mirror of
https://github.com/azaion/ai-training.git
synced 2026-04-22 05:26:36 +00:00
Oleksandr Bezdieniezhnykh
243b69656b
- Modified `.gitignore` to reflect the new path for test results. - Updated `docker-compose.test.yml` to mount the correct test results directory. - Adjusted `Dockerfile.test` to set the `PYTHONPATH` and ensure test results are saved in the updated location. - Added `boto3` and `netron` to `requirements-test.txt` to support new functionalities. - Updated `pytest.ini` to include the new `pythonpath` for test discovery. These changes streamline the testing process and ensure compatibility with the updated directory structure.
65 lines
1.5 KiB
Python
65 lines
1.5 KiB
Python
import shutil
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import time
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from os import path as osp
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from pathlib import Path
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import pytest
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import constants as c_mod
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def _prepare_form_dataset(
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monkeypatch,
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tmp_path,
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constants_patch,
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fixture_images_dir,
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fixture_labels_dir,
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count,
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corrupt_stems,
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):
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constants_patch(tmp_path)
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import train
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proc_img = Path(c_mod.config.processed_images_dir)
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proc_lbl = Path(c_mod.config.processed_labels_dir)
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proc_img.mkdir(parents=True, exist_ok=True)
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proc_lbl.mkdir(parents=True, exist_ok=True)
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imgs = sorted(fixture_images_dir.glob("*.jpg"))[:count]
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for p in imgs:
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stem = p.stem
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shutil.copy2(fixture_images_dir / f"{stem}.jpg", proc_img / f"{stem}.jpg")
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dst = proc_lbl / f"{stem}.txt"
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shutil.copy2(fixture_labels_dir / f"{stem}.txt", dst)
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if stem in corrupt_stems:
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dst.write_text("0 1.5 0.5 0.1 0.1\n", encoding="utf-8")
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today_ds = osp.join(c_mod.config.datasets_dir, train.today_folder)
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return train, today_ds
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@pytest.mark.performance
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def test_pt_dsf_01_dataset_formation_under_thirty_seconds(
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monkeypatch,
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tmp_path,
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constants_patch,
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fixture_images_dir,
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fixture_labels_dir,
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):
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# Arrange
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train, today_ds = _prepare_form_dataset(
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monkeypatch,
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tmp_path,
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constants_patch,
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fixture_images_dir,
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fixture_labels_dir,
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100,
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set(),
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)
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# Act
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t0 = time.perf_counter()
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train.form_dataset()
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elapsed = time.perf_counter() - t0
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# Assert
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assert elapsed <= 30.0
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