Palash DebnathandClaude Opus 4.8
63a0d00f09
Windows + NVIDIA users hit `Could not locate cudnn_ops_infer64_8.dll`: WhisperX/faster-whisper run on CTranslate2, which needs cuDNN 8, but PyTorch 2.8 ships cuDNN 9 and the side-loaded `cudnn8_compat` libs were missing from the venv. The PyTorch-Whisper backend should have been the fallback, but it errored "set OMNIVOICE_PRELOAD_TTS_ASR=1" because it only worked when the TTS model preloaded an ASR head. - `PyTorchWhisperBackend._ensure_pipe()` now builds its OWN transformers ASR pipeline on demand (PyTorch stack → cuDNN 9, no CTranslate2/cuDNN-8), without loading the full TTS model and without the preload env var. A constructor- passed pipe (when the TTS model already has one) is still reused. Model is overridable via OMNIVOICE_PYTORCH_ASR_MODEL. - dub_core transcribe preflight no longer hard-rejects pytorch-whisper when no pipe is preloaded — it lazy-loads; any failure surfaces per-chunk with the real cause. So a Windows box without cuDNN 8 can switch ASR backend to "PyTorch Whisper" in Settings → Models and transcription works. Docs: troubleshooting entry. Tests: tests/test_pytorch_whisper_fallback.py (lazy standalone build, reuse of a passed pipe, no get_model() call, env override). Full tests/ suite: 700 pass. Does NOT close #255 — pending the reporter confirming the fallback works on their machine; the cuDNN-8 install gap (faster-whisper path) is a follow-up. Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
84 lines
2.7 KiB
Python
84 lines
2.7 KiB
Python
"""PyTorch-Whisper backend must work as a standalone fallback (issue #255).
|
|
|
|
On machines where WhisperX / faster-whisper can't load cuDNN 8
|
|
(`cudnn_ops_infer64_8.dll` missing), the PyTorch-Whisper backend should build
|
|
its own transformers pipeline on demand — without OMNIVOICE_PRELOAD_TTS_ASR=1
|
|
and without loading the full TTS model.
|
|
"""
|
|
import sys
|
|
import types
|
|
|
|
import pytest
|
|
|
|
from services import asr_backend as ab
|
|
|
|
|
|
def test_is_available_when_transformers_present():
|
|
ok, msg = ab.PyTorchWhisperBackend.is_available()
|
|
assert ok is True
|
|
assert msg == "ready"
|
|
|
|
|
|
def test_reuses_constructor_pipe_without_building(monkeypatch):
|
|
sentinel = object()
|
|
be = ab.PyTorchWhisperBackend(asr_pipe=sentinel)
|
|
|
|
def _boom(*a, **k):
|
|
raise AssertionError("must not build a pipeline when one was passed in")
|
|
|
|
# transformers.pipeline is imported lazily inside _ensure_pipe.
|
|
fake_tf = types.ModuleType("transformers")
|
|
fake_tf.pipeline = _boom
|
|
monkeypatch.setitem(sys.modules, "transformers", fake_tf)
|
|
|
|
be._ensure_pipe()
|
|
assert be._pipe is sentinel
|
|
|
|
|
|
def test_lazy_builds_standalone_pipeline(monkeypatch):
|
|
"""No preloaded pipe → build a standalone transformers ASR pipeline, with no
|
|
call into the TTS model loader (get_model)."""
|
|
captured = {}
|
|
|
|
def fake_pipeline(task, **kw):
|
|
captured["task"] = task
|
|
captured["kw"] = kw
|
|
return lambda *a, **k: {"chunks": []}
|
|
|
|
fake_tf = types.ModuleType("transformers")
|
|
fake_tf.pipeline = fake_pipeline
|
|
monkeypatch.setitem(sys.modules, "transformers", fake_tf)
|
|
monkeypatch.setattr("services.model_manager.get_best_device", lambda: "cpu")
|
|
|
|
# Guard: building the standalone pipe must NOT pull in the full TTS model.
|
|
import services.model_manager as mm
|
|
|
|
def _no_get_model(*a, **k):
|
|
raise AssertionError("standalone ASR build must not call get_model()")
|
|
|
|
monkeypatch.setattr(mm, "get_model", _no_get_model, raising=False)
|
|
|
|
be = ab.PyTorchWhisperBackend(asr_pipe=None)
|
|
be._ensure_pipe()
|
|
|
|
assert be._pipe is not None
|
|
assert captured["task"] == "automatic-speech-recognition"
|
|
assert captured["kw"]["model"] # a concrete model name was chosen
|
|
|
|
|
|
def test_pytorch_asr_model_overridable_via_env(monkeypatch):
|
|
captured = {}
|
|
|
|
def fake_pipeline(task, **kw):
|
|
captured["kw"] = kw
|
|
return object()
|
|
|
|
fake_tf = types.ModuleType("transformers")
|
|
fake_tf.pipeline = fake_pipeline
|
|
monkeypatch.setitem(sys.modules, "transformers", fake_tf)
|
|
monkeypatch.setattr("services.model_manager.get_best_device", lambda: "cpu")
|
|
monkeypatch.setenv("OMNIVOICE_PYTORCH_ASR_MODEL", "openai/whisper-small")
|
|
|
|
ab.PyTorchWhisperBackend(asr_pipe=None)._ensure_pipe()
|
|
assert captured["kw"]["model"] == "openai/whisper-small"
|