"""Framework-specific CUDA probes must never depend on obsolete Paddle OCR."""
import os
import sys
import types

sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import gpu  # noqa: E402


# --- gpu_available() orchestration -----------------------------------------

def _patch_probes(monkeypatch, torch, onnx, smi):
    """Stub the three existing probes and reset the lru_cache for one call."""
    monkeypatch.delenv("SNAPOTTER_GPU", raising=False)
    monkeypatch.setattr(gpu, "_try_torch_cuda", lambda: torch)
    monkeypatch.setattr(gpu, "_try_onnx_cuda", lambda: onnx)
    monkeypatch.setattr(gpu, "_nvidia_smi_gpu_name", lambda: smi)
    gpu.gpu_available.cache_clear()


def test_gpu_available_does_not_treat_hardware_presence_as_framework_support(monkeypatch):
    _patch_probes(monkeypatch, torch=False, onnx=False, smi="NVIDIA GeForce RTX 4070")
    assert gpu.gpu_available() is False


def test_gpu_module_has_no_paddle_probe():
    assert not hasattr(gpu, "_try_paddle_cuda_subprocess")


# --- Per-framework detection (torch, ctranslate2) --------------------------
#
# Torch and CTranslate2 tools must gate on their OWN framework, not the general
# gpu_available(), which can report True based on ONNX Runtime while
# torch is a CPU-only build. Consuming the shared boolean would make those tools
# route to CUDA on a device their framework cannot use.

def test_torch_gpu_available_true_when_torch_can_use_cuda(monkeypatch):
    monkeypatch.delenv("SNAPOTTER_GPU", raising=False)
    monkeypatch.setattr(gpu, "_try_torch_cuda", lambda: True)
    assert gpu.torch_gpu_available() is True


def test_torch_gpu_available_false_when_override_disables_gpu(monkeypatch):
    monkeypatch.setenv("SNAPOTTER_GPU", "0")
    monkeypatch.setattr(gpu, "_try_torch_cuda", lambda: True)
    assert gpu.torch_gpu_available() is False


def test_torch_gpu_available_false_when_torch_is_cpu_only(monkeypatch):
    # The crux: gpu_available() may be True via ONNX on a GPU box, but a
    # CPU-only torch build must report no GPU so torch tools do not touch CUDA.
    monkeypatch.delenv("SNAPOTTER_GPU", raising=False)
    monkeypatch.setattr(gpu, "_try_torch_cuda", lambda: False)
    assert gpu.torch_gpu_available() is False


def test_ctranslate2_gpu_available_true_when_cuda_device_present(monkeypatch):
    monkeypatch.delenv("SNAPOTTER_GPU", raising=False)
    fake = types.SimpleNamespace(get_cuda_device_count=lambda: 1)
    monkeypatch.setitem(sys.modules, "ctranslate2", fake)
    assert gpu.ctranslate2_gpu_available() is True


def test_ctranslate2_gpu_available_false_when_no_cuda_device(monkeypatch):
    monkeypatch.delenv("SNAPOTTER_GPU", raising=False)
    fake = types.SimpleNamespace(get_cuda_device_count=lambda: 0)
    monkeypatch.setitem(sys.modules, "ctranslate2", fake)
    assert gpu.ctranslate2_gpu_available() is False


def test_ctranslate2_gpu_available_false_when_override_disables_gpu(monkeypatch):
    monkeypatch.setenv("SNAPOTTER_GPU", "0")
    fake = types.SimpleNamespace(get_cuda_device_count=lambda: 4)
    monkeypatch.setitem(sys.modules, "ctranslate2", fake)
    assert gpu.ctranslate2_gpu_available() is False


def test_ctranslate2_gpu_available_false_when_not_installed(monkeypatch):
    # A None entry in sys.modules makes `import ctranslate2` raise ImportError,
    # which models the framework being absent (e.g. no transcription bundle).
    monkeypatch.delenv("SNAPOTTER_GPU", raising=False)
    monkeypatch.setitem(sys.modules, "ctranslate2", None)
    assert gpu.ctranslate2_gpu_available() is False