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https://github.com/jamiepine/voicebox.git
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fix(offline): patch transformers mistral-regex check to survive HF failures (#530)
* fix(offline): patch transformers mistral-regex check to survive HF failures transformers 4.57.x's `PreTrainedTokenizerBase._patch_mistral_regex` calls `huggingface_hub.model_info(repo_id)` unconditionally during any non-local tokenizer load to probe for Mistral-family models. The call raises on `HF_HUB_OFFLINE=1`, on network outages, and on slow/blocked HF endpoints, and transformers doesn't catch any of it — the exception bubbles out of `from_pretrained` and kills the load for unrelated engines (Qwen TTS, Qwen CustomVoice, TADA, etc.). 0.4.2's load-time `force_offline_if_cached` guard walked straight into this trap: on cached online users it flipped `HF_HUB_OFFLINE=1` and converted a healthy load into a hard crash. 0.4.3's inference-path guard masked it; #524 removed the inference guard in 0.4.4, and users updating to 0.4.4 started hitting the same error on the load path instead (#526). Fix: - Wrap `_patch_mistral_regex` so any exception from the inner HF metadata check is swallowed and the tokenizer is returned unchanged. Voicebox never loads Mistral models, so the regex rewrite this check gates is a no-op for us; matches the success-path behavior for non-Mistral repos (tokenization_utils_base.py:2503). - Drop the `force_offline_if_cached` wraps from every load path (pytorch_backend Qwen + Whisper, qwen_custom_voice_backend, mlx_backend Qwen + Whisper). With the mistral patch in place they provide zero value and only risk re-introducing the same class of bug. Helper and its unit tests stay — still correct for targeted future use. - Add `backend/tests/test_offline_patch.py` covering OfflineModeIsEnabled / ConnectionError suppression, success pass-through, idempotence, and the missing-method no-op path. Fixes #526. * fix(offline): install mistral-regex patch for non-MLX backends The previous commit left the patch wired only through ``mlx_backend.py``'s existing import of ``hf_offline_patch``. On Windows/Linux/CUDA users who never load the MLX backend (everyone who hit #526), the patch module was never imported, so ``patch_transformers_mistral_regex`` never ran and the crash persisted. Hoist the import into ``backends/__init__.py``. Every backend imports from this package, so the module-level patch install runs before any ``from_pretrained`` call regardless of which engine the user picks. Caught by CodeRabbit and Cursor Bugbot on #530.
This commit is contained in:
Jamie Pine
@@ -5,6 +5,13 @@ Provides a unified interface for MLX and PyTorch backends,
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and a model config registry that eliminates per-engine dispatch maps.
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"""
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# Install HF compatibility patches before any backend imports transformers /
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# huggingface_hub. The module runs ``patch_transformers_mistral_regex`` at
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# import time, which wraps transformers' tokenizer load against the
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# unconditional HuggingFace metadata call that otherwise raises on
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# HF_HUB_OFFLINE=1 and on network failures.
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from ..utils import hf_offline_patch # noqa: F401
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import threading
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from dataclasses import dataclass, field
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from typing import Protocol, Optional, Tuple, List
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@@ -20,7 +20,6 @@ ensure_original_qwen_config_cached()
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from . import TTSBackend, STTBackend, LANGUAGE_CODE_TO_NAME, WHISPER_HF_REPOS
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from .base import is_model_cached, combine_voice_prompts as _combine_voice_prompts, model_load_progress
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from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
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from ..utils.hf_offline_patch import force_offline_if_cached
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class MLXTTSBackend:
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@@ -99,8 +98,7 @@ class MLXTTSBackend:
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logger.info("Loading MLX TTS model %s...", model_size)
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with force_offline_if_cached(is_cached, model_name):
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self.model = load(model_path)
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self.model = load(model_path)
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self._current_model_size = model_size
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self.model_size = model_size
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@@ -311,8 +309,7 @@ class MLXSTTBackend:
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model_name = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
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logger.info("Loading MLX Whisper model %s...", model_size)
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with force_offline_if_cached(is_cached, progress_model_name):
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self.model = load(model_name)
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self.model = load(model_name)
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self.model_size = model_size
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logger.info("MLX Whisper model %s loaded successfully", model_size)
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@@ -21,7 +21,6 @@ from .base import (
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)
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from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
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from ..utils.audio import load_audio
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from ..utils.hf_offline_patch import force_offline_if_cached
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class PyTorchTTSBackend:
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@@ -106,21 +105,20 @@ class PyTorchTTSBackend:
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from huggingface_hub import constants as hf_constants
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tts_cache_dir = hf_constants.HF_HUB_CACHE
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with force_offline_if_cached(is_cached, model_name):
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if self.device == "cpu":
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self.model = Qwen3TTSModel.from_pretrained(
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model_path,
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cache_dir=tts_cache_dir,
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torch_dtype=torch.float32,
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low_cpu_mem_usage=False,
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)
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else:
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self.model = Qwen3TTSModel.from_pretrained(
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model_path,
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cache_dir=tts_cache_dir,
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device_map=self.device,
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torch_dtype=torch.bfloat16,
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)
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if self.device == "cpu":
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self.model = Qwen3TTSModel.from_pretrained(
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model_path,
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cache_dir=tts_cache_dir,
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torch_dtype=torch.float32,
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low_cpu_mem_usage=False,
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)
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else:
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self.model = Qwen3TTSModel.from_pretrained(
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model_path,
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cache_dir=tts_cache_dir,
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device_map=self.device,
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torch_dtype=torch.bfloat16,
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)
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self._current_model_size = model_size
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self.model_size = model_size
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@@ -297,9 +295,8 @@ class PyTorchSTTBackend:
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model_name = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
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logger.info("Loading Whisper model %s on %s...", model_size, self.device)
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with force_offline_if_cached(is_cached, progress_model_name):
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self.processor = WhisperProcessor.from_pretrained(model_name)
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self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
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self.processor = WhisperProcessor.from_pretrained(model_name)
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self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
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self.model.to(self.device)
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self.model_size = model_size
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@@ -28,7 +28,6 @@ from .base import (
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combine_voice_prompts as _combine_voice_prompts,
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model_load_progress,
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)
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from ..utils.hf_offline_patch import force_offline_if_cached
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logger = logging.getLogger(__name__)
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@@ -105,19 +104,18 @@ class QwenCustomVoiceBackend:
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model_path = self._get_model_path(model_size)
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logger.info("Loading Qwen CustomVoice %s on %s...", model_size, self.device)
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with force_offline_if_cached(is_cached, model_name):
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if self.device == "cpu":
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self.model = Qwen3TTSModel.from_pretrained(
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model_path,
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torch_dtype=torch.float32,
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low_cpu_mem_usage=False,
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)
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else:
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self.model = Qwen3TTSModel.from_pretrained(
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model_path,
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device_map=self.device,
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torch_dtype=torch.bfloat16,
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)
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if self.device == "cpu":
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self.model = Qwen3TTSModel.from_pretrained(
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model_path,
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torch_dtype=torch.float32,
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low_cpu_mem_usage=False,
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)
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else:
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self.model = Qwen3TTSModel.from_pretrained(
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model_path,
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device_map=self.device,
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torch_dtype=torch.bfloat16,
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)
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self._current_model_size = model_size
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self.model_size = model_size
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@@ -0,0 +1,113 @@
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"""
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Unit tests for ``patch_transformers_mistral_regex``.
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Verifies that our wrapper around
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``transformers.PreTrainedTokenizerBase._patch_mistral_regex`` catches
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exceptions from the unconditional ``huggingface_hub.model_info()`` lookup
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and returns the tokenizer unchanged — matching the success-path behavior
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for non-Mistral repos (transformers 4.57.3, ``tokenization_utils_base.py:2503``).
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NOTE: These tests mutate ``transformers.PreTrainedTokenizerBase`` globally;
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run serially, not under ``pytest-xdist`` with per-worker process isolation.
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"""
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import sys
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from pathlib import Path
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import pytest
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from huggingface_hub.errors import OfflineModeIsEnabled # noqa: E402
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from transformers.tokenization_utils_base import PreTrainedTokenizerBase # noqa: E402
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import utils.hf_offline_patch as hf_offline_patch # noqa: E402
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@pytest.fixture(autouse=True)
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def restore_mistral_regex():
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"""Snapshot the current ``_patch_mistral_regex`` and restore after each test."""
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saved = PreTrainedTokenizerBase.__dict__.get("_patch_mistral_regex")
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saved_flag = hf_offline_patch._mistral_regex_patched
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try:
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yield
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finally:
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if saved is not None:
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PreTrainedTokenizerBase._patch_mistral_regex = saved
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hf_offline_patch._mistral_regex_patched = saved_flag
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def _apply_patch():
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hf_offline_patch._mistral_regex_patched = False
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hf_offline_patch.patch_transformers_mistral_regex()
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def test_suppresses_offline_mode_is_enabled(monkeypatch):
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_apply_patch()
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import huggingface_hub
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def raise_offline(*_args, **_kwargs):
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raise OfflineModeIsEnabled("offline")
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monkeypatch.setattr(huggingface_hub, "model_info", raise_offline)
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sentinel = object()
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result = PreTrainedTokenizerBase._patch_mistral_regex(
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sentinel, "Qwen/Qwen3-TTS-12Hz-1.7B-Base"
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)
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assert result is sentinel
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def test_suppresses_connection_errors(monkeypatch):
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_apply_patch()
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import huggingface_hub
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def raise_connection(*_args, **_kwargs):
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raise ConnectionError("network unreachable")
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monkeypatch.setattr(huggingface_hub, "model_info", raise_connection)
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sentinel = object()
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result = PreTrainedTokenizerBase._patch_mistral_regex(
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sentinel, "Qwen/Qwen3-TTS-12Hz-1.7B-Base"
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)
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assert result is sentinel
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def test_passthrough_on_success(monkeypatch):
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"""When model_info returns non-Mistral tags the original falls through and returns the tokenizer unchanged."""
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_apply_patch()
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import huggingface_hub
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class FakeInfo:
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tags = ["model-type:qwen", "language:en"]
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monkeypatch.setattr(huggingface_hub, "model_info", lambda *_a, **_kw: FakeInfo())
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sentinel = object()
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result = PreTrainedTokenizerBase._patch_mistral_regex(
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sentinel, "Qwen/Qwen3-TTS-12Hz-1.7B-Base"
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)
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assert result is sentinel
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def test_idempotent():
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_apply_patch()
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first = PreTrainedTokenizerBase._patch_mistral_regex
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hf_offline_patch.patch_transformers_mistral_regex()
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second = PreTrainedTokenizerBase._patch_mistral_regex
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assert first.__func__ is second.__func__
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def test_missing_method_is_noop(monkeypatch):
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monkeypatch.delattr(PreTrainedTokenizerBase, "_patch_mistral_regex", raising=False)
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hf_offline_patch._mistral_regex_patched = False
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hf_offline_patch.patch_transformers_mistral_regex()
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assert hf_offline_patch._mistral_regex_patched is False
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if __name__ == "__main__":
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pytest.main([__file__, "-v"])
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@@ -142,6 +142,57 @@ def force_offline_if_cached(is_cached: bool, model_label: str = ""):
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_saved_transformers_const = None
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_mistral_regex_patched = False
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def patch_transformers_mistral_regex():
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"""Make transformers' tokenizer load robust to HuggingFace metadata failures.
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transformers 4.57.x added ``PreTrainedTokenizerBase._patch_mistral_regex``
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which unconditionally calls ``huggingface_hub.model_info(repo_id)`` during
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every non-local tokenizer load to check whether the model is a Mistral
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variant. That call raises on ``HF_HUB_OFFLINE=1`` and on plain network
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failures, killing unrelated loads (Qwen TTS, TADA, etc.).
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Voicebox never loads Mistral models, so the rewrite the function would
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apply is a no-op for us anyway. Wrap the method so any exception from the
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metadata lookup returns the tokenizer unchanged — matching the success-path
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behavior for non-Mistral repos (transformers 4.57.3,
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``tokenization_utils_base.py:2503``).
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"""
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global _mistral_regex_patched
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if _mistral_regex_patched:
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return
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try:
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from transformers.tokenization_utils_base import PreTrainedTokenizerBase
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except ImportError:
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logger.debug("transformers not available, skipping mistral-regex patch")
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return
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original = getattr(PreTrainedTokenizerBase, "_patch_mistral_regex", None)
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if original is None:
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logger.debug(
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"transformers has no _patch_mistral_regex attribute, skipping patch",
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)
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return
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def safe_patch_mistral_regex(cls, tokenizer, pretrained_model_name_or_path, *args, **kwargs):
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try:
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return original(tokenizer, pretrained_model_name_or_path, *args, **kwargs)
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except Exception as exc:
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logger.debug(
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"[mistral-regex-patch] suppressed %s for %r, returning tokenizer as-is",
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type(exc).__name__,
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pretrained_model_name_or_path,
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)
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return tokenizer
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PreTrainedTokenizerBase._patch_mistral_regex = classmethod(safe_patch_mistral_regex)
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_mistral_regex_patched = True
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logger.debug("installed _patch_mistral_regex wrapper")
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def patch_huggingface_hub_offline():
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"""Monkey-patch huggingface_hub to force offline mode."""
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try:
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@@ -215,4 +266,5 @@ def ensure_original_qwen_config_cached():
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if os.environ.get("VOICEBOX_OFFLINE_PATCH", "1") != "0":
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patch_huggingface_hub_offline()
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patch_transformers_mistral_regex()
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ensure_original_qwen_config_cached()
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