feat: Sprint 2 — TrOCR ONNX, PP-DocLayout, Model Management
D2: TrOCR ONNX export script (printed + handwritten, int8 quantization) D3: PP-DocLayout ONNX export script (download or Docker-based conversion) B3: Model Management admin page (PyTorch vs ONNX status, benchmarks, config) A4: TrOCR ONNX service with runtime routing (auto/pytorch/onnx via TROCR_BACKEND) A5: PP-DocLayout ONNX detection with OpenCV fallback (via GRAPHIC_DETECT_BACKEND) B4: Structure Detection UI toggle (OpenCV vs PP-DocLayout) with class color coding C3: TrOCR-ONNX.md documentation C4: OCR-Pipeline.md ONNX section added C5: mkdocs.yml nav updated, optimum added to requirements.txt Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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339
klausur-service/backend/tests/test_trocr_onnx.py
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klausur-service/backend/tests/test_trocr_onnx.py
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"""
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Tests for TrOCR ONNX service.
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All tests use mocking — no actual ONNX model files required.
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"""
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import os
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import pytest
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from pathlib import Path
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from unittest.mock import patch, MagicMock, PropertyMock
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _services_path():
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"""Return absolute path to the services/ directory."""
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return Path(__file__).resolve().parent.parent / "services"
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# ---------------------------------------------------------------------------
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# Test: is_onnx_available — no models on disk
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# ---------------------------------------------------------------------------
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class TestIsOnnxAvailableNoModels:
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"""When no ONNX files exist on disk, is_onnx_available must return False."""
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@patch(
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"services.trocr_onnx_service._check_onnx_runtime_available",
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return_value=True,
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)
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@patch(
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"services.trocr_onnx_service._resolve_onnx_model_dir",
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return_value=None,
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)
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def test_is_onnx_available_no_models(self, mock_resolve, mock_runtime):
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from services.trocr_onnx_service import is_onnx_available
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assert is_onnx_available(handwritten=False) is False
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assert is_onnx_available(handwritten=True) is False
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@patch(
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"services.trocr_onnx_service._check_onnx_runtime_available",
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return_value=False,
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)
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def test_is_onnx_available_no_runtime(self, mock_runtime):
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"""Even if model dirs existed, missing runtime → False."""
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from services.trocr_onnx_service import is_onnx_available
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assert is_onnx_available(handwritten=False) is False
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# ---------------------------------------------------------------------------
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# Test: get_onnx_model_status — not available
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# ---------------------------------------------------------------------------
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class TestOnnxModelStatusNotAvailable:
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"""Status dict when ONNX is not loaded."""
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@patch(
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"services.trocr_onnx_service._check_onnx_runtime_available",
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return_value=False,
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)
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@patch(
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"services.trocr_onnx_service._resolve_onnx_model_dir",
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return_value=None,
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)
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def test_onnx_model_status_not_available(self, mock_resolve, mock_runtime):
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from services.trocr_onnx_service import get_onnx_model_status
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# Clear any cached models from prior tests
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import services.trocr_onnx_service as mod
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mod._onnx_models.clear()
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mod._onnx_model_loaded_at = None
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status = get_onnx_model_status()
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assert status["backend"] == "onnx"
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assert status["runtime_available"] is False
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assert status["printed"]["available"] is False
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assert status["printed"]["loaded"] is False
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assert status["printed"]["model_dir"] is None
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assert status["handwritten"]["available"] is False
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assert status["handwritten"]["loaded"] is False
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assert status["handwritten"]["model_dir"] is None
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assert status["loaded_at"] is None
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assert status["providers"] == []
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@patch(
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"services.trocr_onnx_service._check_onnx_runtime_available",
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return_value=True,
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)
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def test_onnx_model_status_runtime_but_no_files(self, mock_runtime):
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"""Runtime installed but no model files on disk."""
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from services.trocr_onnx_service import get_onnx_model_status
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import services.trocr_onnx_service as mod
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mod._onnx_models.clear()
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mod._onnx_model_loaded_at = None
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with patch(
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"services.trocr_onnx_service._resolve_onnx_model_dir",
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return_value=None,
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), patch("services.trocr_onnx_service.onnxruntime", create=True) as mock_ort:
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# Mock onnxruntime import inside get_onnx_model_status
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mock_ort_module = MagicMock()
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mock_ort_module.get_available_providers.return_value = [
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"CPUExecutionProvider"
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]
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with patch.dict("sys.modules", {"onnxruntime": mock_ort_module}):
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status = get_onnx_model_status()
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assert status["runtime_available"] is True
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assert status["printed"]["available"] is False
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assert status["handwritten"]["available"] is False
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# ---------------------------------------------------------------------------
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# Test: path resolution logic
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# ---------------------------------------------------------------------------
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class TestOnnxModelPaths:
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"""Verify the path resolution order."""
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def test_env_var_path_takes_precedence(self, tmp_path):
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"""TROCR_ONNX_DIR env var should be checked first."""
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from services.trocr_onnx_service import _resolve_onnx_model_dir
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# Create a fake model dir with a config.json
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model_dir = tmp_path / "trocr-base-printed"
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model_dir.mkdir(parents=True)
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(model_dir / "config.json").write_text("{}")
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with patch.dict(os.environ, {"TROCR_ONNX_DIR": str(tmp_path)}):
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result = _resolve_onnx_model_dir(handwritten=False)
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assert result is not None
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assert result == model_dir
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def test_env_var_handwritten_variant(self, tmp_path):
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"""TROCR_ONNX_DIR works for handwritten variant too."""
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from services.trocr_onnx_service import _resolve_onnx_model_dir
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model_dir = tmp_path / "trocr-base-handwritten"
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model_dir.mkdir(parents=True)
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(model_dir / "encoder_model.onnx").write_bytes(b"fake")
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with patch.dict(os.environ, {"TROCR_ONNX_DIR": str(tmp_path)}):
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result = _resolve_onnx_model_dir(handwritten=True)
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assert result is not None
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assert result == model_dir
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def test_returns_none_when_no_dirs_exist(self):
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"""When none of the candidate dirs exist, return None."""
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from services.trocr_onnx_service import _resolve_onnx_model_dir
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with patch.dict(os.environ, {}, clear=True):
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# Remove TROCR_ONNX_DIR if set
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os.environ.pop("TROCR_ONNX_DIR", None)
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# The Docker and local-dev paths almost certainly don't contain
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# real ONNX models on the test machine.
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result = _resolve_onnx_model_dir(handwritten=False)
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# Could be None or a real dir if someone has models locally.
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# We just verify it doesn't raise.
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assert result is None or isinstance(result, Path)
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def test_docker_path_checked(self, tmp_path):
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"""Docker path /root/.cache/huggingface/onnx/ is in candidate list."""
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from services.trocr_onnx_service import _resolve_onnx_model_dir
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docker_path = Path("/root/.cache/huggingface/onnx/trocr-base-printed")
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# We can't create that path in tests, but we can verify the logic
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# by checking that when env var points nowhere and docker path
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# doesn't exist, the function still runs without error.
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with patch.dict(os.environ, {}, clear=True):
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os.environ.pop("TROCR_ONNX_DIR", None)
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# Just verify it doesn't crash
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_resolve_onnx_model_dir(handwritten=False)
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def test_local_dev_path_relative_to_backend(self, tmp_path):
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"""Local dev path is models/onnx/<variant>/ relative to backend dir."""
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from services.trocr_onnx_service import _resolve_onnx_model_dir
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# The backend dir is derived from __file__, so we can't easily
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# redirect it. Instead, verify the function signature and return type.
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with patch.dict(os.environ, {}, clear=True):
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os.environ.pop("TROCR_ONNX_DIR", None)
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result = _resolve_onnx_model_dir(handwritten=False)
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# May or may not find models — just verify the return type
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assert result is None or isinstance(result, Path)
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def test_dir_without_onnx_files_is_skipped(self, tmp_path):
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"""A directory that exists but has no .onnx files or config.json is skipped."""
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from services.trocr_onnx_service import _resolve_onnx_model_dir
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empty_dir = tmp_path / "trocr-base-printed"
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empty_dir.mkdir(parents=True)
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# No .onnx files, no config.json
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with patch.dict(os.environ, {"TROCR_ONNX_DIR": str(tmp_path)}):
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result = _resolve_onnx_model_dir(handwritten=False)
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# The env-var candidate exists as a dir but has no model files,
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# so it should be skipped. Result depends on whether other
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# candidate dirs have models.
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if result is not None:
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# If found elsewhere, that's fine — just not the empty dir
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assert result != empty_dir
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# ---------------------------------------------------------------------------
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# Test: fallback to PyTorch
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# ---------------------------------------------------------------------------
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class TestOnnxFallbackToPytorch:
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"""When ONNX is unavailable, the routing layer in trocr_service falls back."""
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@pytest.mark.asyncio
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async def test_onnx_fallback_to_pytorch(self):
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"""With backend='auto' and ONNX unavailable, PyTorch path is used."""
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import services.trocr_service as svc
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original_backend = svc._trocr_backend
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try:
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svc._trocr_backend = "auto"
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with patch(
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"services.trocr_service._try_onnx_ocr",
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return_value=None,
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) as mock_onnx, patch(
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"services.trocr_service._run_pytorch_ocr",
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return_value=("pytorch result", 0.9),
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) as mock_pytorch:
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text, conf = await svc.run_trocr_ocr(b"fake-image-data")
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mock_onnx.assert_called_once()
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mock_pytorch.assert_called_once()
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assert text == "pytorch result"
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assert conf == 0.9
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finally:
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svc._trocr_backend = original_backend
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@pytest.mark.asyncio
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async def test_onnx_backend_forced(self):
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"""With backend='onnx', failure raises RuntimeError."""
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import services.trocr_service as svc
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original_backend = svc._trocr_backend
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try:
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svc._trocr_backend = "onnx"
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with patch(
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"services.trocr_service._try_onnx_ocr",
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return_value=None,
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):
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with pytest.raises(RuntimeError, match="ONNX backend.*unavailable"):
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await svc.run_trocr_ocr(b"fake-image-data")
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finally:
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svc._trocr_backend = original_backend
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@pytest.mark.asyncio
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async def test_pytorch_backend_skips_onnx(self):
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"""With backend='pytorch', ONNX is never attempted."""
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import services.trocr_service as svc
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original_backend = svc._trocr_backend
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try:
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svc._trocr_backend = "pytorch"
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with patch(
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"services.trocr_service._try_onnx_ocr",
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) as mock_onnx, patch(
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"services.trocr_service._run_pytorch_ocr",
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return_value=("pytorch only", 0.85),
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) as mock_pytorch:
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text, conf = await svc.run_trocr_ocr(b"fake-image-data")
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mock_onnx.assert_not_called()
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mock_pytorch.assert_called_once()
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assert text == "pytorch only"
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finally:
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svc._trocr_backend = original_backend
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# ---------------------------------------------------------------------------
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# Test: TROCR_BACKEND env var handling
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# ---------------------------------------------------------------------------
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class TestBackendConfig:
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"""TROCR_BACKEND environment variable handling."""
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def test_default_backend_is_auto(self):
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"""Without env var, backend defaults to 'auto'."""
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import services.trocr_service as svc
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# The module reads the env var at import time; in a fresh import
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# with no TROCR_BACKEND set, it should default to "auto".
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# We test the get_active_backend function instead.
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original = svc._trocr_backend
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try:
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svc._trocr_backend = "auto"
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assert svc.get_active_backend() == "auto"
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finally:
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svc._trocr_backend = original
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def test_backend_pytorch(self):
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"""TROCR_BACKEND=pytorch is reflected in get_active_backend."""
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import services.trocr_service as svc
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original = svc._trocr_backend
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try:
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svc._trocr_backend = "pytorch"
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assert svc.get_active_backend() == "pytorch"
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finally:
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svc._trocr_backend = original
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def test_backend_onnx(self):
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"""TROCR_BACKEND=onnx is reflected in get_active_backend."""
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import services.trocr_service as svc
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original = svc._trocr_backend
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try:
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svc._trocr_backend = "onnx"
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assert svc.get_active_backend() == "onnx"
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finally:
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svc._trocr_backend = original
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def test_env_var_read_at_import(self):
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"""Module reads TROCR_BACKEND from environment."""
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# We can't easily re-import, but we can verify the variable exists
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import services.trocr_service as svc
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assert hasattr(svc, "_trocr_backend")
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assert svc._trocr_backend in ("auto", "pytorch", "onnx")
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