLMOut*>::size_type’ {aka ‘long long unsigned int’} and ‘const int’ [-Wsign-compare]
9650 | ctx_omni->tts_thread_info->cv.wait(lock, [&] { return ctx_omni->tts_thread_info->queue.size() < ctx_omni->tts_thread_info->MAX_QUEUE_SIZE; });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp: In function ‘bool stream_decode(omni_context*, std::string, int)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:9613:22: warning: unused variable ‘llm_elapsed_ms’ [-Wunused-variable]
9613 | auto llm_elapsed_ms = std::chrono::duration_cast<std::chrono::milliseconds>(
| ^~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/omni.cpp:9321:9: warning: unused variable ‘chunk_idx’ [-Wunused-variable]
9321 | int chunk_idx = 0;
| ^~~~~~~~~
[165/174] Building CXX object common/CMakeFiles/common.dir/chat.cpp.obj
[166/174] Building CXX object tools/omni/CMakeFiles/omni.dir/audition.cpp.obj
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/audition.cpp: In function ‘bool audition_audio_batch_encode(audition_ctx*, int, const audition_audio_f32_batch*, float*)’:
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/audition.cpp:1438:15: warning: unused variable ‘n_pos’ [-Wunused-variable]
1438 | const int n_pos = num_patches + (model.class_embedding ? 1 : 0);
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/audition.cpp:1439:15: warning: unused variable ‘pos_w’ [-Wunused-variable]
1439 | const int pos_w = image_size_width / patch_size;
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/audition.cpp:1440:15: warning: unused variable ‘pos_h’ [-Wunused-variable]
1440 | const int pos_h = image_size_height / patch_size;
| ^~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/audition.cpp:1442:16: warning: unused variable ‘use_window_attn’ [-Wunused-variable]
1442 | const bool use_window_attn = hparams.n_wa_pattern > 0; // for qwen2.5vl
| ^~~~~~~~~~~~~~~
/home/zhout/project/edge_infer/llama.cpp-omni/tools/omni/audition.cpp:1462:10: warning: variable ‘set_input_i32’ set but not used [-Wunused-but-set-variable]
1462 | auto set_input_i32 = [&get_inp_tensor](const char * name, std::vector<int32_t> & values) {
| ^~~~~~~~~~~~~
[167/174] Building CXX object ggml/src/ggml-vulkan/CMakeFiles/ggml-vulkan.dir/ggml-vulkan.cpp.obj
[168/174] Linking CXX static library ggml/src/ggml-vulkan/ggml-vulkan.a
[169/174] Linking CXX static library ggml/src/ggml.a
[170/174] Linking CXX static library src/libllama.a
[171/174] Linking CXX static library common/libcommon.a
[172/174] Linking CXX static library tools/omni/libomni.a
[173/174] Linking CXX executable bin/llama-omni-cli.exe
@@ -0,0 +1,22 @@
CMAKE_BUILD_TYPE=Release
-- Setting GGML_NATIVE_DEFAULT to OFF
-- Warning: ccache not found - consider installing it for faster compilation or disable this warning with GGML_CCACHE=OFF
-- CMAKE_SYSTEM_PROCESSOR: x86_64
-- GGML_SYSTEM_ARCH: x86
-- Including CPU backend
-- x86 detected
-- Adding CPU backend variant ggml-cpu:
-- Found Vulkan: /mnt/c/Windows/System32/vulkan-1.dll (found version "1.4.341") found components: glslc missing components: glslangValidator
-- Vulkan found
-- GL_KHR_cooperative_matrix supported by glslc
-- GL_NV_cooperative_matrix2 supported by glslc
-- GL_EXT_integer_dot_product supported by glslc
-- GL_EXT_bfloat16 supported by glslc
-- Host compiler: /usr/bin/gcc /usr/bin/g++
-- vulkan-shaders-gen toolchain file: /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan/host-toolchain.cmake
-- Including Vulkan backend
-- ggml version: 0.9.4
-- ggml commit: 5202b7b
-- Configuring done (1.3s)
-- Generating done (0.3s)
-- Build files have been written to: /home/zhout/project/edge_infer/llama.cpp-omni/build-win64-vulkan
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@@ -0,0 +1,918 @@
=== Model Paths ===
Base dir: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf
LLM: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf\MiniCPM-o-4_5-Q4_K_M.gguf [OK]
Vision: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/vision/MiniCPM-o-4_5-vision-F16.gguf [OK]
Audio: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/audio/MiniCPM-o-4_5-audio-F16.gguf [OK]
TTS: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts/MiniCPM-o-4_5-tts-F16.gguf [OK]
Projector: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts/MiniCPM-o-4_5-projector-F16.gguf [OK]
===================
=== Initializing Omni Context ===
Media type: 2 (omni: audio+vision)
TTS enabled: yes
Context size: 2048
GPU layers: 99
Token2Wav device: cpu
Vision backend: metal
TTS bin dir: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts
Ref audio: C:\Users\zhout\w2\minicpmo_cpp_radeon\default_ref_audio.wav
22:28:06.598 === omni_init start
22:28:06.598 media_type = 2, duplex_mode = 0, base_output_dir = ./tools/omni/output
22:28:06.598 === omni_init: loading new LLM model
22:28:09.715 === omni_init: loading TTS model
22:28:09.715 TTS model: loading with n_gpu_layers=0
22:28:10.056 TTS sampler: temp=0.80, top_p=0.85, top_k=25, rep_penalty=1.05
22:28:10.056 TTS: loading weights from GGUF (emb_code, emb_text, projector_semantic, head_code)...
22:28:10.564 TTS: head_code shape: dim0=6562, dim1=768, will transpose to [6562, 768]
22:28:10.573 TTS: head_code loaded, verifying first few values:
22:28:10.573 head_code_weight[0] = 0.01361084 (expect ~0.01385498)
22:28:10.573 head_code_weight[1] = -0.01660156 (expect ~-0.01647949)
22:28:10.573 head_code_weight[768] = 0.04101562 (this is weight[1, 0], expect ~0.04150391)
22:28:10.668 TTS: weights loaded successfully
22:28:10.668 Projector: loading from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts/MiniCPM-o-4_5-projector-F16.gguf
22:28:10.677 Projector: loaded successfully
22:28:10.677 === omni_init: loading APM model
22:28:10.953 APM: init from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/audio/MiniCPM-o-4_5-audio-F16.gguf
22:28:11.918 Token2Wav: found models in C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/token2wav-gguf
22:28:11.919 Token2Wav: all model files found, initializing session...
22:28:11.919 Token2Wav: non-CUDA backend, vocoder using CPU for better performance
22:28:11.919 Token2Wav: using prompt_cache from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/token2wav-gguf/prompt_cache.gguf
22:28:12.286 Token2Wav: initialized successfully
22:28:12.286 Python T2W: script_dir=./tools/omni/pyt2w, model_dir=./tools/omni/pyt2w/token2wav
22:28:12.286 Token2Wav: 使用 C++ 实现
22:28:12.286 === omni_init success: ctx_llama = 00000220286afaa0
=== Running test case ===
Audio prefix: C:\Users\zhout\w2\minicpmo_cpp_radeon\fixture_
Count: 2
22:28:12.286 stream_prefill: n_past = 0
voice_clone_prompt = <|im_start|>system
模仿音频样本的音色并生�新的内容。
<|audio_start|>
assistant_prompt = <|audio_end|>你的任务是用这�声音模��当一个助手。请认真�高质�地回�用户的问题。请用高自然度的方�和用户�天。<|im_end|>
<|im_start|>user
22:28:12.286 system prompt ref_audio: C:\Users\zhout\w2\minicpmo_cpp_radeon\fixture_0000.wav
22:28:13.326 system prompt ref_audio embedding: n_pos=20
22:28:13.997 🔒 n_keep 设置为 72 (system prompt tokens),这部分永远�会被滑动窗�删除
22:28:13.997 stream_prefill(index=0): system prompt �始化完�,ref_audio 已在其中 prefill
22:28:13.997 [SW] system_prompt registered: preserve_length=72 (will be protected from sliding)
22:28:13.997 n_past = 72
22:28:13.997
c++ finish stream_prefill(index=0). n_past=72, n_keep=72, n_ctx=2048
prefill 0 (audio) : 1.71101 s
22:28:16.166 stream_prefill(index=1): processing user audio: C:\Users\zhout\w2\minicpmo_cpp_radeon\fixture_0001.wav
22:28:16.335 stream_prefill(index=1): user audio embedding: n_pos=20
22:28:16.627
c++ finish stream_prefill(index=1). n_past=161, n_keep=72, n_ctx=2048
prefill 1 (audio+vision) : 2.62999 s
22:28:16.627 � stream_decode 开始: n_past=161, n_keep=72, n_ctx=2048, duplex_mode=0
22:28:16.627 stream_decode: create tts thread (simplex mode)
22:28:16.627 stream_decode: create t2w thread
22:28:16.627 wait prefill done
22:28:16.628 � [�工TTS] 添加 assistant prompt: "<|im_end|>
<|im_start|>assistant
<think>
</think>
<|tts_bos|>", n_past=161
22:28:16.628 T2W thread (C++) started
22:28:16.631 TTS: 创建�工模�输出目录: ./tools/omni/output/round_000
22:28:16.632 TTS thread started
22:28:16.783 � [�工TTS] assistant prompt 完�, n_past=171
22:28:16.784 LLM decode: max_tgt_len = 2048, n_predict = -1, n_ctx = 2048
22:28:17.359 LLM->TTS: text='你知��,有时候啊,我也会想啊', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[107733 101037 3837 104854 103924 3837 35946 103977 99172 103924]
22:28:17.359 TTS<-LLM: chunk_idx=0, text='你知��,有时候啊,我也会想啊', n_tokens=10, hidden_size=40960, token_ids=[107733 101037 3837 104854 103924 3837 35946 103977 99172 103924]
22:28:17.359 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:17.359 TTS: before empty check - response.empty=0, response='你知��,有时候啊,我也会想啊', llm_finish=0
22:28:17.359 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:17.359 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:17.360 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:17.402 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_0/merged_embeddings.txt
22:28:17.402 TTS Simplex: generating audio tokens for chunk 0 (n_tokens=10, tts_n_embd=768)
22:28:17.402 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=0, new_size=11)
22:28:17.402 TTS Simplex: first chunk - cleared KV cache
22:28:17.402 TTS Simplex: first chunk - cleared tts_all_generated_tokens and tts_token_buffer
22:28:17.479 TTS Simplex: prefill completed, n_past_tts=11
22:28:17.479 TTS Simplex: sampler created
22:28:17.479 TTS simplex: is_audio_bos=true (first audio token)
22:28:17.524 TTS Simplex Phase1: token 1/500: rel_id=1571
22:28:17.545 TTS Simplex Phase1: token 2/500: rel_id=6486
22:28:17.564 TTS Simplex Phase1: token 3/500: rel_id=4299
22:28:17.583 TTS Simplex Phase1: token 4/500: rel_id=4299
22:28:17.603 TTS Simplex Phase1: token 5/500: rel_id=4299
22:28:17.992 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 25, buffer=25)
22:28:17.992 TTS Simplex Phase1: token 25/500: rel_id=4299
22:28:17.992 T2W线程(C++): 轮次切� (-1 -> 0),更新输出目录
22:28:17.992 T2W线程(C++): 新输出目录 ./tools/omni/output/round_000/tts_wav
22:28:18.074 LLM->TTS: text=',生活真的挺有��的。�天早上醒�,', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[3837 99424 100672 101174 113062 1773 101922 105083 109877 3837]
22:28:18.524 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 50, buffer=25)
22:28:18.524 TTS Simplex Phase1: token 50/500: rel_id=1703
22:28:18.595 TTS Simplex Phase1: EOS token at step 54
22:28:18.595 TTS Simplex: chunk 结�,tts_token_buffer 剩余 3 tokens (�留等下一个 chunk)
22:28:18.595 TTS Simplex: generated 53 audio tokens for chunk 0
22:28:18.595 TTS Simplex: chunk 0 first tokens: [1571 6486 4299 4299 4299 ], last tokens: [731 1703 1951 2112 719 ]
22:28:18.595 TTS Simplex: updated tts_n_past_accumulated=64, total_generated_tokens=53
22:28:18.596 TTS<-LLM: chunk_idx=1, text=',生活真的挺有��的。�天早上醒�,', n_tokens=10, hidden_size=40960, token_ids=[3837 99424 100672 101174 113062 1773 101922 105083 109877 3837]
22:28:18.596 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:18.596 TTS: before empty check - response.empty=0, response=',生活真的挺有æ„�æ€�的。æ¯�天早上醒æ�', llm_finish=0
22:28:18.596 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:18.596 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:18.596 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:18.630 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_1/merged_embeddings.txt
22:28:18.630 TTS Simplex: generating audio tokens for chunk 1 (n_tokens=10, tts_n_embd=768)
22:28:18.630 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=1, new_size=11)
22:28:18.630 TTS Simplex: chunk 1 - keeping KV cache, n_past_tts=64
22:28:18.665 TTS Simplex: prefill completed, n_past_tts=75
22:28:18.665 TTS Simplex: sampler created
22:28:18.696 TTS Simplex Phase1: token 1/500: rel_id=728
22:28:18.719 TTS Simplex Phase1: token 2/500: rel_id=4613
22:28:18.740 TTS Simplex Phase1: token 3/500: rel_id=4803
22:28:18.763 TTS Simplex Phase1: token 4/500: rel_id=4551
22:28:18.781 TTS Simplex Phase1: token 5/500: rel_id=4466
22:28:18.849 LLM->TTS: text='太阳照在脸上,就觉得这一天充满了�能。', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[101281 99331 18493 104488 3837 115119 112480 106890 87267 1773]
22:28:19.156 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 22, buffer=25)
22:28:19.226 TTS Simplex Phase1: token 25/500: rel_id=4299
22:28:19.617 LLM->TTS: text='�管�一天�生啥事,��新的一天�了', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[101260 115982 99726 101417 29826 3837 100671 118580 35727 101161]
22:28:19.667 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 47, buffer=25)
22:28:19.700 TTS Simplex Phase1: token 50/500: rel_id=219
22:28:19.953 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 72, buffer=25)
22:28:19.988 TTS Simplex Phase1: token 75/500: rel_id=4299
22:28:20.178 TTS Simplex Phase1: EOS token at step 92
22:28:20.178 TTS Simplex: chunk 结�,tts_token_buffer 剩余 19 tokens (�留等下一个 chunk)
22:28:20.178 TTS Simplex: generated 91 audio tokens for chunk 1
22:28:20.178 TTS Simplex: chunk 1 first tokens: [728 4613 4803 4551 4466 ], last tokens: [870 2726 4489 5205 6387 ]
22:28:20.178 TTS Simplex: updated tts_n_past_accumulated=166, total_generated_tokens=144
22:28:20.179 TTS<-LLM: chunk_idx=2, text='太阳照在脸上,就觉得这一天充满了�能。', n_tokens=10, hidden_size=40960, token_ids=[101281 99331 18493 104488 3837 115119 112480 106890 87267 1773]
22:28:20.179 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:20.179 TTS: before empty check - response.empty=0, response='太阳照在脸上,就觉得这一天充满了å�', llm_finish=0
22:28:20.179 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:20.179 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:20.179 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:20.213 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_2/merged_embeddings.txt
22:28:20.213 TTS Simplex: generating audio tokens for chunk 2 (n_tokens=10, tts_n_embd=768)
22:28:20.213 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=2, new_size=11)
22:28:20.213 TTS Simplex: chunk 2 - keeping KV cache, n_past_tts=166
22:28:20.247 TTS Simplex: prefill completed, n_past_tts=177
22:28:20.247 TTS Simplex: sampler created
22:28:20.268 TTS Simplex Phase1: token 1/500: rel_id=2502
22:28:20.293 TTS Simplex Phase1: token 2/500: rel_id=974
22:28:20.325 TTS Simplex Phase1: token 3/500: rel_id=1163
22:28:20.350 TTS Simplex Phase1: token 4/500: rel_id=5970
22:28:20.378 TTS Simplex Phase1: token 5/500: rel_id=957
22:28:20.405 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 6, buffer=25)
22:28:20.938 TTS Simplex Phase1: token 25/500: rel_id=2112
22:28:21.011 LLM->TTS: text=',就有机会�新开始。你有没有觉得,', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[3837 104435 101135 70361 55286 1773 56568 104710 99801 3837]
22:28:21.056 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 31, buffer=25)
22:28:21.326 TTS Simplex Phase1: token 50/500: rel_id=5914
22:28:21.408 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 56, buffer=25)
22:28:21.597 🎉 首�时间 (First Audio Response): 4969ms
22:28:21.597 T2W线程: wav_0.wav | 0.84s audio | 3603.6ms inference | RTF=4.29 | t=4969ms
22:28:21.674 TTS Simplex Phase1: token 75/500: rel_id=4593
22:28:21.745 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 81, buffer=25)
22:28:21.841 TTS Simplex Phase1: EOS token at step 90
22:28:21.841 TTS Simplex: chunk 结�,tts_token_buffer 剩余 8 tokens (�留等下一个 chunk)
22:28:21.841 TTS Simplex: generated 89 audio tokens for chunk 2
22:28:21.841 TTS Simplex: chunk 2 first tokens: [2502 974 1163 5970 957 ], last tokens: [4382 5937 2130 6051 1539 ]
22:28:21.841 TTS Simplex: updated tts_n_past_accumulated=266, total_generated_tokens=233
22:28:21.843 TTS<-LLM: chunk_idx=3, text='�管�一天�生啥事,��新的一天�了', n_tokens=10, hidden_size=40960, token_ids=[101260 115982 99726 101417 29826 3837 100671 118580 35727 101161]
22:28:21.843 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:21.843 TTS: before empty check - response.empty=0, response='ä¸�管å‰�一天å�‘生啥事,å�ªè¦�新的一天æ�', llm_finish=0
22:28:21.843 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:21.843 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:21.843 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:21.877 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_3/merged_embeddings.txt
22:28:21.877 TTS Simplex: generating audio tokens for chunk 3 (n_tokens=10, tts_n_embd=768)
22:28:21.877 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=3, new_size=11)
22:28:21.877 TTS Simplex: chunk 3 - keeping KV cache, n_past_tts=266
22:28:21.913 TTS Simplex: prefill completed, n_past_tts=277
22:28:21.913 TTS Simplex: sampler created
22:28:21.936 TTS Simplex Phase1: token 1/500: rel_id=2676
22:28:21.959 TTS Simplex Phase1: token 2/500: rel_id=4981
22:28:21.981 TTS Simplex Phase1: token 3/500: rel_id=5065
22:28:22.001 TTS Simplex Phase1: token 4/500: rel_id=5775
22:28:22.026 TTS Simplex Phase1: token 5/500: rel_id=6501
22:28:22.300 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 17, buffer=25)
22:28:22.482 TTS Simplex Phase1: token 25/500: rel_id=6486
22:28:22.597 LLM->TTS: text='就算�到�难的事,��咬咬牙', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[104501 104011 87256 99349 104140 3837 100671 105118 105118 100446]
22:28:22.738 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 42, buffer=25)
22:28:22.838 TTS Simplex Phase1: token 50/500: rel_id=2274
22:28:23.048 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 67, buffer=25)
22:28:23.146 TTS Simplex Phase1: token 75/500: rel_id=1648
22:28:23.335 TTS Simplex Phase1: EOS token at step 91
22:28:23.335 TTS Simplex: chunk 结�,tts_token_buffer 剩余 23 tokens (�留等下一个 chunk)
22:28:23.336 TTS Simplex: generated 90 audio tokens for chunk 3
22:28:23.336 TTS Simplex: chunk 3 first tokens: [2676 4981 5065 5775 6501 ], last tokens: [5323 1132 476 974 2756 ]
22:28:23.336 TTS Simplex: updated tts_n_past_accumulated=367, total_generated_tokens=323
22:28:23.336 TTS<-LLM: chunk_idx=4, text=',就有机会�新开始。你有没有觉得,', n_tokens=10, hidden_size=40960, token_ids=[3837 104435 101135 70361 55286 1773 56568 104710 99801 3837]
22:28:23.336 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:23.337 TTS: before empty check - response.empty=0, response=',就有机会é‡�新开始。你有没有觉得ï¼', llm_finish=0
22:28:23.337 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:23.337 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:23.337 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:23.368 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_4/merged_embeddings.txt
22:28:23.368 TTS Simplex: generating audio tokens for chunk 4 (n_tokens=10, tts_n_embd=768)
22:28:23.368 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=4, new_size=11)
22:28:23.368 TTS Simplex: chunk 4 - keeping KV cache, n_past_tts=367
22:28:23.397 TTS Simplex: prefill completed, n_past_tts=378
22:28:23.397 TTS Simplex: sampler created
22:28:23.409 TTS Simplex Phase1: token 1/500: rel_id=4441
22:28:23.422 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 2, buffer=25)
22:28:23.422 TTS Simplex Phase1: token 2/500: rel_id=6455
22:28:23.436 TTS Simplex Phase1: token 3/500: rel_id=2229
22:28:23.450 TTS Simplex Phase1: token 4/500: rel_id=4803
22:28:23.465 TTS Simplex Phase1: token 5/500: rel_id=6261
22:28:23.755 TTS Simplex Phase1: token 25/500: rel_id=1944
22:28:23.783 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 27, buffer=25)
22:28:24.439 TTS Simplex Phase1: token 50/500: rel_id=5325
22:28:24.513 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 52, buffer=25)
22:28:24.695 LLM->TTS: text='挺过去,回头看的时候,�而觉得挺酷', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[101174 100688 3837 115204 103920 3837 104503 99801 101174 102382]
22:28:24.760 T2W线程: wav_1.wav | 1.00s audio | 3161.9ms inference | RTF=3.16 | t=8132ms
22:28:24.933 TTS Simplex Phase1: token 75/500: rel_id=6486
22:28:24.957 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 77, buffer=25)
22:28:25.045 TTS Simplex Phase1: EOS token at step 85
22:28:25.045 TTS Simplex: chunk 结�,tts_token_buffer 剩余 7 tokens (�留等下一个 chunk)
22:28:25.045 TTS Simplex: generated 84 audio tokens for chunk 4
22:28:25.045 TTS Simplex: chunk 4 first tokens: [4441 6455 2229 4803 6261 ], last tokens: [4299 4299 1726 5614 4831 ]
22:28:25.045 TTS Simplex: updated tts_n_past_accumulated=462, total_generated_tokens=407
22:28:25.047 TTS<-LLM: chunk_idx=5, text='就算�到�难的事,��咬咬牙', n_tokens=10, hidden_size=40960, token_ids=[104501 104011 87256 99349 104140 3837 100671 105118 105118 100446]
22:28:25.047 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:25.047 TTS: before empty check - response.empty=0, response='就算�到�难的事,��咬咬牙', llm_finish=0
22:28:25.047 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:25.047 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:25.047 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:25.081 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_5/merged_embeddings.txt
22:28:25.081 TTS Simplex: generating audio tokens for chunk 5 (n_tokens=10, tts_n_embd=768)
22:28:25.081 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=5, new_size=11)
22:28:25.081 TTS Simplex: chunk 5 - keeping KV cache, n_past_tts=462
22:28:25.122 TTS Simplex: prefill completed, n_past_tts=473
22:28:25.122 TTS Simplex: sampler created
22:28:25.146 TTS Simplex Phase1: token 1/500: rel_id=2306
22:28:25.172 TTS Simplex Phase1: token 2/500: rel_id=667
22:28:25.197 TTS Simplex Phase1: token 3/500: rel_id=2125
22:28:25.221 TTS Simplex Phase1: token 4/500: rel_id=4580
22:28:25.244 TTS Simplex Phase1: token 5/500: rel_id=4520
22:28:25.559 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 18, buffer=25)
22:28:25.737 TTS Simplex Phase1: token 25/500: rel_id=4678
22:28:25.817 LLM->TTS: text='的?其实啊,�个人心里都��一个�', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[9370 11319 101045 103924 3837 101587 101998 71268 114880 107861]
22:28:26.001 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 43, buffer=25)
22:28:26.089 TTS Simplex Phase1: token 50/500: rel_id=5
22:28:26.318 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 68, buffer=25)
22:28:26.345 TTS Simplex Phase1: EOS token at step 71
22:28:26.345 TTS Simplex: chunk 结�,tts_token_buffer 剩余 2 tokens (�留等下一个 chunk)
22:28:26.345 TTS Simplex: generated 70 audio tokens for chunk 5
22:28:26.345 TTS Simplex: chunk 5 first tokens: [2306 667 2125 4580 4520 ], last tokens: [5241 1862 1376 2357 6401 ]
22:28:26.345 TTS Simplex: updated tts_n_past_accumulated=543, total_generated_tokens=477
22:28:26.346 TTS<-LLM: chunk_idx=6, text='挺过去,回头看的时候,�而觉得挺酷', n_tokens=10, hidden_size=40960, token_ids=[101174 100688 3837 115204 103920 3837 104503 99801 101174 102382]
22:28:26.346 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:26.346 TTS: before empty check - response.empty=0, response='挺过去,回头看的时候,å��而觉得挺é…', llm_finish=0
22:28:26.346 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:26.346 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:26.346 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:26.390 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_6/merged_embeddings.txt
22:28:26.390 TTS Simplex: generating audio tokens for chunk 6 (n_tokens=10, tts_n_embd=768)
22:28:26.390 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=6, new_size=11)
22:28:26.390 TTS Simplex: chunk 6 - keeping KV cache, n_past_tts=543
22:28:26.433 TTS Simplex: prefill completed, n_past_tts=554
22:28:26.433 TTS Simplex: sampler created
22:28:26.457 TTS Simplex Phase1: token 1/500: rel_id=2591
22:28:26.482 TTS Simplex Phase1: token 2/500: rel_id=566
22:28:26.504 TTS Simplex Phase1: token 3/500: rel_id=974
22:28:26.534 TTS Simplex Phase1: token 4/500: rel_id=4571
22:28:26.558 TTS Simplex Phase1: token 5/500: rel_id=4579
22:28:27.086 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 23, buffer=25)
22:28:27.152 TTS Simplex Phase1: token 25/500: rel_id=4921
22:28:27.154 LLM->TTS: text='宇宙,里�装�勇气�梦想和一点点', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[105339 3837 100420 98641 99164 106860 5373 102294 33108 107342]
22:28:27.499 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 48, buffer=25)
22:28:27.530 TTS Simplex Phase1: token 50/500: rel_id=0
22:28:27.898 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 73, buffer=25)
22:28:27.900 T2W线程: wav_2.wav | 1.00s audio | 3138.7ms inference | RTF=3.14 | t=11272ms
22:28:27.922 TTS Simplex Phase1: token 75/500: rel_id=1431
22:28:27.989 TTS Simplex Phase1: EOS token at step 81
22:28:27.989 TTS Simplex: chunk 结�,tts_token_buffer 剩余 7 tokens (�留等下一个 chunk)
22:28:27.989 TTS Simplex: generated 80 audio tokens for chunk 6
22:28:27.989 TTS Simplex: chunk 6 first tokens: [2591 566 974 4571 4579 ], last tokens: [1055 1460 1625 1649 5332 ]
22:28:27.989 TTS Simplex: updated tts_n_past_accumulated=634, total_generated_tokens=557
22:28:27.989 TTS<-LLM: chunk_idx=7, text='的?其实啊,�个人心里都��一个�', n_tokens=10, hidden_size=40960, token_ids=[9370 11319 101045 103924 3837 101587 101998 71268 114880 107861]
22:28:27.989 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:27.989 TTS: before empty check - response.empty=0, response='的?其实啊,æ¯�个人心里都è—�ç�€ä¸€ä¸ªå°', llm_finish=0
22:28:27.989 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:27.989 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:27.990 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:28.021 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_7/merged_embeddings.txt
22:28:28.021 TTS Simplex: generating audio tokens for chunk 7 (n_tokens=10, tts_n_embd=768)
22:28:28.021 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=7, new_size=11)
22:28:28.021 TTS Simplex: chunk 7 - keeping KV cache, n_past_tts=634
22:28:28.067 TTS Simplex: prefill completed, n_past_tts=645
22:28:28.067 TTS Simplex: sampler created
22:28:28.091 TTS Simplex Phase1: token 1/500: rel_id=2742
22:28:28.116 TTS Simplex Phase1: token 2/500: rel_id=4758
22:28:28.140 TTS Simplex Phase1: token 3/500: rel_id=1943
22:28:28.164 TTS Simplex Phase1: token 4/500: rel_id=59
22:28:28.188 TTS Simplex Phase1: token 5/500: rel_id=63
22:28:28.518 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 18, buffer=25)
22:28:28.691 TTS Simplex Phase1: token 25/500: rel_id=6486
22:28:28.782 LLM->TTS: text='�期待。别怕犯错,�还没', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[30709 104177 1773 62922 99756 100238 28726 3837 100165 104789]
22:28:28.965 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 43, buffer=25)
22:28:29.058 TTS Simplex Phase1: token 50/500: rel_id=3170
22:28:29.286 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 68, buffer=25)
22:28:29.376 TTS Simplex Phase1: token 75/500: rel_id=4445
22:28:29.417 TTS Simplex Phase1: EOS token at step 79
22:28:29.417 TTS Simplex: chunk 结�,tts_token_buffer 剩余 10 tokens (�留等下一个 chunk)
22:28:29.417 TTS Simplex: generated 78 audio tokens for chunk 7
22:28:29.417 TTS Simplex: chunk 7 first tokens: [2742 4758 1943 59 63 ], last tokens: [5986 4445 2753 566 395 ]
22:28:29.417 TTS Simplex: updated tts_n_past_accumulated=723, total_generated_tokens=635
22:28:29.418 TTS<-LLM: chunk_idx=8, text='宇宙,里�装�勇气�梦想和一点点', n_tokens=10, hidden_size=40960, token_ids=[105339 3837 100420 98641 99164 106860 5373 102294 33108 107342]
22:28:29.418 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:29.418 TTS: before empty check - response.empty=0, response='宇宙,里�装�勇气�梦想和一点点', llm_finish=0
22:28:29.418 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:29.418 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:29.418 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:29.453 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_8/merged_embeddings.txt
22:28:29.453 TTS Simplex: generating audio tokens for chunk 8 (n_tokens=10, tts_n_embd=768)
22:28:29.454 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=8, new_size=11)
22:28:29.454 TTS Simplex: chunk 8 - keeping KV cache, n_past_tts=723
22:28:29.506 TTS Simplex: prefill completed, n_past_tts=734
22:28:29.506 TTS Simplex: sampler created
22:28:29.533 TTS Simplex Phase1: token 1/500: rel_id=876
22:28:29.563 TTS Simplex Phase1: token 2/500: rel_id=1032
22:28:29.586 TTS Simplex Phase1: token 3/500: rel_id=65
22:28:29.610 TTS Simplex Phase1: token 4/500: rel_id=5087
22:28:29.635 TTS Simplex Phase1: token 5/500: rel_id=2259
22:28:29.905 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 15, buffer=25)
22:28:30.229 TTS Simplex Phase1: token 25/500: rel_id=4842
22:28:30.231 LLM->TTS: text='摔过跟头呢?��的是,你', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[103036 38182 99557 64355 101036 11319 99335 100146 3837 56568]
22:28:30.458 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 40, buffer=25)
22:28:30.617 TTS Simplex Phase1: token 50/500: rel_id=1885
22:28:30.878 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 65, buffer=25)
22:28:31.003 T2W线程: wav_3.wav | 1.00s audio | 3102.7ms inference | RTF=3.10 | t=14375ms
22:28:31.040 TTS Simplex Phase1: token 75/500: rel_id=4461
22:28:31.181 TTS Simplex Phase1: EOS token at step 86
22:28:31.181 TTS Simplex: chunk 结�,tts_token_buffer 剩余 20 tokens (�留等下一个 chunk)
22:28:31.181 TTS Simplex: generated 85 audio tokens for chunk 8
22:28:31.181 TTS Simplex: chunk 8 first tokens: [876 1032 65 5087 2259 ], last tokens: [3732 5835 3645 1701 2112 ]
22:28:31.181 TTS Simplex: updated tts_n_past_accumulated=819, total_generated_tokens=720
22:28:31.182 TTS<-LLM: chunk_idx=9, text='�期待。别怕犯错,�还没', n_tokens=10, hidden_size=40960, token_ids=[30709 104177 1773 62922 99756 100238 28726 3837 100165 104789]
22:28:31.182 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:31.182 TTS: before empty check - response.empty=0, response='�期待。别怕犯错,�还没', llm_finish=0
22:28:31.182 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:31.182 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:31.182 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:31.223 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_9/merged_embeddings.txt
22:28:31.223 TTS Simplex: generating audio tokens for chunk 9 (n_tokens=10, tts_n_embd=768)
22:28:31.223 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=9, new_size=11)
22:28:31.223 TTS Simplex: chunk 9 - keeping KV cache, n_past_tts=819
22:28:31.263 TTS Simplex: prefill completed, n_past_tts=830
22:28:31.263 TTS Simplex: sampler created
22:28:31.278 TTS Simplex Phase1: token 1/500: rel_id=6258
22:28:31.292 TTS Simplex Phase1: token 2/500: rel_id=4311
22:28:31.305 TTS Simplex Phase1: token 3/500: rel_id=4942
22:28:31.319 TTS Simplex Phase1: token 4/500: rel_id=5608
22:28:31.334 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 5, buffer=25)
22:28:31.334 TTS Simplex Phase1: token 5/500: rel_id=3266
22:28:31.643 TTS Simplex Phase1: token 25/500: rel_id=566
22:28:31.767 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 30, buffer=25)
22:28:32.292 TTS Simplex Phase1: token 50/500: rel_id=3647
22:28:32.346 LLM->TTS: text='有没有勇气爬起�继续往�走。所以说啊', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[104710 106860 102377 99793 100640 114796 99314 1773 109304 103924]
22:28:32.386 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 55, buffer=25)
22:28:32.659 TTS Simplex Phase1: token 75/500: rel_id=4700
22:28:32.727 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 80, buffer=25)
22:28:32.787 TTS Simplex Phase1: EOS token at step 85
22:28:32.787 TTS Simplex: chunk 结�,tts_token_buffer 剩余 4 tokens (�留等下一个 chunk)
22:28:32.787 TTS Simplex: generated 84 audio tokens for chunk 9
22:28:32.787 TTS Simplex: chunk 9 first tokens: [6258 4311 4942 5608 3266 ], last tokens: [3024 5800 5093 2816 2675 ]
22:28:32.787 TTS Simplex: updated tts_n_past_accumulated=914, total_generated_tokens=804
22:28:32.788 TTS<-LLM: chunk_idx=10, text='摔过跟头呢?��的是,你', n_tokens=10, hidden_size=40960, token_ids=[103036 38182 99557 64355 101036 11319 99335 100146 3837 56568]
22:28:32.788 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:32.788 TTS: before empty check - response.empty=0, response='摔过跟头呢?��的是,你', llm_finish=0
22:28:32.788 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:32.788 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:32.788 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:32.829 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_10/merged_embeddings.txt
22:28:32.829 TTS Simplex: generating audio tokens for chunk 10 (n_tokens=10, tts_n_embd=768)
22:28:32.829 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=10, new_size=11)
22:28:32.829 TTS Simplex: chunk 10 - keeping KV cache, n_past_tts=914
22:28:32.875 TTS Simplex: prefill completed, n_past_tts=925
22:28:32.875 TTS Simplex: sampler created
22:28:32.890 TTS Simplex Phase1: token 1/500: rel_id=524
22:28:32.906 TTS Simplex Phase1: token 2/500: rel_id=2031
22:28:32.922 TTS Simplex Phase1: token 3/500: rel_id=3645
22:28:32.939 TTS Simplex Phase1: token 4/500: rel_id=5838
22:28:32.955 TTS Simplex Phase1: token 5/500: rel_id=5838
22:28:33.387 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 21, buffer=25)
22:28:33.528 TTS Simplex Phase1: token 25/500: rel_id=4851
22:28:33.942 LLM: detected end token, set llm_generation_done=true
22:28:33.942 LLM->TTS: text=',活�本身就是一�奇迹,对�?', n_tokens=9, hidden_size=36864, n_embd=4096, token_ids=[3837 107473 114300 101053 107012 3837 32664 100003 11319]
22:28:34.112 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 46, buffer=25)
22:28:34.182 TTS Simplex Phase1: token 50/500: rel_id=2112
22:28:34.280 T2W线程: wav_4.wav | 1.00s audio | 3276.0ms inference | RTF=3.28 | t=17653ms
22:28:34.351 TTS Simplex Phase1: EOS token at step 61
22:28:34.351 TTS Simplex: chunk 结�,tts_token_buffer 剩余 14 tokens (�留等下一个 chunk)
22:28:34.351 TTS Simplex: generated 60 audio tokens for chunk 10
22:28:34.351 TTS Simplex: chunk 10 first tokens: [524 2031 3645 5838 5838 ], last tokens: [4886 2276 5591 352 559 ]
22:28:34.351 TTS Simplex: updated tts_n_past_accumulated=985, total_generated_tokens=864
22:28:34.352 TTS<-LLM: chunk_idx=11, text='有没有勇气爬起�继续往�走。所以说啊', n_tokens=10, hidden_size=40960, token_ids=[104710 106860 102377 99793 100640 114796 99314 1773 109304 103924]
22:28:34.352 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:34.352 TTS: before empty check - response.empty=0, response='有没有勇气爬起æ�¥ç»§ç»­å¾€å‰�走。所以è¯', llm_finish=0
22:28:34.352 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:34.352 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:34.352 � Decode 结�: n_past=301, 剩余空间=1747, 无需滑窗
22:28:34.352 � 轮次 1 结�,记录边界于 n_past=301
22:28:34.352 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:34.383 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_11/merged_embeddings.txt
22:28:34.383 TTS Simplex: generating audio tokens for chunk 11 (n_tokens=10, tts_n_embd=768)
22:28:34.383 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=11, new_size=11)
22:28:34.383 TTS Simplex: chunk 11 - keeping KV cache, n_past_tts=985
22:28:34.431 TTS Simplex: prefill completed, n_past_tts=996
22:28:34.431 TTS Simplex: sampler created
22:28:34.445 TTS Simplex Phase1: token 1/500: rel_id=113
22:28:34.460 TTS Simplex Phase1: token 2/500: rel_id=5264
22:28:34.475 TTS Simplex Phase1: token 3/500: rel_id=5319
22:28:34.489 TTS Simplex Phase1: token 4/500: rel_id=5322
22:28:34.503 TTS Simplex Phase1: token 5/500: rel_id=876
22:28:34.588 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 11, buffer=25)
22:28:34.690 � 为下一轮准备: eval <|im_end|>\n<|im_start|>user\n, n_past=306
22:28:34.820 TTS Simplex Phase1: token 25/500: rel_id=4978
22:28:34.971 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 36, buffer=25)
22:28:35.171 TTS Simplex Phase1: token 50/500: rel_id=1466
22:28:35.330 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 61, buffer=25)
22:28:35.530 TTS Simplex Phase1: token 75/500: rel_id=494
22:28:35.602 TTS Simplex Phase1: EOS token at step 81
22:28:35.602 TTS Simplex: chunk 结�,tts_token_buffer 剩余 19 tokens (�留等下一个 chunk)
22:28:35.602 TTS Simplex: generated 80 audio tokens for chunk 11
22:28:35.602 TTS Simplex: chunk 11 first tokens: [113 5264 5319 5322 876 ], last tokens: [602 2060 4299 6486 6486 ]
22:28:35.602 TTS Simplex: updated tts_n_past_accumulated=1076, total_generated_tokens=944
22:28:35.612 TTS<-LLM: chunk_idx=12, text=',活�本身就是一�奇迹,对�?', n_tokens=9, hidden_size=36864, token_ids=[3837 107473 114300 101053 107012 3837 32664 100003 11319]
22:28:35.612 TTS: after queue pop - speek_done=0, llm_finish=1, llm_text.empty=0, token_ids.size=9
22:28:35.612 TTS: before empty check - response.empty=0, response=',活�本身就是一�奇迹,对�?', llm_finish=1
22:28:35.612 TTS: DEBUG before has_llm_data - token_ids.size=9, hidden_states.size=36864, n_embd=4096
22:28:35.612 TTS: has_llm_data=1, token_ids=9, hidden_states=36864, n_embd=4096, llm_finish=1
22:28:35.612 TTS: n_tokens_orig=9, n_tokens_filtered=9 (filtered 0 special tokens)
22:28:35.642 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_12/merged_embeddings.txt
22:28:35.642 TTS Simplex: generating audio tokens for chunk 12 (n_tokens=9, tts_n_embd=768)
22:28:35.642 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=12, new_size=10)
22:28:35.642 TTS Simplex: chunk 12 - keeping KV cache, n_past_tts=1076
22:28:35.690 TTS Simplex: prefill completed, n_past_tts=1086
22:28:35.690 TTS Simplex: sampler created
22:28:35.704 TTS Simplex Phase1: token 1/500: rel_id=6486
22:28:35.718 TTS Simplex Phase1: token 2/500: rel_id=4299
22:28:35.732 TTS Simplex Phase1: token 3/500: rel_id=4218
22:28:35.747 TTS Simplex Phase1: token 4/500: rel_id=3975
22:28:35.761 TTS Simplex Phase1: token 5/500: rel_id=4299
22:28:35.775 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 6, buffer=25)
22:28:36.069 TTS Simplex Phase1: token 25/500: rel_id=3647
22:28:36.168 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 31, buffer=25)
22:28:36.481 TTS Simplex Phase1: token 50/500: rel_id=361
22:28:36.589 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 56, buffer=25)
22:28:36.883 T2W线程: wav_5.wav | 1.00s audio | 2601.6ms inference | RTF=2.60 | t=20255ms
22:28:36.923 TTS Simplex Phase1: token 75/500: rel_id=2436
22:28:37.013 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 81, buffer=25)
22:28:37.145 TTS Simplex Phase1: EOS token at step 90
22:28:37.145 TTS Simplex: is_final_text_chunk=true, will enter Phase 2 for text_eos_embed
22:28:37.145 TTS Simplex Phase2: injecting text_eos_embed + audio_bos at n_past=1175
22:28:37.157 TTS Simplex Phase2: text_eos_embed injected, n_past=1176
22:28:37.168 TTS Simplex Phase2: audio_bos injected, n_past=1177, starting final generation
22:28:37.390 TTS Simplex Phase2: EOS at step 14 (final end)
22:28:37.390 TTS Simplex: chunk 结�,tts_token_buffer 剩余 21 tokens (�留等下一个 chunk)
22:28:37.390 TTS Simplex: is_final_text_chunk=true, flush 剩余 21 tokens 从 tts_token_buffer
22:28:37.390 TTS Simplex: generated 102 audio tokens for chunk 12
22:28:37.390 TTS Simplex: chunk 12 first tokens: [6486 4299 4218 3975 4299 ], last tokens: [4384 3897 6486 6486 4299 ]
22:28:37.390 TTS Simplex: updated tts_n_past_accumulated=1191, total_generated_tokens=1046
22:28:37.399 TTS: finished processing all chunks
22:28:37.399 TTS: �工模�轮次结�,下一轮 round_idx=1
22:28:37.399 TTS: sent is_final=true to T2W queue (turn end)
22:28:39.451 T2W线程: wav_6.wav | 1.00s audio | 2567.8ms inference | RTF=2.57 | t=22823ms
22:28:41.704 T2W线程: wav_7.wav | 1.00s audio | 2251.6ms inference | RTF=2.25 | t=25076ms
22:28:43.954 T2W线程: wav_8.wav | 1.00s audio | 2249.3ms inference | RTF=2.25 | t=27326ms
22:28:46.208 T2W线程: wav_9.wav | 1.00s audio | 2254.1ms inference | RTF=2.25 | t=29581ms
22:28:48.471 T2W线程: wav_10.wav | 1.00s audio | 2261.9ms inference | RTF=2.26 | t=31843ms
22:28:50.731 T2W线程: wav_11.wav | 1.00s audio | 2259.2ms inference | RTF=2.26 | t=34103ms
22:28:52.994 T2W线程: wav_12.wav | 1.00s audio | 2262.3ms inference | RTF=2.26 | t=36366ms
22:28:55.241 T2W线程: wav_13.wav | 1.00s audio | 2245.8ms inference | RTF=2.25 | t=38613ms
22:28:57.493 T2W线程: wav_14.wav | 1.00s audio | 2243.6ms inference | RTF=2.24 | t=40865ms
22:28:59.727 T2W线程: wav_15.wav | 1.00s audio | 2233.5ms inference | RTF=2.23 | t=43099ms
22:29:01.986 T2W线程: wav_16.wav | 1.00s audio | 2247.9ms inference | RTF=2.25 | t=45358ms
22:29:04.270 T2W线程: wav_17.wav | 1.00s audio | 2283.5ms inference | RTF=2.28 | t=47642ms
22:29:06.553 T2W线程: wav_18.wav | 1.00s audio | 2282.2ms inference | RTF=2.28 | t=49925ms
22:29:08.804 T2W线程: wav_19.wav | 1.00s audio | 2250.0ms inference | RTF=2.25 | t=52176ms
22:29:11.073 T2W线程: wav_20.wav | 1.00s audio | 2258.2ms inference | RTF=2.26 | t=54445ms
22:29:13.334 T2W线程: wav_21.wav | 1.00s audio | 2260.2ms inference | RTF=2.26 | t=56706ms
22:29:15.586 T2W线程: wav_22.wav | 1.00s audio | 2251.7ms inference | RTF=2.25 | t=58958ms
22:29:17.855 T2W线程: wav_23.wav | 1.00s audio | 2268.6ms inference | RTF=2.27 | t=61227ms
22:29:20.119 T2W线程: wav_24.wav | 1.00s audio | 2263.4ms inference | RTF=2.26 | t=63492ms
22:29:22.375 T2W线程: wav_25.wav | 1.00s audio | 2255.1ms inference | RTF=2.26 | t=65747ms
22:29:24.634 T2W线程: wav_26.wav | 1.00s audio | 2258.4ms inference | RTF=2.26 | t=68006ms
22:29:26.885 T2W线程: wav_27.wav | 1.00s audio | 2250.1ms inference | RTF=2.25 | t=70257ms
22:29:29.146 T2W线程: wav_28.wav | 1.00s audio | 2260.1ms inference | RTF=2.26 | t=72518ms
22:29:31.398 T2W线程: wav_29.wav | 1.00s audio | 2251.4ms inference | RTF=2.25 | t=74770ms
22:29:33.656 T2W线程: wav_30.wav | 1.00s audio | 2257.1ms inference | RTF=2.26 | t=77028ms
22:29:35.899 T2W线程: wav_31.wav | 1.00s audio | 2242.6ms inference | RTF=2.24 | t=79271ms
22:29:38.169 T2W线程: wav_32.wav | 1.00s audio | 2269.3ms inference | RTF=2.27 | t=81541ms
22:29:40.423 T2W线程: wav_33.wav | 1.00s audio | 2252.7ms inference | RTF=2.25 | t=83795ms
22:29:42.682 T2W线程: wav_34.wav | 1.00s audio | 2250.6ms inference | RTF=2.25 | t=86054ms
22:29:44.941 T2W线程: wav_35.wav | 1.00s audio | 2257.8ms inference | RTF=2.26 | t=88313ms
22:29:47.208 T2W线程: wav_36.wav | 1.00s audio | 2267.2ms inference | RTF=2.27 | t=90581ms
22:29:49.462 T2W线程: wav_37.wav | 1.00s audio | 2252.6ms inference | RTF=2.25 | t=92834ms
22:29:51.715 T2W线程: wav_38.wav | 1.00s audio | 2253.0ms inference | RTF=2.25 | t=95088ms
22:29:53.969 T2W线程: wav_39.wav | 1.00s audio | 2252.7ms inference | RTF=2.25 | t=97341ms
22:29:56.231 T2W线程: wav_40.wav | 1.00s audio | 2261.3ms inference | RTF=2.26 | t=99603ms
22:29:58.497 T2W线程: wav_41.wav | 1.12s audio | 2265.0ms inference | RTF=2.02 | t=101869ms
22:29:58.497 T2W线程: 写入结�标记 ./tools/omni/output/round_000/tts_wav/generation_done.flag (last_wav=41)
22:29:58.497 T2W线程: 轮次结��更新输出目录为 ./tools/omni/output/round_001/tts_wav
22:29:58.605 omni_stop_threads: stop signals sent
22:29:58.605 T2W(C++) 线程: �止
tts thread end
t2w thread end
build: 64 (5202b7b) with x86_64-w64-mingw32-gcc-posix (GCC) 13-posix for x86_64-w64-mingw32
llama_model_load_from_file_impl: using device Vulkan0 (AMD Radeon(TM) 890M Graphics) (unknown id) - 30720 MiB free
llama_model_loader: loaded meta data with 27 key-value pairs and 399 tensors from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf\MiniCPM-o-4_5-Q4_K_M.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen3
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Llm
llama_model_loader: - kv 3: general.size_label str = 8.2B
llama_model_loader: - kv 4: qwen3.block_count u32 = 36
llama_model_loader: - kv 5: qwen3.context_length u32 = 40960
llama_model_loader: - kv 6: qwen3.embedding_length u32 = 4096
llama_model_loader: - kv 7: qwen3.feed_forward_length u32 = 12288
llama_model_loader: - kv 8: qwen3.attention.head_count u32 = 32
llama_model_loader: - kv 9: qwen3.attention.head_count_kv u32 = 8
llama_model_loader: - kv 10: qwen3.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 11: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 12: qwen3.attention.key_length u32 = 128
llama_model_loader: - kv 13: qwen3.attention.value_length u32 = 128
llama_model_loader: - kv 14: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 15: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,151748] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,151748] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 18: tokenizer.ggml.merges arr[str,151387] = ["Ä  Ä ", "Ä Ä  Ä Ä ", "i n", "Ä  t",...
llama_model_loader: - kv 19: tokenizer.ggml.bos_token_id u32 = 151644
llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 21: tokenizer.ggml.unknown_token_id u32 = 128244
llama_model_loader: - kv 22: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 25: general.quantization_version u32 = 2
llama_model_loader: - kv 26: general.file_type u32 = 15
llama_model_loader: - type f32: 145 tensors
llama_model_loader: - type q4_K: 217 tensors
llama_model_loader: - type q6_K: 37 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 4.68 GiB (4.90 BPW)
load: printing all EOG tokens:
load: - 151643 ('<|endoftext|>')
load: - 151645 ('<|im_end|>')
load: - 151662 ('<|fim_pad|>')
load: - 151663 ('<|repo_name|>')
load: - 151664 ('<|file_sep|>')
load: special tokens cache size = 106
load: token to piece cache size = 0.9319 MB
print_info: arch = qwen3
print_info: vocab_only = 0
print_info: n_ctx_train = 40960
print_info: n_embd = 4096
print_info: n_layer = 36
print_info: n_head = 32
print_info: n_head_kv = 8
print_info: n_rot = 128
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 4
print_info: n_embd_k_gqa = 1024
print_info: n_embd_v_gqa = 1024
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-06
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 12288
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = -1
print_info: rope type = 2
print_info: rope scaling = linear
print_info: freq_base_train = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 40960
print_info: rope_finetuned = unknown
print_info: model type = 8B
print_info: model params = 8.19 B
print_info: general.name = Llm
print_info: vocab type = BPE
print_info: n_vocab = 151748
print_info: n_merges = 151387
print_info: BOS token = 151644 '<|im_start|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: UNK token = 128244 '<unk>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'ÄŠ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 36 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 37/37 layers to GPU
load_tensors: Vulkan0 model buffer size = 4454.74 MiB
load_tensors: CPU_Mapped model buffer size = 333.43 MiB
.....................................................................................
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 2048
llama_context: n_ctx_per_seq = 2048
llama_context: n_batch = 2048
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = auto
llama_context: kv_unified = false
llama_context: freq_base = 1000000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (2048) < n_ctx_train (40960) -- the full capacity of the model will not be utilized
llama_context: Vulkan_Host output buffer size = 0.58 MiB
llama_kv_cache: Vulkan0 KV buffer size = 288.00 MiB
llama_kv_cache: size = 288.00 MiB ( 2048 cells, 36 layers, 1/1 seqs), K (f16): 144.00 MiB, V (f16): 144.00 MiB
llama_context: Flash Attention was auto, set to enabled
llama_context: Vulkan0 compute buffer size = 304.38 MiB
llama_context: Vulkan_Host compute buffer size = 12.01 MiB
llama_context: graph nodes = 1267
llama_context: graph splits = 2
llama_model_load_from_file_impl: using device Vulkan0 (AMD Radeon(TM) 890M Graphics) (unknown id) - 25673 MiB free
llama_model_loader: loaded meta data with 30 key-value pairs and 193 tensors from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts/MiniCPM-o-4_5-tts-F16.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Tts
llama_model_loader: - kv 3: general.size_label str = 445M
llama_model_loader: - kv 4: llama.block_count u32 = 20
llama_model_loader: - kv 5: llama.context_length u32 = 4096
llama_model_loader: - kv 6: llama.embedding_length u32 = 768
llama_model_loader: - kv 7: llama.feed_forward_length u32 = 3072
llama_model_loader: - kv 8: llama.attention.head_count u32 = 12
llama_model_loader: - kv 9: llama.attention.head_count_kv u32 = 12
llama_model_loader: - kv 10: llama.rope.freq_base f32 = 10000.000000
llama_model_loader: - kv 11: llama.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 12: llama.attention.key_length u32 = 64
llama_model_loader: - kv 13: llama.attention.value_length u32 = 64
llama_model_loader: - kv 14: general.file_type u32 = 1
llama_model_loader: - kv 15: llama.vocab_size u32 = 158626
llama_model_loader: - kv 16: llama.rope.dimension_count u32 = 64
llama_model_loader: - kv 17: general.quantization_version u32 = 2
llama_model_loader: - kv 18: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 19: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 20: tokenizer.ggml.tokens arr[str,158626] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 21: tokenizer.ggml.token_type arr[i32,158626] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 22: tokenizer.ggml.merges arr[str,151387] = ["Ä  Ä ", "Ä Ä  Ä Ä ", "i n", "Ä  t",...
llama_model_loader: - kv 23: tokenizer.ggml.bos_token_id u32 = 151644
llama_model_loader: - kv 24: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 25: tokenizer.ggml.unknown_token_id u32 = 128244
llama_model_loader: - kv 26: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 27: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 28: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 29: tokenizer.ggml.add_space_prefix bool = false
llama_model_loader: - type f32: 50 tensors
llama_model_loader: - type f16: 143 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = F16
print_info: file size = 1.07 GiB (20.70 BPW)
load: printing all EOG tokens:
load: - 151643 ('<|endoftext|>')
load: - 151645 ('<|im_end|>')
load: - 151662 ('<|fim_pad|>')
load: - 151663 ('<|repo_name|>')
load: - 151664 ('<|file_sep|>')
load: special tokens cache size = 106
load: token to piece cache size = 0.9319 MB
print_info: arch = llama
print_info: vocab_only = 0
print_info: n_ctx_train = 4096
print_info: n_embd = 768
print_info: n_layer = 20
print_info: n_head = 12
print_info: n_head_kv = 12
print_info: n_rot = 64
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 64
print_info: n_embd_head_v = 64
print_info: n_gqa = 1
print_info: n_embd_k_gqa = 768
print_info: n_embd_v_gqa = 768
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-06
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 3072
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 0
print_info: rope scaling = linear
print_info: freq_base_train = 10000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 4096
print_info: rope_finetuned = unknown
print_info: model type = ?B
print_info: model params = 444.94 M
print_info: general.name = Tts
print_info: vocab type = BPE
print_info: n_vocab = 158626
print_info: n_merges = 151387
print_info: BOS token = 151644 '<|im_start|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: UNK token = 128244 '<unk>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'ÄŠ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: skipping TTS tensor emb_code.0.weight (size = 20158464 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor emb_text.weight (size = 467140608 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_semantic.linear1.weight (size = 12582912 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_semantic.linear1.bias (size = 3072 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_semantic.linear2.weight (size = 2359296 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_semantic.linear2.bias (size = 3072 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_spk.linear1.weight (size = 6291456 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_spk.linear1.bias (size = 3072 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_spk.linear2.weight (size = 1179648 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_spk.linear2.bias (size = 3072 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor head_code.0.weight (size = 20158464 bytes) -- will be loaded separately
load_tensors: offloading 0 repeating layers to GPU
load_tensors: offloaded 0/21 layers to GPU
load_tensors: CPU_Mapped model buffer size = 592.48 MiB
..............................................................
llama_init_from_model: model default pooling_type is [0], but [-1] was specified
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 2048
llama_context: n_ctx_per_seq = 2048
llama_context: n_batch = 2048
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = auto
llama_context: kv_unified = false
llama_context: freq_base = 10000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (2048) < n_ctx_train (4096) -- the full capacity of the model will not be utilized
llama_context: CPU output buffer size = 0.61 MiB
llama_kv_cache: CPU KV buffer size = 120.00 MiB
llama_kv_cache: size = 120.00 MiB ( 2048 cells, 20 layers, 1/1 seqs), K (f16): 60.00 MiB, V (f16): 60.00 MiB
llama_context: Flash Attention was auto, set to enabled
llama_context: Vulkan0 compute buffer size = 30.75 MiB
llama_context: Vulkan_Host compute buffer size = 7.01 MiB
llama_context: graph nodes = 613
llama_context: graph splits = 216 (with bs=512), 1 (with bs=1)
vision_model_loader: model name:
vision_model_loader: description: image encoder for MiniCPM-V
vision_model_loader: GGUF version: 3
vision_model_loader: alignment: 32
vision_model_loader: n_tensors: 455
vision_model_loader: n_kv: 20
vision_ctx: vision using Vulkan0 backend
load_hparams: model_type: 0
load_hparams: n_embd: 1152
load_hparams: n_head: 16
load_hparams: n_ff: 4304
load_hparams: n_layer: 27
load_hparams: ffn_op: gelu
load_hparams: projection_dim: 0
--- vision hparams ---
load_hparams: image_size: 448
load_hparams: patch_size: 14
load_hparams: minicpmv_version: 100045
load_hparams: proj_scale_factor: 0
load_hparams: n_wa_pattern: 0
load_hparams: model size: 1044.36 MiB
load_hparams: metadata size: 0.16 MiB
load_tensors: ffn up/down are swapped
alloc_compute_meta: Vulkan0 compute buffer size = 100.30 MiB
alloc_compute_meta: CPU compute buffer size = 18.30 MiB
init tts....init t2w....voc_hg2_model: CPU backend using 8 threads
audition_audio_preprocess: Decoded audio - sample_rate=16000, n_samples=32000
audition_get_mel_filters: Retrieved mel filters from model: 80 mel bins x 201 fft bins
audition_audio_preprocess: Using mel filters - n_mel=80, n_fft=201
audition_audio_preprocess: Generated 1 mel spectrogram chunk(s)
audition_audio_preprocess: Mel spectrogram ready - n_len=200, n_mel=80, total_size=16000
build_whisper: Whisper encoder graph built (projector output, pre-pooling)
audition_audio_batch_encode: Audio input data - n_step=200, n_mel=80, total_elements=16000
audition_audio_batch_encode: Before incrementing iter: input_frames=200, n_tokens=100, current_iter=0, current_total=0, new_total=100, max_tokens=1500
audition_audio_batch_encode: KV cache iter incremented to 1 (total_tokens=100, max_tokens=1500)
audition_audio_batch_encode: Final output shape: [4096, 20]
audition_audio_batch_encode: Final output: 20 tokens x 4096 dims
encode_image_with_vision_chunks: step 1 of 1 encoded in 1617.01 ms
encode_image_with_vision_chunks: all 1 chunks encoded in 1635.01 ms (grid: 1x1)
encode_image_with_vision_chunks: image encoded in 1635.01 ms by vision ( 1635.01 ms per chunk, 64 total tokens)
omni_image_embed_make_chunks_with_filename: created 1 vision chunks from C:\Users\zhout\w2\minicpmo_cpp_radeon\fixture_0001.jpg
stream_prefill: prefilled 1 vision chunks (64 tokens each)
audition_audio_preprocess: Decoded audio - sample_rate=16000, n_samples=32000
audition_get_mel_filters: Retrieved mel filters from model: 80 mel bins x 201 fft bins
audition_audio_preprocess: Using mel filters - n_mel=80, n_fft=201
audition_audio_preprocess: Generated 1 mel spectrogram chunk(s)
audition_audio_preprocess: Mel spectrogram ready - n_len=200, n_mel=80, total_size=16000
build_whisper: Whisper encoder graph built (projector output, pre-pooling)
audition_audio_batch_encode: Audio input data - n_step=200, n_mel=80, total_elements=16000
audition_audio_batch_encode: Before incrementing iter: input_frames=200, n_tokens=100, current_iter=1, current_total=100, new_total=200, max_tokens=1500
audition_audio_batch_encode: KV cache iter incremented to 2 (total_tokens=200, max_tokens=1500)
audition_audio_batch_encode: Final output shape: [4096, 20]
audition_audio_batch_encode: Final output: 20 tokens x 4096 dims
<user>
<assistant>[timing] call=0 tokens=28 final=0 token2mel=3244.086ms vocoder=359.413ms total=3603.528ms audio=20160
[timing] call=1 tokens=28 final=0 token2mel=2583.070ms vocoder=578.836ms total=3161.921ms audio=24000
[timing] call=2 tokens=28 final=0 token2mel=2720.120ms vocoder=418.546ms total=3138.675ms audio=24000
[timing] call=3 tokens=28 final=0 token2mel=2702.357ms vocoder=400.267ms total=3102.637ms audio=24000
[timing] call=4 tokens=28 final=0 token2mel=2831.007ms vocoder=444.991ms total=3276.016ms audio=24000
Waiting for audio generation to complete...
[timing] call=5 tokens=28 final=0 token2mel=2186.155ms vocoder=415.404ms total=2601.571ms audio=24000
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_0.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_1.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_2.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_3.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_4.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_5.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_6.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_7.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_8.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_9.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_10.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_11.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_12.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_13.wav does not exist or is empty
TTS: no valid WAV files to merge
[timing] call=6 tokens=28 final=0 token2mel=2191.143ms vocoder=376.579ms total=2567.733ms audio=24000
[timing] call=7 tokens=28 final=0 token2mel=1873.429ms vocoder=378.172ms total=2251.612ms audio=24000
[timing] call=8 tokens=28 final=0 token2mel=1865.689ms vocoder=383.563ms total=2249.263ms audio=24000
[timing] call=9 tokens=28 final=0 token2mel=1883.567ms vocoder=370.476ms total=2254.054ms audio=24000
[timing] call=10 tokens=28 final=0 token2mel=1883.619ms vocoder=378.244ms total=2261.873ms audio=24000
[timing] call=11 tokens=28 final=0 token2mel=1881.421ms vocoder=377.737ms total=2259.169ms audio=24000
[timing] call=12 tokens=28 final=0 token2mel=1882.963ms vocoder=379.295ms total=2262.267ms audio=24000
[timing] call=13 tokens=28 final=0 token2mel=1866.974ms vocoder=378.789ms total=2245.774ms audio=24000
[timing] call=14 tokens=28 final=0 token2mel=1862.498ms vocoder=381.036ms total=2243.544ms audio=24000
[timing] call=15 tokens=28 final=0 token2mel=1862.182ms vocoder=371.245ms total=2233.437ms audio=24000
[timing] call=16 tokens=28 final=0 token2mel=1869.784ms vocoder=378.069ms total=2247.863ms audio=24000
[timing] call=17 tokens=28 final=0 token2mel=1907.270ms vocoder=376.247ms total=2283.528ms audio=24000
[timing] call=18 tokens=28 final=0 token2mel=1891.931ms vocoder=390.200ms total=2282.142ms audio=24000
[timing] call=19 tokens=28 final=0 token2mel=1876.856ms vocoder=373.099ms total=2249.966ms audio=24000
[timing] call=20 tokens=28 final=0 token2mel=1881.694ms vocoder=376.436ms total=2258.141ms audio=24000
[timing] call=21 tokens=28 final=0 token2mel=1877.034ms vocoder=383.119ms total=2260.163ms audio=24000
[timing] call=22 tokens=28 final=0 token2mel=1873.869ms vocoder=377.816ms total=2251.696ms audio=24000
[timing] call=23 tokens=28 final=0 token2mel=1891.518ms vocoder=377.053ms total=2268.581ms audio=24000
[timing] call=24 tokens=28 final=0 token2mel=1886.656ms vocoder=376.669ms total=2263.336ms audio=24000
[timing] call=25 tokens=28 final=0 token2mel=1885.998ms vocoder=369.118ms total=2255.126ms audio=24000
[timing] call=26 tokens=28 final=0 token2mel=1876.853ms vocoder=381.546ms total=2258.409ms audio=24000
[timing] call=27 tokens=28 final=0 token2mel=1872.564ms vocoder=377.462ms total=2250.037ms audio=24000
[timing] call=28 tokens=28 final=0 token2mel=1884.822ms vocoder=375.263ms total=2260.095ms audio=24000
[timing] call=29 tokens=28 final=0 token2mel=1867.917ms vocoder=383.469ms total=2251.396ms audio=24000
[timing] call=30 tokens=28 final=0 token2mel=1878.216ms vocoder=378.829ms total=2257.056ms audio=24000
[timing] call=31 tokens=28 final=0 token2mel=1863.766ms vocoder=378.836ms total=2242.612ms audio=24000
[timing] call=32 tokens=28 final=0 token2mel=1896.603ms vocoder=372.658ms total=2269.271ms audio=24000
[timing] call=33 tokens=28 final=0 token2mel=1866.058ms vocoder=386.570ms total=2252.641ms audio=24000
[timing] call=34 tokens=28 final=0 token2mel=1879.893ms vocoder=370.639ms total=2250.543ms audio=24000
[timing] call=35 tokens=28 final=0 token2mel=1871.253ms vocoder=386.568ms total=2257.831ms audio=24000
[timing] call=36 tokens=28 final=0 token2mel=1890.302ms vocoder=376.857ms total=2267.171ms audio=24000
[timing] call=37 tokens=28 final=0 token2mel=1866.266ms vocoder=386.295ms total=2252.571ms audio=24000
[timing] call=38 tokens=28 final=0 token2mel=1882.129ms vocoder=370.886ms total=2253.025ms audio=24000
[timing] call=39 tokens=28 final=0 token2mel=1870.137ms vocoder=382.574ms total=2252.722ms audio=24000
[timing] call=40 tokens=28 final=0 token2mel=1878.943ms vocoder=382.292ms total=2261.245ms audio=24000
[timing] call=41 tokens=24 final=1 token2mel=1899.809ms vocoder=365.195ms total=2265.014ms audio=26880
Audio generation completed.
llama_perf_context_print: load time = 6915.94 ms
llama_perf_context_print: prompt eval time = 4496.81 ms / 171 tokens ( 26.30 ms per token, 38.03 tokens per second)
llama_perf_context_print: eval time = 11234.37 ms / 130 runs ( 86.42 ms per token, 11.57 tokens per second)
llama_perf_context_print: total time = 108736.83 ms / 301 tokens
llama_perf_context_print: graphs reused = 130
Token2Wav (C++): session released
@@ -0,0 +1,29 @@
{
"command": [
"C:\\Users\\zhout\\w2\\minicpmo_cpp_radeon\\llama-omni-cli.exe",
"-m",
"C:\\Users\\zhout\\w2\\models\\MiniCPM-o-4_5-gguf\\MiniCPM-o-4_5-Q4_K_M.gguf",
"-ngl",
"99",
"-c",
"2048",
"--omni",
"--t2w-device",
"cpu",
"--t2w-wait-seconds",
"900",
"--ref-audio",
"C:\\Users\\zhout\\w2\\minicpmo_cpp_radeon\\default_ref_audio.wav",
"--test",
"C:\\Users\\zhout\\w2\\minicpmo_cpp_radeon\\fixture_",
"2"
],
"cwd": "C:\\Users\\zhout\\w2\\minicpmo_cpp_radeon",
"exit_code": 0,
"wall_s": 113.42734129994642,
"memory_sample_interval_ms": 100,
"memory_samples": 1128,
"peak_sampled_rss_bytes": 15568060416,
"peak_sampled_private_bytes": 15451271168,
"measurement_note": "sampled process values, not guaranteed loading peaks"
}
@@ -0,0 +1,390 @@
build: 64 (5202b7b) with x86_64-w64-mingw32-gcc-posix (GCC) 13-posix for x86_64-w64-mingw32
llama_model_load_from_file_impl: using device Vulkan0 (AMD Radeon(TM) 890M Graphics) (unknown id) - 30720 MiB free
llama_model_loader: loaded meta data with 27 key-value pairs and 399 tensors from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf\MiniCPM-o-4_5-Q4_K_M.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen3
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Llm
llama_model_loader: - kv 3: general.size_label str = 8.2B
llama_model_loader: - kv 4: qwen3.block_count u32 = 36
llama_model_loader: - kv 5: qwen3.context_length u32 = 40960
llama_model_loader: - kv 6: qwen3.embedding_length u32 = 4096
llama_model_loader: - kv 7: qwen3.feed_forward_length u32 = 12288
llama_model_loader: - kv 8: qwen3.attention.head_count u32 = 32
llama_model_loader: - kv 9: qwen3.attention.head_count_kv u32 = 8
llama_model_loader: - kv 10: qwen3.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 11: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 12: qwen3.attention.key_length u32 = 128
llama_model_loader: - kv 13: qwen3.attention.value_length u32 = 128
llama_model_loader: - kv 14: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 15: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,151748] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,151748] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 18: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 19: tokenizer.ggml.bos_token_id u32 = 151644
llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 21: tokenizer.ggml.unknown_token_id u32 = 128244
llama_model_loader: - kv 22: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 24: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 25: general.quantization_version u32 = 2
llama_model_loader: - kv 26: general.file_type u32 = 15
llama_model_loader: - type f32: 145 tensors
llama_model_loader: - type q4_K: 217 tensors
llama_model_loader: - type q6_K: 37 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 4.68 GiB (4.90 BPW)
load: printing all EOG tokens:
load: - 151643 ('<|endoftext|>')
load: - 151645 ('<|im_end|>')
load: - 151662 ('<|fim_pad|>')
load: - 151663 ('<|repo_name|>')
load: - 151664 ('<|file_sep|>')
load: special tokens cache size = 106
load: token to piece cache size = 0.9319 MB
print_info: arch = qwen3
print_info: vocab_only = 0
print_info: n_ctx_train = 40960
print_info: n_embd = 4096
print_info: n_layer = 36
print_info: n_head = 32
print_info: n_head_kv = 8
print_info: n_rot = 128
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 4
print_info: n_embd_k_gqa = 1024
print_info: n_embd_v_gqa = 1024
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-06
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 12288
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = -1
print_info: rope type = 2
print_info: rope scaling = linear
print_info: freq_base_train = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 40960
print_info: rope_finetuned = unknown
print_info: model type = 8B
print_info: model params = 8.19 B
print_info: general.name = Llm
print_info: vocab type = BPE
print_info: n_vocab = 151748
print_info: n_merges = 151387
print_info: BOS token = 151644 '<|im_start|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: UNK token = 128244 '<unk>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 36 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 37/37 layers to GPU
load_tensors: Vulkan0 model buffer size = 4454.74 MiB
load_tensors: CPU_Mapped model buffer size = 333.43 MiB
.....................................................................................
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 2048
llama_context: n_ctx_per_seq = 2048
llama_context: n_batch = 2048
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = auto
llama_context: kv_unified = false
llama_context: freq_base = 1000000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (2048) < n_ctx_train (40960) -- the full capacity of the model will not be utilized
llama_context: Vulkan_Host output buffer size = 0.58 MiB
llama_kv_cache: Vulkan0 KV buffer size = 288.00 MiB
llama_kv_cache: size = 288.00 MiB ( 2048 cells, 36 layers, 1/1 seqs), K (f16): 144.00 MiB, V (f16): 144.00 MiB
llama_context: Flash Attention was auto, set to enabled
llama_context: Vulkan0 compute buffer size = 304.38 MiB
llama_context: Vulkan_Host compute buffer size = 12.01 MiB
llama_context: graph nodes = 1267
llama_context: graph splits = 2
llama_model_load_from_file_impl: using device Vulkan0 (AMD Radeon(TM) 890M Graphics) (unknown id) - 25673 MiB free
llama_model_loader: loaded meta data with 30 key-value pairs and 193 tensors from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts/MiniCPM-o-4_5-tts-F16.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Tts
llama_model_loader: - kv 3: general.size_label str = 445M
llama_model_loader: - kv 4: llama.block_count u32 = 20
llama_model_loader: - kv 5: llama.context_length u32 = 4096
llama_model_loader: - kv 6: llama.embedding_length u32 = 768
llama_model_loader: - kv 7: llama.feed_forward_length u32 = 3072
llama_model_loader: - kv 8: llama.attention.head_count u32 = 12
llama_model_loader: - kv 9: llama.attention.head_count_kv u32 = 12
llama_model_loader: - kv 10: llama.rope.freq_base f32 = 10000.000000
llama_model_loader: - kv 11: llama.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 12: llama.attention.key_length u32 = 64
llama_model_loader: - kv 13: llama.attention.value_length u32 = 64
llama_model_loader: - kv 14: general.file_type u32 = 1
llama_model_loader: - kv 15: llama.vocab_size u32 = 158626
llama_model_loader: - kv 16: llama.rope.dimension_count u32 = 64
llama_model_loader: - kv 17: general.quantization_version u32 = 2
llama_model_loader: - kv 18: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 19: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 20: tokenizer.ggml.tokens arr[str,158626] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 21: tokenizer.ggml.token_type arr[i32,158626] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 22: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 23: tokenizer.ggml.bos_token_id u32 = 151644
llama_model_loader: - kv 24: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 25: tokenizer.ggml.unknown_token_id u32 = 128244
llama_model_loader: - kv 26: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 27: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 28: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 29: tokenizer.ggml.add_space_prefix bool = false
llama_model_loader: - type f32: 50 tensors
llama_model_loader: - type f16: 143 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = F16
print_info: file size = 1.07 GiB (20.70 BPW)
load: printing all EOG tokens:
load: - 151643 ('<|endoftext|>')
load: - 151645 ('<|im_end|>')
load: - 151662 ('<|fim_pad|>')
load: - 151663 ('<|repo_name|>')
load: - 151664 ('<|file_sep|>')
load: special tokens cache size = 106
load: token to piece cache size = 0.9319 MB
print_info: arch = llama
print_info: vocab_only = 0
print_info: n_ctx_train = 4096
print_info: n_embd = 768
print_info: n_layer = 20
print_info: n_head = 12
print_info: n_head_kv = 12
print_info: n_rot = 64
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 64
print_info: n_embd_head_v = 64
print_info: n_gqa = 1
print_info: n_embd_k_gqa = 768
print_info: n_embd_v_gqa = 768
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-06
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 3072
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 0
print_info: rope scaling = linear
print_info: freq_base_train = 10000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 4096
print_info: rope_finetuned = unknown
print_info: model type = ?B
print_info: model params = 444.94 M
print_info: general.name = Tts
print_info: vocab type = BPE
print_info: n_vocab = 158626
print_info: n_merges = 151387
print_info: BOS token = 151644 '<|im_start|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: UNK token = 128244 '<unk>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: skipping TTS tensor emb_code.0.weight (size = 20158464 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor emb_text.weight (size = 467140608 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_semantic.linear1.weight (size = 12582912 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_semantic.linear1.bias (size = 3072 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_semantic.linear2.weight (size = 2359296 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_semantic.linear2.bias (size = 3072 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_spk.linear1.weight (size = 6291456 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_spk.linear1.bias (size = 3072 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_spk.linear2.weight (size = 1179648 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor projector_spk.linear2.bias (size = 3072 bytes) -- will be loaded separately
load_tensors: skipping TTS tensor head_code.0.weight (size = 20158464 bytes) -- will be loaded separately
load_tensors: offloading 0 repeating layers to GPU
load_tensors: offloaded 0/21 layers to GPU
load_tensors: CPU_Mapped model buffer size = 592.48 MiB
..............................................................
llama_init_from_model: model default pooling_type is [0], but [-1] was specified
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 2048
llama_context: n_ctx_per_seq = 2048
llama_context: n_batch = 2048
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = auto
llama_context: kv_unified = false
llama_context: freq_base = 10000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (2048) < n_ctx_train (4096) -- the full capacity of the model will not be utilized
llama_context: CPU output buffer size = 0.61 MiB
llama_kv_cache: CPU KV buffer size = 120.00 MiB
llama_kv_cache: size = 120.00 MiB ( 2048 cells, 20 layers, 1/1 seqs), K (f16): 60.00 MiB, V (f16): 60.00 MiB
llama_context: Flash Attention was auto, set to enabled
llama_context: Vulkan0 compute buffer size = 30.75 MiB
llama_context: Vulkan_Host compute buffer size = 7.01 MiB
llama_context: graph nodes = 613
llama_context: graph splits = 216 (with bs=512), 1 (with bs=1)
vision_model_loader: model name:
vision_model_loader: description: image encoder for MiniCPM-V
vision_model_loader: GGUF version: 3
vision_model_loader: alignment: 32
vision_model_loader: n_tensors: 455
vision_model_loader: n_kv: 20
vision_ctx: vision using Vulkan0 backend
load_hparams: model_type: 0
load_hparams: n_embd: 1152
load_hparams: n_head: 16
load_hparams: n_ff: 4304
load_hparams: n_layer: 27
load_hparams: ffn_op: gelu
load_hparams: projection_dim: 0
--- vision hparams ---
load_hparams: image_size: 448
load_hparams: patch_size: 14
load_hparams: minicpmv_version: 100045
load_hparams: proj_scale_factor: 0
load_hparams: n_wa_pattern: 0
load_hparams: model size: 1044.36 MiB
load_hparams: metadata size: 0.16 MiB
load_tensors: ffn up/down are swapped
alloc_compute_meta: Vulkan0 compute buffer size = 100.30 MiB
alloc_compute_meta: CPU compute buffer size = 18.30 MiB
init tts....init t2w....voc_hg2_model: CPU backend using 8 threads
audition_audio_preprocess: Decoded audio - sample_rate=16000, n_samples=32000
audition_get_mel_filters: Retrieved mel filters from model: 80 mel bins x 201 fft bins
audition_audio_preprocess: Using mel filters - n_mel=80, n_fft=201
audition_audio_preprocess: Generated 1 mel spectrogram chunk(s)
audition_audio_preprocess: Mel spectrogram ready - n_len=200, n_mel=80, total_size=16000
build_whisper: Whisper encoder graph built (projector output, pre-pooling)
audition_audio_batch_encode: Audio input data - n_step=200, n_mel=80, total_elements=16000
audition_audio_batch_encode: Before incrementing iter: input_frames=200, n_tokens=100, current_iter=0, current_total=0, new_total=100, max_tokens=1500
audition_audio_batch_encode: KV cache iter incremented to 1 (total_tokens=100, max_tokens=1500)
audition_audio_batch_encode: Final output shape: [4096, 20]
audition_audio_batch_encode: Final output: 20 tokens x 4096 dims
encode_image_with_vision_chunks: step 1 of 1 encoded in 1617.01 ms
encode_image_with_vision_chunks: all 1 chunks encoded in 1635.01 ms (grid: 1x1)
encode_image_with_vision_chunks: image encoded in 1635.01 ms by vision ( 1635.01 ms per chunk, 64 total tokens)
omni_image_embed_make_chunks_with_filename: created 1 vision chunks from C:\Users\zhout\w2\minicpmo_cpp_radeon\fixture_0001.jpg
stream_prefill: prefilled 1 vision chunks (64 tokens each)
audition_audio_preprocess: Decoded audio - sample_rate=16000, n_samples=32000
audition_get_mel_filters: Retrieved mel filters from model: 80 mel bins x 201 fft bins
audition_audio_preprocess: Using mel filters - n_mel=80, n_fft=201
audition_audio_preprocess: Generated 1 mel spectrogram chunk(s)
audition_audio_preprocess: Mel spectrogram ready - n_len=200, n_mel=80, total_size=16000
build_whisper: Whisper encoder graph built (projector output, pre-pooling)
audition_audio_batch_encode: Audio input data - n_step=200, n_mel=80, total_elements=16000
audition_audio_batch_encode: Before incrementing iter: input_frames=200, n_tokens=100, current_iter=1, current_total=100, new_total=200, max_tokens=1500
audition_audio_batch_encode: KV cache iter incremented to 2 (total_tokens=200, max_tokens=1500)
audition_audio_batch_encode: Final output shape: [4096, 20]
audition_audio_batch_encode: Final output: 20 tokens x 4096 dims
<user>
<assistant>[timing] call=0 tokens=28 final=0 token2mel=3244.086ms vocoder=359.413ms total=3603.528ms audio=20160
[timing] call=1 tokens=28 final=0 token2mel=2583.070ms vocoder=578.836ms total=3161.921ms audio=24000
[timing] call=2 tokens=28 final=0 token2mel=2720.120ms vocoder=418.546ms total=3138.675ms audio=24000
[timing] call=3 tokens=28 final=0 token2mel=2702.357ms vocoder=400.267ms total=3102.637ms audio=24000
[timing] call=4 tokens=28 final=0 token2mel=2831.007ms vocoder=444.991ms total=3276.016ms audio=24000
Waiting for audio generation to complete...
[timing] call=5 tokens=28 final=0 token2mel=2186.155ms vocoder=415.404ms total=2601.571ms audio=24000
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_0.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_1.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_2.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_3.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_4.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_5.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_6.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_7.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_8.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_9.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_10.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_11.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_12.wav does not exist or is empty
TTS: chunk file ./tools/omni/output/round_000/tts_wav/tts_output_chunk_13.wav does not exist or is empty
TTS: no valid WAV files to merge
[timing] call=6 tokens=28 final=0 token2mel=2191.143ms vocoder=376.579ms total=2567.733ms audio=24000
[timing] call=7 tokens=28 final=0 token2mel=1873.429ms vocoder=378.172ms total=2251.612ms audio=24000
[timing] call=8 tokens=28 final=0 token2mel=1865.689ms vocoder=383.563ms total=2249.263ms audio=24000
[timing] call=9 tokens=28 final=0 token2mel=1883.567ms vocoder=370.476ms total=2254.054ms audio=24000
[timing] call=10 tokens=28 final=0 token2mel=1883.619ms vocoder=378.244ms total=2261.873ms audio=24000
[timing] call=11 tokens=28 final=0 token2mel=1881.421ms vocoder=377.737ms total=2259.169ms audio=24000
[timing] call=12 tokens=28 final=0 token2mel=1882.963ms vocoder=379.295ms total=2262.267ms audio=24000
[timing] call=13 tokens=28 final=0 token2mel=1866.974ms vocoder=378.789ms total=2245.774ms audio=24000
[timing] call=14 tokens=28 final=0 token2mel=1862.498ms vocoder=381.036ms total=2243.544ms audio=24000
[timing] call=15 tokens=28 final=0 token2mel=1862.182ms vocoder=371.245ms total=2233.437ms audio=24000
[timing] call=16 tokens=28 final=0 token2mel=1869.784ms vocoder=378.069ms total=2247.863ms audio=24000
[timing] call=17 tokens=28 final=0 token2mel=1907.270ms vocoder=376.247ms total=2283.528ms audio=24000
[timing] call=18 tokens=28 final=0 token2mel=1891.931ms vocoder=390.200ms total=2282.142ms audio=24000
[timing] call=19 tokens=28 final=0 token2mel=1876.856ms vocoder=373.099ms total=2249.966ms audio=24000
[timing] call=20 tokens=28 final=0 token2mel=1881.694ms vocoder=376.436ms total=2258.141ms audio=24000
[timing] call=21 tokens=28 final=0 token2mel=1877.034ms vocoder=383.119ms total=2260.163ms audio=24000
[timing] call=22 tokens=28 final=0 token2mel=1873.869ms vocoder=377.816ms total=2251.696ms audio=24000
[timing] call=23 tokens=28 final=0 token2mel=1891.518ms vocoder=377.053ms total=2268.581ms audio=24000
[timing] call=24 tokens=28 final=0 token2mel=1886.656ms vocoder=376.669ms total=2263.336ms audio=24000
[timing] call=25 tokens=28 final=0 token2mel=1885.998ms vocoder=369.118ms total=2255.126ms audio=24000
[timing] call=26 tokens=28 final=0 token2mel=1876.853ms vocoder=381.546ms total=2258.409ms audio=24000
[timing] call=27 tokens=28 final=0 token2mel=1872.564ms vocoder=377.462ms total=2250.037ms audio=24000
[timing] call=28 tokens=28 final=0 token2mel=1884.822ms vocoder=375.263ms total=2260.095ms audio=24000
[timing] call=29 tokens=28 final=0 token2mel=1867.917ms vocoder=383.469ms total=2251.396ms audio=24000
[timing] call=30 tokens=28 final=0 token2mel=1878.216ms vocoder=378.829ms total=2257.056ms audio=24000
[timing] call=31 tokens=28 final=0 token2mel=1863.766ms vocoder=378.836ms total=2242.612ms audio=24000
[timing] call=32 tokens=28 final=0 token2mel=1896.603ms vocoder=372.658ms total=2269.271ms audio=24000
[timing] call=33 tokens=28 final=0 token2mel=1866.058ms vocoder=386.570ms total=2252.641ms audio=24000
[timing] call=34 tokens=28 final=0 token2mel=1879.893ms vocoder=370.639ms total=2250.543ms audio=24000
[timing] call=35 tokens=28 final=0 token2mel=1871.253ms vocoder=386.568ms total=2257.831ms audio=24000
[timing] call=36 tokens=28 final=0 token2mel=1890.302ms vocoder=376.857ms total=2267.171ms audio=24000
[timing] call=37 tokens=28 final=0 token2mel=1866.266ms vocoder=386.295ms total=2252.571ms audio=24000
[timing] call=38 tokens=28 final=0 token2mel=1882.129ms vocoder=370.886ms total=2253.025ms audio=24000
[timing] call=39 tokens=28 final=0 token2mel=1870.137ms vocoder=382.574ms total=2252.722ms audio=24000
[timing] call=40 tokens=28 final=0 token2mel=1878.943ms vocoder=382.292ms total=2261.245ms audio=24000
[timing] call=41 tokens=24 final=1 token2mel=1899.809ms vocoder=365.195ms total=2265.014ms audio=26880
Audio generation completed.
llama_perf_context_print: load time = 6915.94 ms
llama_perf_context_print: prompt eval time = 4496.81 ms / 171 tokens ( 26.30 ms per token, 38.03 tokens per second)
llama_perf_context_print: eval time = 11234.37 ms / 130 runs ( 86.42 ms per token, 11.57 tokens per second)
llama_perf_context_print: total time = 108736.83 ms / 301 tokens
llama_perf_context_print: graphs reused = 130
Token2Wav (C++): session released
@@ -0,0 +1,528 @@
=== Model Paths ===
Base dir: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf
LLM: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf\MiniCPM-o-4_5-Q4_K_M.gguf [OK]
Vision: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/vision/MiniCPM-o-4_5-vision-F16.gguf [OK]
Audio: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/audio/MiniCPM-o-4_5-audio-F16.gguf [OK]
TTS: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts/MiniCPM-o-4_5-tts-F16.gguf [OK]
Projector: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts/MiniCPM-o-4_5-projector-F16.gguf [OK]
===================
=== Initializing Omni Context ===
Media type: 2 (omni: audio+vision)
TTS enabled: yes
Context size: 2048
GPU layers: 99
Token2Wav device: cpu
Vision backend: metal
TTS bin dir: C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts
Ref audio: C:\Users\zhout\w2\minicpmo_cpp_radeon\default_ref_audio.wav
22:28:06.598 === omni_init start
22:28:06.598 media_type = 2, duplex_mode = 0, base_output_dir = ./tools/omni/output
22:28:06.598 === omni_init: loading new LLM model
22:28:09.715 === omni_init: loading TTS model
22:28:09.715 TTS model: loading with n_gpu_layers=0
22:28:10.056 TTS sampler: temp=0.80, top_p=0.85, top_k=25, rep_penalty=1.05
22:28:10.056 TTS: loading weights from GGUF (emb_code, emb_text, projector_semantic, head_code)...
22:28:10.564 TTS: head_code shape: dim0=6562, dim1=768, will transpose to [6562, 768]
22:28:10.573 TTS: head_code loaded, verifying first few values:
22:28:10.573 head_code_weight[0] = 0.01361084 (expect ~0.01385498)
22:28:10.573 head_code_weight[1] = -0.01660156 (expect ~-0.01647949)
22:28:10.573 head_code_weight[768] = 0.04101562 (this is weight[1, 0], expect ~0.04150391)
22:28:10.668 TTS: weights loaded successfully
22:28:10.668 Projector: loading from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/tts/MiniCPM-o-4_5-projector-F16.gguf
22:28:10.677 Projector: loaded successfully
22:28:10.677 === omni_init: loading APM model
22:28:10.953 APM: init from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/audio/MiniCPM-o-4_5-audio-F16.gguf
22:28:11.918 Token2Wav: found models in C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/token2wav-gguf
22:28:11.919 Token2Wav: all model files found, initializing session...
22:28:11.919 Token2Wav: non-CUDA backend, vocoder using CPU for better performance
22:28:11.919 Token2Wav: using prompt_cache from C:\Users\zhout\w2\models\MiniCPM-o-4_5-gguf/token2wav-gguf/prompt_cache.gguf
22:28:12.286 Token2Wav: initialized successfully
22:28:12.286 Python T2W: script_dir=./tools/omni/pyt2w, model_dir=./tools/omni/pyt2w/token2wav
22:28:12.286 Token2Wav: 使用 C++ 实现
22:28:12.286 === omni_init success: ctx_llama = 00000220286afaa0
=== Running test case ===
Audio prefix: C:\Users\zhout\w2\minicpmo_cpp_radeon\fixture_
Count: 2
22:28:12.286 stream_prefill: n_past = 0
voice_clone_prompt = <|im_start|>system
模仿音频样本的音色并生�新的内容。
<|audio_start|>
assistant_prompt = <|audio_end|>你的任务是用这�声音模��当一个助手。请认真�高质�地回�用户的问题。请用高自然度的方�和用户�天。<|im_end|>
<|im_start|>user
22:28:12.286 system prompt ref_audio: C:\Users\zhout\w2\minicpmo_cpp_radeon\fixture_0000.wav
22:28:13.326 system prompt ref_audio embedding: n_pos=20
22:28:13.997 🔒 n_keep 设置为 72 (system prompt tokens),这部分永远�会被滑动窗�删除
22:28:13.997 stream_prefill(index=0): system prompt �始化完�,ref_audio 已在其中 prefill
22:28:13.997 [SW] system_prompt registered: preserve_length=72 (will be protected from sliding)
22:28:13.997 n_past = 72
22:28:13.997
c++ finish stream_prefill(index=0). n_past=72, n_keep=72, n_ctx=2048
prefill 0 (audio) : 1.71101 s
22:28:16.166 stream_prefill(index=1): processing user audio: C:\Users\zhout\w2\minicpmo_cpp_radeon\fixture_0001.wav
22:28:16.335 stream_prefill(index=1): user audio embedding: n_pos=20
22:28:16.627
c++ finish stream_prefill(index=1). n_past=161, n_keep=72, n_ctx=2048
prefill 1 (audio+vision) : 2.62999 s
22:28:16.627 � stream_decode 开始: n_past=161, n_keep=72, n_ctx=2048, duplex_mode=0
22:28:16.627 stream_decode: create tts thread (simplex mode)
22:28:16.627 stream_decode: create t2w thread
22:28:16.627 wait prefill done
22:28:16.628 � [�工TTS] 添加 assistant prompt: "<|im_end|>
<|im_start|>assistant
<think>
</think>
<|tts_bos|>", n_past=161
22:28:16.628 T2W thread (C++) started
22:28:16.631 TTS: 创建�工模�输出目录: ./tools/omni/output/round_000
22:28:16.632 TTS thread started
22:28:16.783 � [�工TTS] assistant prompt 完�, n_past=171
22:28:16.784 LLM decode: max_tgt_len = 2048, n_predict = -1, n_ctx = 2048
22:28:17.359 LLM->TTS: text='你知��,有时候啊,我也会想啊', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[107733 101037 3837 104854 103924 3837 35946 103977 99172 103924]
22:28:17.359 TTS<-LLM: chunk_idx=0, text='你知��,有时候啊,我也会想啊', n_tokens=10, hidden_size=40960, token_ids=[107733 101037 3837 104854 103924 3837 35946 103977 99172 103924]
22:28:17.359 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:17.359 TTS: before empty check - response.empty=0, response='你知��,有时候啊,我也会想啊', llm_finish=0
22:28:17.359 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:17.359 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:17.360 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:17.402 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_0/merged_embeddings.txt
22:28:17.402 TTS Simplex: generating audio tokens for chunk 0 (n_tokens=10, tts_n_embd=768)
22:28:17.402 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=0, new_size=11)
22:28:17.402 TTS Simplex: first chunk - cleared KV cache
22:28:17.402 TTS Simplex: first chunk - cleared tts_all_generated_tokens and tts_token_buffer
22:28:17.479 TTS Simplex: prefill completed, n_past_tts=11
22:28:17.479 TTS Simplex: sampler created
22:28:17.479 TTS simplex: is_audio_bos=true (first audio token)
22:28:17.524 TTS Simplex Phase1: token 1/500: rel_id=1571
22:28:17.545 TTS Simplex Phase1: token 2/500: rel_id=6486
22:28:17.564 TTS Simplex Phase1: token 3/500: rel_id=4299
22:28:17.583 TTS Simplex Phase1: token 4/500: rel_id=4299
22:28:17.603 TTS Simplex Phase1: token 5/500: rel_id=4299
22:28:17.992 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 25, buffer=25)
22:28:17.992 TTS Simplex Phase1: token 25/500: rel_id=4299
22:28:17.992 T2W线程(C++): 轮次切� (-1 -> 0),更新输出目录
22:28:17.992 T2W线程(C++): 新输出目录 ./tools/omni/output/round_000/tts_wav
22:28:18.074 LLM->TTS: text=',生活真的挺有��的。�天早上醒�,', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[3837 99424 100672 101174 113062 1773 101922 105083 109877 3837]
22:28:18.524 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 50, buffer=25)
22:28:18.524 TTS Simplex Phase1: token 50/500: rel_id=1703
22:28:18.595 TTS Simplex Phase1: EOS token at step 54
22:28:18.595 TTS Simplex: chunk 结�,tts_token_buffer 剩余 3 tokens (�留等下一个 chunk)
22:28:18.595 TTS Simplex: generated 53 audio tokens for chunk 0
22:28:18.595 TTS Simplex: chunk 0 first tokens: [1571 6486 4299 4299 4299 ], last tokens: [731 1703 1951 2112 719 ]
22:28:18.595 TTS Simplex: updated tts_n_past_accumulated=64, total_generated_tokens=53
22:28:18.596 TTS<-LLM: chunk_idx=1, text=',生活真的挺有��的。�天早上醒�,', n_tokens=10, hidden_size=40960, token_ids=[3837 99424 100672 101174 113062 1773 101922 105083 109877 3837]
22:28:18.596 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:18.596 TTS: before empty check - response.empty=0, response=',生活真的挺有æ„�æ€�的。æ¯�天早上醒æ�', llm_finish=0
22:28:18.596 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:18.596 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:18.596 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:18.630 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_1/merged_embeddings.txt
22:28:18.630 TTS Simplex: generating audio tokens for chunk 1 (n_tokens=10, tts_n_embd=768)
22:28:18.630 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=1, new_size=11)
22:28:18.630 TTS Simplex: chunk 1 - keeping KV cache, n_past_tts=64
22:28:18.665 TTS Simplex: prefill completed, n_past_tts=75
22:28:18.665 TTS Simplex: sampler created
22:28:18.696 TTS Simplex Phase1: token 1/500: rel_id=728
22:28:18.719 TTS Simplex Phase1: token 2/500: rel_id=4613
22:28:18.740 TTS Simplex Phase1: token 3/500: rel_id=4803
22:28:18.763 TTS Simplex Phase1: token 4/500: rel_id=4551
22:28:18.781 TTS Simplex Phase1: token 5/500: rel_id=4466
22:28:18.849 LLM->TTS: text='太阳照在脸上,就觉得这一天充满了�能。', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[101281 99331 18493 104488 3837 115119 112480 106890 87267 1773]
22:28:19.156 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 22, buffer=25)
22:28:19.226 TTS Simplex Phase1: token 25/500: rel_id=4299
22:28:19.617 LLM->TTS: text='�管�一天�生啥事,��新的一天�了', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[101260 115982 99726 101417 29826 3837 100671 118580 35727 101161]
22:28:19.667 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 47, buffer=25)
22:28:19.700 TTS Simplex Phase1: token 50/500: rel_id=219
22:28:19.953 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 72, buffer=25)
22:28:19.988 TTS Simplex Phase1: token 75/500: rel_id=4299
22:28:20.178 TTS Simplex Phase1: EOS token at step 92
22:28:20.178 TTS Simplex: chunk 结�,tts_token_buffer 剩余 19 tokens (�留等下一个 chunk)
22:28:20.178 TTS Simplex: generated 91 audio tokens for chunk 1
22:28:20.178 TTS Simplex: chunk 1 first tokens: [728 4613 4803 4551 4466 ], last tokens: [870 2726 4489 5205 6387 ]
22:28:20.178 TTS Simplex: updated tts_n_past_accumulated=166, total_generated_tokens=144
22:28:20.179 TTS<-LLM: chunk_idx=2, text='太阳照在脸上,就觉得这一天充满了�能。', n_tokens=10, hidden_size=40960, token_ids=[101281 99331 18493 104488 3837 115119 112480 106890 87267 1773]
22:28:20.179 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:20.179 TTS: before empty check - response.empty=0, response='太阳照在脸上,就觉得这一天充满了å�', llm_finish=0
22:28:20.179 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:20.179 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:20.179 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:20.213 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_2/merged_embeddings.txt
22:28:20.213 TTS Simplex: generating audio tokens for chunk 2 (n_tokens=10, tts_n_embd=768)
22:28:20.213 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=2, new_size=11)
22:28:20.213 TTS Simplex: chunk 2 - keeping KV cache, n_past_tts=166
22:28:20.247 TTS Simplex: prefill completed, n_past_tts=177
22:28:20.247 TTS Simplex: sampler created
22:28:20.268 TTS Simplex Phase1: token 1/500: rel_id=2502
22:28:20.293 TTS Simplex Phase1: token 2/500: rel_id=974
22:28:20.325 TTS Simplex Phase1: token 3/500: rel_id=1163
22:28:20.350 TTS Simplex Phase1: token 4/500: rel_id=5970
22:28:20.378 TTS Simplex Phase1: token 5/500: rel_id=957
22:28:20.405 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 6, buffer=25)
22:28:20.938 TTS Simplex Phase1: token 25/500: rel_id=2112
22:28:21.011 LLM->TTS: text=',就有机会�新开始。你有没有觉得,', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[3837 104435 101135 70361 55286 1773 56568 104710 99801 3837]
22:28:21.056 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 31, buffer=25)
22:28:21.326 TTS Simplex Phase1: token 50/500: rel_id=5914
22:28:21.408 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 56, buffer=25)
22:28:21.597 🎉 首�时间 (First Audio Response): 4969ms
22:28:21.597 T2W线程: wav_0.wav | 0.84s audio | 3603.6ms inference | RTF=4.29 | t=4969ms
22:28:21.674 TTS Simplex Phase1: token 75/500: rel_id=4593
22:28:21.745 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 81, buffer=25)
22:28:21.841 TTS Simplex Phase1: EOS token at step 90
22:28:21.841 TTS Simplex: chunk 结�,tts_token_buffer 剩余 8 tokens (�留等下一个 chunk)
22:28:21.841 TTS Simplex: generated 89 audio tokens for chunk 2
22:28:21.841 TTS Simplex: chunk 2 first tokens: [2502 974 1163 5970 957 ], last tokens: [4382 5937 2130 6051 1539 ]
22:28:21.841 TTS Simplex: updated tts_n_past_accumulated=266, total_generated_tokens=233
22:28:21.843 TTS<-LLM: chunk_idx=3, text='�管�一天�生啥事,��新的一天�了', n_tokens=10, hidden_size=40960, token_ids=[101260 115982 99726 101417 29826 3837 100671 118580 35727 101161]
22:28:21.843 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:21.843 TTS: before empty check - response.empty=0, response='ä¸�管å‰�一天å�‘生啥事,å�ªè¦�新的一天æ�', llm_finish=0
22:28:21.843 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:21.843 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:21.843 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:21.877 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_3/merged_embeddings.txt
22:28:21.877 TTS Simplex: generating audio tokens for chunk 3 (n_tokens=10, tts_n_embd=768)
22:28:21.877 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=3, new_size=11)
22:28:21.877 TTS Simplex: chunk 3 - keeping KV cache, n_past_tts=266
22:28:21.913 TTS Simplex: prefill completed, n_past_tts=277
22:28:21.913 TTS Simplex: sampler created
22:28:21.936 TTS Simplex Phase1: token 1/500: rel_id=2676
22:28:21.959 TTS Simplex Phase1: token 2/500: rel_id=4981
22:28:21.981 TTS Simplex Phase1: token 3/500: rel_id=5065
22:28:22.001 TTS Simplex Phase1: token 4/500: rel_id=5775
22:28:22.026 TTS Simplex Phase1: token 5/500: rel_id=6501
22:28:22.300 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 17, buffer=25)
22:28:22.482 TTS Simplex Phase1: token 25/500: rel_id=6486
22:28:22.597 LLM->TTS: text='就算�到�难的事,��咬咬牙', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[104501 104011 87256 99349 104140 3837 100671 105118 105118 100446]
22:28:22.738 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 42, buffer=25)
22:28:22.838 TTS Simplex Phase1: token 50/500: rel_id=2274
22:28:23.048 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 67, buffer=25)
22:28:23.146 TTS Simplex Phase1: token 75/500: rel_id=1648
22:28:23.335 TTS Simplex Phase1: EOS token at step 91
22:28:23.335 TTS Simplex: chunk 结�,tts_token_buffer 剩余 23 tokens (�留等下一个 chunk)
22:28:23.336 TTS Simplex: generated 90 audio tokens for chunk 3
22:28:23.336 TTS Simplex: chunk 3 first tokens: [2676 4981 5065 5775 6501 ], last tokens: [5323 1132 476 974 2756 ]
22:28:23.336 TTS Simplex: updated tts_n_past_accumulated=367, total_generated_tokens=323
22:28:23.336 TTS<-LLM: chunk_idx=4, text=',就有机会�新开始。你有没有觉得,', n_tokens=10, hidden_size=40960, token_ids=[3837 104435 101135 70361 55286 1773 56568 104710 99801 3837]
22:28:23.336 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:23.337 TTS: before empty check - response.empty=0, response=',就有机会é‡�新开始。你有没有觉得ï¼', llm_finish=0
22:28:23.337 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:23.337 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:23.337 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:23.368 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_4/merged_embeddings.txt
22:28:23.368 TTS Simplex: generating audio tokens for chunk 4 (n_tokens=10, tts_n_embd=768)
22:28:23.368 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=4, new_size=11)
22:28:23.368 TTS Simplex: chunk 4 - keeping KV cache, n_past_tts=367
22:28:23.397 TTS Simplex: prefill completed, n_past_tts=378
22:28:23.397 TTS Simplex: sampler created
22:28:23.409 TTS Simplex Phase1: token 1/500: rel_id=4441
22:28:23.422 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 2, buffer=25)
22:28:23.422 TTS Simplex Phase1: token 2/500: rel_id=6455
22:28:23.436 TTS Simplex Phase1: token 3/500: rel_id=2229
22:28:23.450 TTS Simplex Phase1: token 4/500: rel_id=4803
22:28:23.465 TTS Simplex Phase1: token 5/500: rel_id=6261
22:28:23.755 TTS Simplex Phase1: token 25/500: rel_id=1944
22:28:23.783 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 27, buffer=25)
22:28:24.439 TTS Simplex Phase1: token 50/500: rel_id=5325
22:28:24.513 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 52, buffer=25)
22:28:24.695 LLM->TTS: text='挺过去,回头看的时候,�而觉得挺酷', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[101174 100688 3837 115204 103920 3837 104503 99801 101174 102382]
22:28:24.760 T2W线程: wav_1.wav | 1.00s audio | 3161.9ms inference | RTF=3.16 | t=8132ms
22:28:24.933 TTS Simplex Phase1: token 75/500: rel_id=6486
22:28:24.957 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 77, buffer=25)
22:28:25.045 TTS Simplex Phase1: EOS token at step 85
22:28:25.045 TTS Simplex: chunk 结�,tts_token_buffer 剩余 7 tokens (�留等下一个 chunk)
22:28:25.045 TTS Simplex: generated 84 audio tokens for chunk 4
22:28:25.045 TTS Simplex: chunk 4 first tokens: [4441 6455 2229 4803 6261 ], last tokens: [4299 4299 1726 5614 4831 ]
22:28:25.045 TTS Simplex: updated tts_n_past_accumulated=462, total_generated_tokens=407
22:28:25.047 TTS<-LLM: chunk_idx=5, text='就算�到�难的事,��咬咬牙', n_tokens=10, hidden_size=40960, token_ids=[104501 104011 87256 99349 104140 3837 100671 105118 105118 100446]
22:28:25.047 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:25.047 TTS: before empty check - response.empty=0, response='就算�到�难的事,��咬咬牙', llm_finish=0
22:28:25.047 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:25.047 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:25.047 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:25.081 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_5/merged_embeddings.txt
22:28:25.081 TTS Simplex: generating audio tokens for chunk 5 (n_tokens=10, tts_n_embd=768)
22:28:25.081 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=5, new_size=11)
22:28:25.081 TTS Simplex: chunk 5 - keeping KV cache, n_past_tts=462
22:28:25.122 TTS Simplex: prefill completed, n_past_tts=473
22:28:25.122 TTS Simplex: sampler created
22:28:25.146 TTS Simplex Phase1: token 1/500: rel_id=2306
22:28:25.172 TTS Simplex Phase1: token 2/500: rel_id=667
22:28:25.197 TTS Simplex Phase1: token 3/500: rel_id=2125
22:28:25.221 TTS Simplex Phase1: token 4/500: rel_id=4580
22:28:25.244 TTS Simplex Phase1: token 5/500: rel_id=4520
22:28:25.559 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 18, buffer=25)
22:28:25.737 TTS Simplex Phase1: token 25/500: rel_id=4678
22:28:25.817 LLM->TTS: text='的?其实啊,�个人心里都��一个�', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[9370 11319 101045 103924 3837 101587 101998 71268 114880 107861]
22:28:26.001 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 43, buffer=25)
22:28:26.089 TTS Simplex Phase1: token 50/500: rel_id=5
22:28:26.318 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 68, buffer=25)
22:28:26.345 TTS Simplex Phase1: EOS token at step 71
22:28:26.345 TTS Simplex: chunk 结�,tts_token_buffer 剩余 2 tokens (�留等下一个 chunk)
22:28:26.345 TTS Simplex: generated 70 audio tokens for chunk 5
22:28:26.345 TTS Simplex: chunk 5 first tokens: [2306 667 2125 4580 4520 ], last tokens: [5241 1862 1376 2357 6401 ]
22:28:26.345 TTS Simplex: updated tts_n_past_accumulated=543, total_generated_tokens=477
22:28:26.346 TTS<-LLM: chunk_idx=6, text='挺过去,回头看的时候,�而觉得挺酷', n_tokens=10, hidden_size=40960, token_ids=[101174 100688 3837 115204 103920 3837 104503 99801 101174 102382]
22:28:26.346 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:26.346 TTS: before empty check - response.empty=0, response='挺过去,回头看的时候,å��而觉得挺é…', llm_finish=0
22:28:26.346 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:26.346 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:26.346 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:26.390 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_6/merged_embeddings.txt
22:28:26.390 TTS Simplex: generating audio tokens for chunk 6 (n_tokens=10, tts_n_embd=768)
22:28:26.390 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=6, new_size=11)
22:28:26.390 TTS Simplex: chunk 6 - keeping KV cache, n_past_tts=543
22:28:26.433 TTS Simplex: prefill completed, n_past_tts=554
22:28:26.433 TTS Simplex: sampler created
22:28:26.457 TTS Simplex Phase1: token 1/500: rel_id=2591
22:28:26.482 TTS Simplex Phase1: token 2/500: rel_id=566
22:28:26.504 TTS Simplex Phase1: token 3/500: rel_id=974
22:28:26.534 TTS Simplex Phase1: token 4/500: rel_id=4571
22:28:26.558 TTS Simplex Phase1: token 5/500: rel_id=4579
22:28:27.086 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 23, buffer=25)
22:28:27.152 TTS Simplex Phase1: token 25/500: rel_id=4921
22:28:27.154 LLM->TTS: text='宇宙,里�装�勇气�梦想和一点点', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[105339 3837 100420 98641 99164 106860 5373 102294 33108 107342]
22:28:27.499 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 48, buffer=25)
22:28:27.530 TTS Simplex Phase1: token 50/500: rel_id=0
22:28:27.898 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 73, buffer=25)
22:28:27.900 T2W线程: wav_2.wav | 1.00s audio | 3138.7ms inference | RTF=3.14 | t=11272ms
22:28:27.922 TTS Simplex Phase1: token 75/500: rel_id=1431
22:28:27.989 TTS Simplex Phase1: EOS token at step 81
22:28:27.989 TTS Simplex: chunk 结�,tts_token_buffer 剩余 7 tokens (�留等下一个 chunk)
22:28:27.989 TTS Simplex: generated 80 audio tokens for chunk 6
22:28:27.989 TTS Simplex: chunk 6 first tokens: [2591 566 974 4571 4579 ], last tokens: [1055 1460 1625 1649 5332 ]
22:28:27.989 TTS Simplex: updated tts_n_past_accumulated=634, total_generated_tokens=557
22:28:27.989 TTS<-LLM: chunk_idx=7, text='的?其实啊,�个人心里都��一个�', n_tokens=10, hidden_size=40960, token_ids=[9370 11319 101045 103924 3837 101587 101998 71268 114880 107861]
22:28:27.989 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:27.989 TTS: before empty check - response.empty=0, response='的?其实啊,æ¯�个人心里都è—�ç�€ä¸€ä¸ªå°', llm_finish=0
22:28:27.989 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:27.989 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:27.990 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:28.021 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_7/merged_embeddings.txt
22:28:28.021 TTS Simplex: generating audio tokens for chunk 7 (n_tokens=10, tts_n_embd=768)
22:28:28.021 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=7, new_size=11)
22:28:28.021 TTS Simplex: chunk 7 - keeping KV cache, n_past_tts=634
22:28:28.067 TTS Simplex: prefill completed, n_past_tts=645
22:28:28.067 TTS Simplex: sampler created
22:28:28.091 TTS Simplex Phase1: token 1/500: rel_id=2742
22:28:28.116 TTS Simplex Phase1: token 2/500: rel_id=4758
22:28:28.140 TTS Simplex Phase1: token 3/500: rel_id=1943
22:28:28.164 TTS Simplex Phase1: token 4/500: rel_id=59
22:28:28.188 TTS Simplex Phase1: token 5/500: rel_id=63
22:28:28.518 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 18, buffer=25)
22:28:28.691 TTS Simplex Phase1: token 25/500: rel_id=6486
22:28:28.782 LLM->TTS: text='�期待。别怕犯错,�还没', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[30709 104177 1773 62922 99756 100238 28726 3837 100165 104789]
22:28:28.965 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 43, buffer=25)
22:28:29.058 TTS Simplex Phase1: token 50/500: rel_id=3170
22:28:29.286 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 68, buffer=25)
22:28:29.376 TTS Simplex Phase1: token 75/500: rel_id=4445
22:28:29.417 TTS Simplex Phase1: EOS token at step 79
22:28:29.417 TTS Simplex: chunk 结�,tts_token_buffer 剩余 10 tokens (�留等下一个 chunk)
22:28:29.417 TTS Simplex: generated 78 audio tokens for chunk 7
22:28:29.417 TTS Simplex: chunk 7 first tokens: [2742 4758 1943 59 63 ], last tokens: [5986 4445 2753 566 395 ]
22:28:29.417 TTS Simplex: updated tts_n_past_accumulated=723, total_generated_tokens=635
22:28:29.418 TTS<-LLM: chunk_idx=8, text='宇宙,里�装�勇气�梦想和一点点', n_tokens=10, hidden_size=40960, token_ids=[105339 3837 100420 98641 99164 106860 5373 102294 33108 107342]
22:28:29.418 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:29.418 TTS: before empty check - response.empty=0, response='宇宙,里�装�勇气�梦想和一点点', llm_finish=0
22:28:29.418 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:29.418 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:29.418 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:29.453 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_8/merged_embeddings.txt
22:28:29.453 TTS Simplex: generating audio tokens for chunk 8 (n_tokens=10, tts_n_embd=768)
22:28:29.454 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=8, new_size=11)
22:28:29.454 TTS Simplex: chunk 8 - keeping KV cache, n_past_tts=723
22:28:29.506 TTS Simplex: prefill completed, n_past_tts=734
22:28:29.506 TTS Simplex: sampler created
22:28:29.533 TTS Simplex Phase1: token 1/500: rel_id=876
22:28:29.563 TTS Simplex Phase1: token 2/500: rel_id=1032
22:28:29.586 TTS Simplex Phase1: token 3/500: rel_id=65
22:28:29.610 TTS Simplex Phase1: token 4/500: rel_id=5087
22:28:29.635 TTS Simplex Phase1: token 5/500: rel_id=2259
22:28:29.905 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 15, buffer=25)
22:28:30.229 TTS Simplex Phase1: token 25/500: rel_id=4842
22:28:30.231 LLM->TTS: text='摔过跟头呢?��的是,你', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[103036 38182 99557 64355 101036 11319 99335 100146 3837 56568]
22:28:30.458 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 40, buffer=25)
22:28:30.617 TTS Simplex Phase1: token 50/500: rel_id=1885
22:28:30.878 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 65, buffer=25)
22:28:31.003 T2W线程: wav_3.wav | 1.00s audio | 3102.7ms inference | RTF=3.10 | t=14375ms
22:28:31.040 TTS Simplex Phase1: token 75/500: rel_id=4461
22:28:31.181 TTS Simplex Phase1: EOS token at step 86
22:28:31.181 TTS Simplex: chunk 结�,tts_token_buffer 剩余 20 tokens (�留等下一个 chunk)
22:28:31.181 TTS Simplex: generated 85 audio tokens for chunk 8
22:28:31.181 TTS Simplex: chunk 8 first tokens: [876 1032 65 5087 2259 ], last tokens: [3732 5835 3645 1701 2112 ]
22:28:31.181 TTS Simplex: updated tts_n_past_accumulated=819, total_generated_tokens=720
22:28:31.182 TTS<-LLM: chunk_idx=9, text='�期待。别怕犯错,�还没', n_tokens=10, hidden_size=40960, token_ids=[30709 104177 1773 62922 99756 100238 28726 3837 100165 104789]
22:28:31.182 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:31.182 TTS: before empty check - response.empty=0, response='�期待。别怕犯错,�还没', llm_finish=0
22:28:31.182 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:31.182 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:31.182 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:31.223 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_9/merged_embeddings.txt
22:28:31.223 TTS Simplex: generating audio tokens for chunk 9 (n_tokens=10, tts_n_embd=768)
22:28:31.223 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=9, new_size=11)
22:28:31.223 TTS Simplex: chunk 9 - keeping KV cache, n_past_tts=819
22:28:31.263 TTS Simplex: prefill completed, n_past_tts=830
22:28:31.263 TTS Simplex: sampler created
22:28:31.278 TTS Simplex Phase1: token 1/500: rel_id=6258
22:28:31.292 TTS Simplex Phase1: token 2/500: rel_id=4311
22:28:31.305 TTS Simplex Phase1: token 3/500: rel_id=4942
22:28:31.319 TTS Simplex Phase1: token 4/500: rel_id=5608
22:28:31.334 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 5, buffer=25)
22:28:31.334 TTS Simplex Phase1: token 5/500: rel_id=3266
22:28:31.643 TTS Simplex Phase1: token 25/500: rel_id=566
22:28:31.767 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 30, buffer=25)
22:28:32.292 TTS Simplex Phase1: token 50/500: rel_id=3647
22:28:32.346 LLM->TTS: text='有没有勇气爬起�继续往�走。所以说啊', n_tokens=10, hidden_size=40960, n_embd=4096, token_ids=[104710 106860 102377 99793 100640 114796 99314 1773 109304 103924]
22:28:32.386 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 55, buffer=25)
22:28:32.659 TTS Simplex Phase1: token 75/500: rel_id=4700
22:28:32.727 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 80, buffer=25)
22:28:32.787 TTS Simplex Phase1: EOS token at step 85
22:28:32.787 TTS Simplex: chunk 结�,tts_token_buffer 剩余 4 tokens (�留等下一个 chunk)
22:28:32.787 TTS Simplex: generated 84 audio tokens for chunk 9
22:28:32.787 TTS Simplex: chunk 9 first tokens: [6258 4311 4942 5608 3266 ], last tokens: [3024 5800 5093 2816 2675 ]
22:28:32.787 TTS Simplex: updated tts_n_past_accumulated=914, total_generated_tokens=804
22:28:32.788 TTS<-LLM: chunk_idx=10, text='摔过跟头呢?��的是,你', n_tokens=10, hidden_size=40960, token_ids=[103036 38182 99557 64355 101036 11319 99335 100146 3837 56568]
22:28:32.788 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:32.788 TTS: before empty check - response.empty=0, response='摔过跟头呢?��的是,你', llm_finish=0
22:28:32.788 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:32.788 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:32.788 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:32.829 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_10/merged_embeddings.txt
22:28:32.829 TTS Simplex: generating audio tokens for chunk 10 (n_tokens=10, tts_n_embd=768)
22:28:32.829 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=10, new_size=11)
22:28:32.829 TTS Simplex: chunk 10 - keeping KV cache, n_past_tts=914
22:28:32.875 TTS Simplex: prefill completed, n_past_tts=925
22:28:32.875 TTS Simplex: sampler created
22:28:32.890 TTS Simplex Phase1: token 1/500: rel_id=524
22:28:32.906 TTS Simplex Phase1: token 2/500: rel_id=2031
22:28:32.922 TTS Simplex Phase1: token 3/500: rel_id=3645
22:28:32.939 TTS Simplex Phase1: token 4/500: rel_id=5838
22:28:32.955 TTS Simplex Phase1: token 5/500: rel_id=5838
22:28:33.387 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 21, buffer=25)
22:28:33.528 TTS Simplex Phase1: token 25/500: rel_id=4851
22:28:33.942 LLM: detected end token, set llm_generation_done=true
22:28:33.942 LLM->TTS: text=',活�本身就是一�奇迹,对�?', n_tokens=9, hidden_size=36864, n_embd=4096, token_ids=[3837 107473 114300 101053 107012 3837 32664 100003 11319]
22:28:34.112 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 46, buffer=25)
22:28:34.182 TTS Simplex Phase1: token 50/500: rel_id=2112
22:28:34.280 T2W线程: wav_4.wav | 1.00s audio | 3276.0ms inference | RTF=3.28 | t=17653ms
22:28:34.351 TTS Simplex Phase1: EOS token at step 61
22:28:34.351 TTS Simplex: chunk 结�,tts_token_buffer 剩余 14 tokens (�留等下一个 chunk)
22:28:34.351 TTS Simplex: generated 60 audio tokens for chunk 10
22:28:34.351 TTS Simplex: chunk 10 first tokens: [524 2031 3645 5838 5838 ], last tokens: [4886 2276 5591 352 559 ]
22:28:34.351 TTS Simplex: updated tts_n_past_accumulated=985, total_generated_tokens=864
22:28:34.352 TTS<-LLM: chunk_idx=11, text='有没有勇气爬起�继续往�走。所以说啊', n_tokens=10, hidden_size=40960, token_ids=[104710 106860 102377 99793 100640 114796 99314 1773 109304 103924]
22:28:34.352 TTS: after queue pop - speek_done=0, llm_finish=0, llm_text.empty=0, token_ids.size=10
22:28:34.352 TTS: before empty check - response.empty=0, response='有没有勇气爬起æ�¥ç»§ç»­å¾€å‰�走。所以è¯', llm_finish=0
22:28:34.352 TTS: DEBUG before has_llm_data - token_ids.size=10, hidden_states.size=40960, n_embd=4096
22:28:34.352 TTS: has_llm_data=1, token_ids=10, hidden_states=40960, n_embd=4096, llm_finish=0
22:28:34.352 � Decode 结�: n_past=301, 剩余空间=1747, 无需滑窗
22:28:34.352 � 轮次 1 结�,记录边界于 n_past=301
22:28:34.352 TTS: n_tokens_orig=10, n_tokens_filtered=10 (filtered 0 special tokens)
22:28:34.383 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_11/merged_embeddings.txt
22:28:34.383 TTS Simplex: generating audio tokens for chunk 11 (n_tokens=10, tts_n_embd=768)
22:28:34.383 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=11, new_size=11)
22:28:34.383 TTS Simplex: chunk 11 - keeping KV cache, n_past_tts=985
22:28:34.431 TTS Simplex: prefill completed, n_past_tts=996
22:28:34.431 TTS Simplex: sampler created
22:28:34.445 TTS Simplex Phase1: token 1/500: rel_id=113
22:28:34.460 TTS Simplex Phase1: token 2/500: rel_id=5264
22:28:34.475 TTS Simplex Phase1: token 3/500: rel_id=5319
22:28:34.489 TTS Simplex Phase1: token 4/500: rel_id=5322
22:28:34.503 TTS Simplex Phase1: token 5/500: rel_id=876
22:28:34.588 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 11, buffer=25)
22:28:34.690 � 为下一轮准备: eval <|im_end|>\n<|im_start|>user\n, n_past=306
22:28:34.820 TTS Simplex Phase1: token 25/500: rel_id=4978
22:28:34.971 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 36, buffer=25)
22:28:35.171 TTS Simplex Phase1: token 50/500: rel_id=1466
22:28:35.330 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 61, buffer=25)
22:28:35.530 TTS Simplex Phase1: token 75/500: rel_id=494
22:28:35.602 TTS Simplex Phase1: EOS token at step 81
22:28:35.602 TTS Simplex: chunk 结�,tts_token_buffer 剩余 19 tokens (�留等下一个 chunk)
22:28:35.602 TTS Simplex: generated 80 audio tokens for chunk 11
22:28:35.602 TTS Simplex: chunk 11 first tokens: [113 5264 5319 5322 876 ], last tokens: [602 2060 4299 6486 6486 ]
22:28:35.602 TTS Simplex: updated tts_n_past_accumulated=1076, total_generated_tokens=944
22:28:35.612 TTS<-LLM: chunk_idx=12, text=',活�本身就是一�奇迹,对�?', n_tokens=9, hidden_size=36864, token_ids=[3837 107473 114300 101053 107012 3837 32664 100003 11319]
22:28:35.612 TTS: after queue pop - speek_done=0, llm_finish=1, llm_text.empty=0, token_ids.size=9
22:28:35.612 TTS: before empty check - response.empty=0, response=',活�本身就是一�奇迹,对�?', llm_finish=1
22:28:35.612 TTS: DEBUG before has_llm_data - token_ids.size=9, hidden_states.size=36864, n_embd=4096
22:28:35.612 TTS: has_llm_data=1, token_ids=9, hidden_states=36864, n_embd=4096, llm_finish=1
22:28:35.612 TTS: n_tokens_orig=9, n_tokens_filtered=9 (filtered 0 special tokens)
22:28:35.642 TTS: saved merged embeddings (text) to ./tools/omni/output/round_000/llm_debug/chunk_12/merged_embeddings.txt
22:28:35.642 TTS Simplex: generating audio tokens for chunk 12 (n_tokens=9, tts_n_embd=768)
22:28:35.642 TTS Simplex: 在 prefill �添加 audio_bos (chunk_idx=12, new_size=10)
22:28:35.642 TTS Simplex: chunk 12 - keeping KV cache, n_past_tts=1076
22:28:35.690 TTS Simplex: prefill completed, n_past_tts=1086
22:28:35.690 TTS Simplex: sampler created
22:28:35.704 TTS Simplex Phase1: token 1/500: rel_id=6486
22:28:35.718 TTS Simplex Phase1: token 2/500: rel_id=4299
22:28:35.732 TTS Simplex Phase1: token 3/500: rel_id=4218
22:28:35.747 TTS Simplex Phase1: token 4/500: rel_id=3975
22:28:35.761 TTS Simplex Phase1: token 5/500: rel_id=4299
22:28:35.775 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 6, buffer=25)
22:28:36.069 TTS Simplex Phase1: token 25/500: rel_id=3647
22:28:36.168 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 31, buffer=25)
22:28:36.481 TTS Simplex Phase1: token 50/500: rel_id=361
22:28:36.589 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 56, buffer=25)
22:28:36.883 T2W线程: wav_5.wav | 1.00s audio | 2601.6ms inference | RTF=2.60 | t=20255ms
22:28:36.923 TTS Simplex Phase1: token 75/500: rel_id=2436
22:28:37.013 TTS Simplex Phase1: yield 25 tokens 到 T2W (step 81, buffer=25)
22:28:37.145 TTS Simplex Phase1: EOS token at step 90
22:28:37.145 TTS Simplex: is_final_text_chunk=true, will enter Phase 2 for text_eos_embed
22:28:37.145 TTS Simplex Phase2: injecting text_eos_embed + audio_bos at n_past=1175
22:28:37.157 TTS Simplex Phase2: text_eos_embed injected, n_past=1176
22:28:37.168 TTS Simplex Phase2: audio_bos injected, n_past=1177, starting final generation
22:28:37.390 TTS Simplex Phase2: EOS at step 14 (final end)
22:28:37.390 TTS Simplex: chunk 结�,tts_token_buffer 剩余 21 tokens (�留等下一个 chunk)
22:28:37.390 TTS Simplex: is_final_text_chunk=true, flush 剩余 21 tokens 从 tts_token_buffer
22:28:37.390 TTS Simplex: generated 102 audio tokens for chunk 12
22:28:37.390 TTS Simplex: chunk 12 first tokens: [6486 4299 4218 3975 4299 ], last tokens: [4384 3897 6486 6486 4299 ]
22:28:37.390 TTS Simplex: updated tts_n_past_accumulated=1191, total_generated_tokens=1046
22:28:37.399 TTS: finished processing all chunks
22:28:37.399 TTS: �工模�轮次结�,下一轮 round_idx=1
22:28:37.399 TTS: sent is_final=true to T2W queue (turn end)
22:28:39.451 T2W线程: wav_6.wav | 1.00s audio | 2567.8ms inference | RTF=2.57 | t=22823ms
22:28:41.704 T2W线程: wav_7.wav | 1.00s audio | 2251.6ms inference | RTF=2.25 | t=25076ms
22:28:43.954 T2W线程: wav_8.wav | 1.00s audio | 2249.3ms inference | RTF=2.25 | t=27326ms
22:28:46.208 T2W线程: wav_9.wav | 1.00s audio | 2254.1ms inference | RTF=2.25 | t=29581ms
22:28:48.471 T2W线程: wav_10.wav | 1.00s audio | 2261.9ms inference | RTF=2.26 | t=31843ms
22:28:50.731 T2W线程: wav_11.wav | 1.00s audio | 2259.2ms inference | RTF=2.26 | t=34103ms
22:28:52.994 T2W线程: wav_12.wav | 1.00s audio | 2262.3ms inference | RTF=2.26 | t=36366ms
22:28:55.241 T2W线程: wav_13.wav | 1.00s audio | 2245.8ms inference | RTF=2.25 | t=38613ms
22:28:57.493 T2W线程: wav_14.wav | 1.00s audio | 2243.6ms inference | RTF=2.24 | t=40865ms
22:28:59.727 T2W线程: wav_15.wav | 1.00s audio | 2233.5ms inference | RTF=2.23 | t=43099ms
22:29:01.986 T2W线程: wav_16.wav | 1.00s audio | 2247.9ms inference | RTF=2.25 | t=45358ms
22:29:04.270 T2W线程: wav_17.wav | 1.00s audio | 2283.5ms inference | RTF=2.28 | t=47642ms
22:29:06.553 T2W线程: wav_18.wav | 1.00s audio | 2282.2ms inference | RTF=2.28 | t=49925ms
22:29:08.804 T2W线程: wav_19.wav | 1.00s audio | 2250.0ms inference | RTF=2.25 | t=52176ms
22:29:11.073 T2W线程: wav_20.wav | 1.00s audio | 2258.2ms inference | RTF=2.26 | t=54445ms
22:29:13.334 T2W线程: wav_21.wav | 1.00s audio | 2260.2ms inference | RTF=2.26 | t=56706ms
22:29:15.586 T2W线程: wav_22.wav | 1.00s audio | 2251.7ms inference | RTF=2.25 | t=58958ms
22:29:17.855 T2W线程: wav_23.wav | 1.00s audio | 2268.6ms inference | RTF=2.27 | t=61227ms
22:29:20.119 T2W线程: wav_24.wav | 1.00s audio | 2263.4ms inference | RTF=2.26 | t=63492ms
22:29:22.375 T2W线程: wav_25.wav | 1.00s audio | 2255.1ms inference | RTF=2.26 | t=65747ms
22:29:24.634 T2W线程: wav_26.wav | 1.00s audio | 2258.4ms inference | RTF=2.26 | t=68006ms
22:29:26.885 T2W线程: wav_27.wav | 1.00s audio | 2250.1ms inference | RTF=2.25 | t=70257ms
22:29:29.146 T2W线程: wav_28.wav | 1.00s audio | 2260.1ms inference | RTF=2.26 | t=72518ms
22:29:31.398 T2W线程: wav_29.wav | 1.00s audio | 2251.4ms inference | RTF=2.25 | t=74770ms
22:29:33.656 T2W线程: wav_30.wav | 1.00s audio | 2257.1ms inference | RTF=2.26 | t=77028ms
22:29:35.899 T2W线程: wav_31.wav | 1.00s audio | 2242.6ms inference | RTF=2.24 | t=79271ms
22:29:38.169 T2W线程: wav_32.wav | 1.00s audio | 2269.3ms inference | RTF=2.27 | t=81541ms
22:29:40.423 T2W线程: wav_33.wav | 1.00s audio | 2252.7ms inference | RTF=2.25 | t=83795ms
22:29:42.682 T2W线程: wav_34.wav | 1.00s audio | 2250.6ms inference | RTF=2.25 | t=86054ms
22:29:44.941 T2W线程: wav_35.wav | 1.00s audio | 2257.8ms inference | RTF=2.26 | t=88313ms
22:29:47.208 T2W线程: wav_36.wav | 1.00s audio | 2267.2ms inference | RTF=2.27 | t=90581ms
22:29:49.462 T2W线程: wav_37.wav | 1.00s audio | 2252.6ms inference | RTF=2.25 | t=92834ms
22:29:51.715 T2W线程: wav_38.wav | 1.00s audio | 2253.0ms inference | RTF=2.25 | t=95088ms
22:29:53.969 T2W线程: wav_39.wav | 1.00s audio | 2252.7ms inference | RTF=2.25 | t=97341ms
22:29:56.231 T2W线程: wav_40.wav | 1.00s audio | 2261.3ms inference | RTF=2.26 | t=99603ms
22:29:58.497 T2W线程: wav_41.wav | 1.12s audio | 2265.0ms inference | RTF=2.02 | t=101869ms
22:29:58.497 T2W线程: 写入结�标记 ./tools/omni/output/round_000/tts_wav/generation_done.flag (last_wav=41)
22:29:58.497 T2W线程: 轮次结��更新输出目录为 ./tools/omni/output/round_001/tts_wav
22:29:58.605 omni_stop_threads: stop signals sent
22:29:58.605 T2W(C++) 线程: �止
tts thread end
t2w thread end
@@ -0,0 +1,302 @@
{
"scope": "standalone MiniCPM-o 4.5 GGUF audio+image input to text+speech on native-Windows-11-HX370-Radeon-890M-plus-CPU",
"status": "scoped_complete_path_pass",
"expected_placement": "radeon-hybrid",
"quality": "synthetic red-square/tone response not established as semantically correct",
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"response_text": "你知道吗,有时候啊,我也会想啊,生活真的挺有意思的。每天早上醒来,太阳照在脸上,就觉得这一天充满了可能。不管前一天发生啥事,只要新的一天来了,就有机会重新开始。你有没有觉得,就算遇到再难的事,只要咬咬牙挺过去,回头看的时候,反而觉得挺酷的?其实啊,每个人心里都藏着一个小宇宙,里面装着勇气、梦想和一点点小期待。别怕犯错,谁还没摔过跟头呢?重要的是,你有没有勇气爬起来继续往前走。所以说啊,活着本身就是一种奇迹,对吧?",
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"name": "wav_37.wav",
"frames": 24000,
"sha256": "c9e9fe238f8cd98b4af583314ef7cf4877e98470d6471c7c218fa0d760b23de8"
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{
"name": "wav_38.wav",
"frames": 24000,
"sha256": "33c3ba34178e49520c9d5f8c48895bbfb8d7475505e1b53fa763bb37e79a9c15"
},
{
"name": "wav_39.wav",
"frames": 24000,
"sha256": "0f9ab5b3ec79a5464d9c818239f4da19cf1cf649db25a742b11189afbb20451f"
},
{
"name": "wav_40.wav",
"frames": 24000,
"sha256": "39a5e184c96d2fec5bbe492adba5980d67c2c235bbeed2af9b994816159f65a5"
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{
"name": "wav_41.wav",
"frames": 26880,
"sha256": "bb775223b13183f8c2dd75fdc1c8e43aa213dffc19d93abe81eb39c36a85bbbc"
}
],
"audio_frames": 1007040,
"audio_duration_s": 41.96,
"audio_rms_pcm16": 2399.4583535294237,
"pcm_sha256": "ee8de0dc5a574a8168a23c4a0e70f911d7b981ecd6cb921a5fbf9698f7d45636",
"merged_wav_sha256": "bf1d7c665eec4e7da09d03f89bac110ff07a7f4335fde7add212c0363fadaa80",
"peak_rss_kib_from_time": null,
"wall_clock_from_time": null,
"sampled_process_profile": {
"command": [
"C:\\Users\\zhout\\w2\\minicpmo_cpp_radeon\\llama-omni-cli.exe",
"-m",
"C:\\Users\\zhout\\w2\\models\\MiniCPM-o-4_5-gguf\\MiniCPM-o-4_5-Q4_K_M.gguf",
"-ngl",
"99",
"-c",
"2048",
"--omni",
"--t2w-device",
"cpu",
"--t2w-wait-seconds",
"900",
"--ref-audio",
"C:\\Users\\zhout\\w2\\minicpmo_cpp_radeon\\default_ref_audio.wav",
"--test",
"C:\\Users\\zhout\\w2\\minicpmo_cpp_radeon\\fixture_",
"2"
],
"cwd": "C:\\Users\\zhout\\w2\\minicpmo_cpp_radeon",
"exit_code": 0,
"wall_s": 113.42734129994642,
"memory_sample_interval_ms": 100,
"memory_samples": 1128,
"peak_sampled_rss_bytes": 15568060416,
"peak_sampled_private_bytes": 15451271168,
"measurement_note": "sampled process values, not guaranteed loading peaks"
},
"upstream_merge_name_mismatch": true
}
@@ -0,0 +1 @@
你知道吗,有时候啊,我也会想啊,生活真的挺有意思的。每天早上醒来,太阳照在脸上,就觉得这一天充满了可能。不管前一天发生啥事,只要新的一天来了,就有机会重新开始。你有没有觉得,就算遇到再难的事,只要咬咬牙挺过去,回头看的时候,反而觉得挺酷的?其实啊,每个人心里都藏着一个小宇宙,里面装着勇气、梦想和一点点小期待。别怕犯错,谁还没摔过跟头呢?重要的是,你有没有勇气爬起来继续往前走。所以说啊,活着本身就是一种奇迹,对吧?
@@ -0,0 +1 @@
你知道吗,有时候啊,我也会想啊
@@ -0,0 +1 @@
,生活真的挺有意思的。每天早上醒来,
@@ -0,0 +1 @@
有没有勇气爬起来继续往前走。所以说啊
@@ -0,0 +1 @@
,活着本身就是一种奇迹,对吧?
@@ -0,0 +1 @@
太阳照在脸上,就觉得这一天充满了可能。
@@ -0,0 +1 @@
不管前一天发生啥事,只要新的一天来了
@@ -0,0 +1 @@
,就有机会重新开始。你有没有觉得,
@@ -0,0 +1 @@
挺过去,回头看的时候,反而觉得挺酷
@@ -0,0 +1 @@
的?其实啊,每个人心里都藏着一个小
@@ -0,0 +1 @@
宇宙,里面装着勇气、梦想和一点点
@@ -0,0 +1 @@
1571,6486,4299,4299,4299,4299,1960,566,404,1041,4593,3077,396,4375,5590,1395,2125,4619,5357,4628,4636,5365,4299,6486,4299,4299,4299,3975,5838,3732,4299,2040,3480,2753,218,713,5944,5322,159,110,5589,5602,5053,4982,4907,2279,2189,2918,731,1703,1951,2112,719
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728,4613,4803,4551,4466,2673,2772,2408,4778,5482,4920,2276,1703,1964,991,11,2918,5105,5834,3647,3656,1459,4299,6486,4299,4299,4218,5838,3732,1788,6021,5322,159,137,4961,2698,2763,635,218,231,4515,3077,4414,5937,6261,2259,4456,2189,2,219,60,4623,1241,5777,4507,389,632,80,4911,4992,5100,4425,6454,6373,3231,543,2246,731,3161,3169,3888,6486,6486,4299,4299,4218,3648,5835,5838,3651,1545,2112,2121,1882,287,485,870,2726,4489,5205,6387
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@@ -0,0 +1 @@
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@@ -0,0 +1 @@
2502,974,1163,5970,957,5915,4557,5402,5404,2888,1079,1721,1262,29,3650,3650,2924,4543,4570,2032,2922,5838,2922,1545,2112,54,5835,5111,4688,2474,731,2720,3103,1743,3147,4538,4943,63,5652,4463,166,3717,2582,143,845,998,5214,2409,2303,5914,2675,263,2028,3888,5835,3732,3003,2112,4920,969,3638,888,4921,1943,140,138,73,2354,2300,113,1520,2112,4299,1005,4593,3157,4598,4778,3482,969,1029,4704,2724,2573,4382,5937,2130,6051,1539
@@ -0,0 +1 @@
2676,4981,5065,5775,6501,2854,5113,1463,1010,1262,2216,960,162,2349,2476,56,1641,748,731,497,515,4907,5608,2032,6486,6486,4299,4218,5832,5832,5919,5838,5835,3648,2106,2166,1440,5098,582,721,191,104,6396,4432,25,116,4967,4966,1644,2274,2688,2339,2219,4744,3531,6537,2756,6157,4489,5319,2290,5286,5953,5322,89,1703,1460,2393,5319,2406,4571,6239,1622,1649,1648,6486,4299,3732,5919,5838,3651,2922,816,2112,1518,5323,1132,476,974,2756
@@ -0,0 +1 @@
4441,6455,2229,4803,6261,2232,4445,5668,4912,960,2274,2454,4543,4637,6149,2918,1463,737,2195,3071,4691,4537,5348,254,1944,3888,5835,5838,3651,2112,1977,4675,2423,2426,890,713,875,1275,5404,2023,5507,2585,2757,2775,4835,2411,386,1286,2112,5325,3807,502,1403,4316,4452,5645,2238,4803,6504,33,5835,3653,2600,4778,5319,5322,3063,1862,1610,1601,4299,6486,6486,6486,6486,6486,6486,4299,4299,4299,4299,1726,5614,4831
@@ -0,0 +1 @@
2306,667,2125,4580,4520,281,321,4675,1133,62,2246,300,4433,4376,2189,2198,1701,3888,5919,5838,5838,3003,2112,3462,4678,5587,5086,4448,5645,3456,4511,4376,4643,5775,6289,888,63,3242,4646,1110,6374,4411,4542,4462,834,2236,3650,18,1719,5,2348,5319,4593,2399,5267,1622,1649,1625,1623,3972,5919,5838,3003,1869,1491,5241,1862,1376,2357,6401
@@ -0,0 +1 @@
2591,566,974,4571,4579,5672,245,2753,2752,818,3647,5834,5265,1896,60,4704,2679,620,1484,1970,1239,696,5077,2415,4921,4569,1149,6074,968,869,1519,1707,4215,4299,3972,3888,6156,6075,3888,4131,2112,1383,2841,1373,4604,60,2187,4871,5095,0,2268,5832,5994,2205,4149,2219,5173,5319,879,137,2710,4860,4877,4973,2789,2870,2789,3486,4299,4215,3975,4299,4218,6537,1431,1055,1460,1625,1649,5332
@@ -0,0 +1 @@
2742,4758,1943,59,63,4568,2415,60,4704,2760,593,1724,2050,648,5751,2766,5100,5088,144,306,5,1460,1459,4299,6486,6486,6486,6486,4299,4218,4002,4299,4299,4299,4299,2085,5648,4432,1051,5588,5251,5319,3054,1537,1691,3083,5834,6077,3890,3170,1710,1704,5832,5835,3648,1461,2040,4068,911,2465,476,3,2666,4600,6073,1682,4553,4399,5402,4675,5398,4522,5931,5986,4445,2753,566,395
@@ -0,0 +1 @@
876,1032,65,5087,2259,5647,2916,5832,1946,1253,4151,1509,3141,4607,4940,3455,2672,3,4612,4441,5483,2463,8,2678,4842,4857,3534,1943,1862,1680,5325,970,4807,5053,2789,611,2032,4299,4299,3891,5916,5838,2922,1465,2031,1854,80,2753,1888,1885,359,2285,1725,6051,3155,4862,4879,3832,5244,3158,2300,2324,29,1517,1987,2022,3237,3152,701,2132,1808,3462,5402,4408,4461,4857,5100,5021,2591,1816,3732,5835,3645,1701,2112
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@@ -0,0 +1,3 @@
# WAV file generation timing log
# Format: chunk_index, elapsed_time_ms (since stream_decode start), file_size_bytes, request_duration_ms
# Time 0 is when stream_decode() function starts
Loaded 100 of 150 files, more files were not shown because too many files have changed in this diff. Show more