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chore: bump version, add changelog
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CHANGELOG.md

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<a id='changelog-0.1.15'></a>
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<a id='changelog-0.1.17'></a>
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# 0.1.17 — 2022-12-29
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## Features
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- Add transformer modules
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- Add exact, slice, and memory efficient (xformers) self attention computations
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- Add transformers modules to `Decoder` modules
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- Add common transformer mlp activation functions: star-relu, geglu, approximate-gelu.
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- Add Linformer self-attention mechanism.
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- Add support for model intialization from yaml-file in `MultiTaskUnet`.
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- Add a new cross-attention long-skip module. Works with `long_skip='cross-attn'`
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## Refactor
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- Added more verbose error messages for the abstract wrapper-modules in `modules.base_modules`
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- Added more verbose error catching for xformers.ops.memory_efficient_attention.
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<a id='changelog-0.1.16'></a>
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# 0.1.16 — 2022-12-14
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cellseg_models_pytorch/__init__.py

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from . import inference, models, utils
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from .models import CellPoseUnet, HoverNet, StarDistUnet
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__version__ = "0.1.16"
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__version__ = "0.1.17"
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submodules = ["utils", "models", "inference"]
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__all__ = [
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"__version__",

changelog.d/20221221_155406_oskari.lehtonen.md

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changelog.d/20221222_110850_oskari.lehtonen.md

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changelog.d/20221223_131600_oskari.lehtonen.md

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changelog.d/20221229_130852_oskari.lehtonen.md

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pyproject.toml

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[tool.poetry]
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name = "cellseg_models_pytorch"
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version = "0.1.16"
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version = "0.1.17"
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description = "Python library for 2D cell/nuclei instance segmentation models written with PyTorch."
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authors = ["Okunator <oskari.lehtonen@helsinki.fi>"]
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license = "MIT"

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