feat: switch from poetry to micromamba

.gitignore

@@ -1,8 +1,6 @@
-data/
-dataset*/
-*.parquet
-.venv/
-lightning_logs/
-__pycache__/
+dataset*
+lightning_logs
+__pycache__
 
 *.jpg
+*.png

env.yml

@@ -0,0 +1,34 @@
+name: qcav
+
+channels:
+  - nodefaults
+  - pytorch
+  - nvidia
+  - conda-forge
+
+dependencies:
+  # basic python
+  - rich
+  # science
+  - numpy
+  - scipy
+  - opencv
+  # pytorch
+  - pytorch
+  - torchvision
+  - torchaudio
+  - pytorch-cuda=11.8
+  - pytorch-lightning
+  # deep learning libraries
+  - transformers
+  - datasets
+  - timm
+  # dev tools
+  - ruff
+  - isort
+  - mypy
+  - pre-commit
+  # logging
+  - tensorboard
+  # visualization
+  - matplotlib

poetry.toml

@@ -1,3 +0,0 @@
-[virtualenvs]
-create = true
-in-project = true

pyproject.toml

@@ -1,58 +1,6 @@
-[tool.poetry]
-authors = ["Laurent Fainsin <laurentfainsin@protonmail.com>"]
-description = ""
-name = "label-studio"
-version = "1.0.0"
-
-[tool.poetry.dependencies]
-datasets = "^2.9.0"
-fastapi = "0.86.0"
-jsonargparse = {extras = ["signatures"], version = "^4.20.0"}
-lightning = "1.9.1"
-matplotlib = "^3.7.0"
-numpy = "^1.24.2"
-opencv-python = "^4.7.0.72"
-opencv-python-headless = "^4.7.0.72"
-python = ">=3.8,<3.12"
-rich = "^13.3.1"
-scipy = "^1.10.0"
-timm = "^0.6.12"
-torch = "^1.13.1"
-transformers = "^4.26.1"
-
-[tool.poetry.group.notebooks]
-optional = true
-
-[tool.poetry.group.notebooks.dependencies]
-ipykernel = "^6.20.2"
-ipywidgets = "^8.0.4"
-jupyter = "^1.0.0"
-matplotlib = "^3.6.3"
-
-[tool.poetry.group.dev.dependencies]
-Flake8-pyproject = "^1.1.0"
-bandit = "^1.7.4"
-black = "^22.8.0"
-flake8 = "^5.0.4"
-flake8-docstrings = "^1.6.0"
-isort = "^5.10.1"
-mypy = "^0.971"
-pre-commit = "^2.20.0"
-tensorboard = "^2.12.0"
-torchtyping = "^0.1.4"
-torch-tb-profiler = "^0.4.1"
-
-[build-system]
-build-backend = "poetry.core.masonry.api"
-requires = ["poetry-core"]
-
-[tool.flake8]
-# rules ignored
-extend-ignore = ["W503", "D401", "D100", "D104"]
-per-file-ignores = ["__init__.py:F401"]
-# black
-ignore = "E203"
-max-line-length = 120
+[tool.ruff]
+line-length = 120
+select = ["E", "F", "I"]
 
 [tool.black]
 exclude = '''

src/datamodule.py

@@ -1,9 +1,8 @@
 import datasets
 import torch
-from lightning.pytorch import LightningDataModule
-from lightning.pytorch.trainer.supporters import CombinedLoader
+from pytorch_lightning import LightningDataModule
+from pytorch_lightning.utilities import CombinedLoader
 from torch.utils.data import DataLoader
-from torchvision.datasets import ImageFolder
 from torchvision.transforms import AugMix
 from transformers import DetrFeatureExtractor
 

src/main.py

@@ -1,12 +1,11 @@
-from lightning.pytorch.callbacks import (
+from datamodule import DETRDataModule
+from module import DETR
+from pytorch_lightning.callbacks import (
     ModelCheckpoint,
     RichModelSummary,
     RichProgressBar,
 )
-from lightning.pytorch.cli import LightningCLI
-
-from datamodule import DETRDataModule
-from module import DETR
+from pytorch_lightning.cli import LightningCLI
 
 
 class MyLightningCLI(LightningCLI):

src/module.py

@@ -1,6 +1,6 @@
 import torch
-from lightning.pytorch import LightningModule
 from PIL import ImageDraw
+from pytorch_lightning import LightningModule
 from transformers import (
     DetrForObjectDetection,
     get_cosine_with_hard_restarts_schedule_with_warmup,

src/spheres_predict.py

@@ -74,8 +74,6 @@ class SpherePredict(datasets.GeneratorBasedBuilder):
 
 
 if __name__ == "__main__":
-    from PIL import ImageDraw
-
     # load dataset
     dataset = datasets.load_dataset("src/spheres_predict.py", split="train")