"""Interpreter-startup stub for Hugging Face Inference Endpoint containers.

Banyan Sapling is a text-only verifier: torchaudio and torchvision are never
used. torchaudio has no release matching torch 2.14.x (its final release is
2.11.0), so the container's stale compiled torchaudio extension fails to load
against upgraded torch, and transformers 5.x imports torchaudio eagerly while
registering models - crashing the worker before the custom handler runs.

Pre-importing None into sys.modules here makes `import torchaudio` raise a
clean ImportError that transformers treats as "feature unavailable". This is
the same mechanism the reference runtime uses (see inference.py: "The
text-only runtime does not require torchvision or torchaudio").

Activated by setting PYTHONPATH=/repository on the endpoint, which causes
CPython to auto-import this module at interpreter startup (gunicorn master
and workers included), before anything imports transformers.
"""
import sys

sys.modules.setdefault("torchaudio", None)
sys.modules.setdefault("torchvision", None)


def _patch_transformers_file_utils() -> None:
    """Restore transformers-4.x file_utils symbols that HF's container toolkit
    still imports (e.g. `from transformers.file_utils import is_tf_available`),
    which transformers 5.17.0 removed. Predicates answer False - correct for a
    text-only GPU container (no TF/Flax/TPU/etc.); torch resolves truthily.
    Applied via a module-level __getattr__ so ANY removed is_*_available name
    is covered, not just the ones we know about today.
    """
    try:
        import transformers.file_utils as _fu
    except Exception:
        return  # transformers not installed yet (e.g. early pip runs)
    if getattr(_fu, "_banyan_compat_shim", False):
        return
    import types as _types

    class _CompatFileUtils(_types.ModuleType):
        def __getattr__(self, name):
            if name.startswith("is_") and name.endswith("_available"):
                # torch is present (the whole point of this container);
                # everything else 5.17 removed is genuinely absent here.
                if name == "is_torch_available":
                    return lambda: True
                return lambda: False
            raise AttributeError(f"module {self.__name__!r} has no attribute {name!r}")

    _fu.__class__ = _CompatFileUtils
    _fu._banyan_compat_shim = True


def _patch_torch_determinism() -> None:
    """The model's seed_all() enables strict deterministic algorithms; the
    container's (older) torch raises on ops without deterministic CUDA kernels
    (e.g. _histc_cuda), killing requests after a successful forward pass. The
    reference numerics were validated on torch 2.14.1/H200; on this container
    we keep deterministic mode enabled but with warn_only=True so undeterministic
    ops warn instead of raising. torch is preinstalled in the container (and in
    the pre-flight venv), so importing it here is safe; if absent, skip.
    """
    try:
        import torch
    except Exception:
        return
    if getattr(torch, "_banyan_warn_only_wrap", False):
        return
    _orig = torch.use_deterministic_algorithms

    def _warn_only(mode=True, *, warn_only=False):
        _orig(bool(mode), warn_only=True)

    torch.use_deterministic_algorithms = _warn_only
    torch._banyan_warn_only_wrap = True


_patch_transformers_file_utils()
_patch_torch_determinism()