ci: add github actions (#16)

* chore: update pre-commit versions

* ci: remove old configurations

* ci: copy workflow from prototorch

* ci: run precommit for all files

* ci: add examples CPU test

* ci(test): failing example test

* ci: fix workflow definition

* ci(test): repeat failing example test

* ci: fix workflow definition

* ci(test): repeat failing example test II

* ci: fix test command

* ci: cleanup example test

* ci: remove travis badge

.codacy.yml

@@ -1,15 +0,0 @@
-# To validate the contents of your configuration file
-# run the following command in the folder where the configuration file is located:
-# codacy-analysis-cli validate-configuration --directory `pwd`
-# To analyse, run:
-# codacy-analysis-cli analyse --tool remark-lint --directory `pwd`
----
-engines:
-  pylintpython3:
-    exclude_paths:
-      - config/engines.yml
-  remark-lint:
-    exclude_paths:
-      - config/engines.yml
-exclude_paths:
-  - 'tests/**'

.codecov.yml

@@ -1,2 +0,0 @@
-comment:
-  require_changes: yes

.github/workflows/examples.yml

@@ -0,0 +1,25 @@
+# Thi workflow will install Python dependencies, run tests and lint with a single version of Python
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: examples
+
+on:
+  push:
+    paths:
+      - 'examples/**.py'
+jobs:
+  cpu:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python 3.9
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.9
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install .[all]
+    - name: Run examples
+      run: |
+        ./tests/test_examples.sh examples/

.github/workflows/pythonapp.yml

@@ -0,0 +1,73 @@
+# This workflow will install Python dependencies, run tests and lint with a single version of Python
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: tests
+
+on:
+  push:
+  pull_request:
+    branches: [ master ]
+
+jobs:
+  style:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python 3.9
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.9
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install .[all]
+    - uses: pre-commit/action@v2.0.3
+  compatibility:
+    needs: style
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.7", "3.8", "3.9"]
+        os: [ubuntu-latest, windows-latest]
+        exclude:
+        - os: windows-latest
+          python-version: "3.7"
+        - os: windows-latest
+          python-version: "3.8"
+
+    runs-on: ${{ matrix.os }}
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install .[all]
+    - name: Test with pytest
+      run: |
+        pytest
+  publish_pypi:
+    if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags')
+    needs: compatibility
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python 3.9
+      uses: actions/setup-python@v2
+      with:
+        python-version: "3.9"
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install .[all]
+        pip install wheel
+    - name: Build package
+      run: python setup.py sdist bdist_wheel
+    - name: Publish a Python distribution to PyPI
+      uses: pypa/gh-action-pypi-publish@release/v1
+      with:
+        user: __token__
+        password: ${{ secrets.PYPI_API_TOKEN }}

.pre-commit-config.yaml

@@ -3,7 +3,7 @@
 
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.0.1
+  rev: v4.1.0
   hooks:
   - id: trailing-whitespace
   - id: end-of-file-fixer
@@ -18,19 +18,19 @@ repos:
   - id: autoflake
 
 - repo: http://github.com/PyCQA/isort
-  rev: 5.8.0
+  rev: 5.10.1
   hooks:
   - id: isort
 
 - repo: https://github.com/pre-commit/mirrors-mypy
-  rev: v0.902
+  rev: v0.931
   hooks:
   - id: mypy
     files: prototorch
     additional_dependencies: [types-pkg_resources]
 
 - repo: https://github.com/pre-commit/mirrors-yapf
-  rev: v0.31.0
+  rev: v0.32.0
   hooks:
   - id: yapf
 
@@ -42,7 +42,7 @@ repos:
   - id: python-check-blanket-noqa
 
 - repo: https://github.com/asottile/pyupgrade
-  rev: v2.19.4
+  rev: v2.31.0
   hooks:
   - id: pyupgrade
 

.travis.yml

@@ -1,44 +0,0 @@
-dist: bionic
-sudo: false
-language: python
-python:
-  - 3.9
-  - 3.8
-  - 3.7
-  - 3.6
-cache:
-  directories:
-  - "$HOME/.cache/pip"
-  - "./tests/artifacts"
-  - "$HOME/datasets"
-install:
-- pip install git+git://github.com/si-cim/prototorch@dev --progress-bar off
-- pip install .[all] --progress-bar off
-script:
-- coverage run -m pytest
-- ./tests/test_examples.sh examples/
-after_success:
-- bash <(curl -s https://codecov.io/bash)
-
-# Publish on PyPI
-jobs:
-  include:
-    - stage: build
-      python: 3.9
-      script: echo "Starting Pypi build"
-      deploy:
-        provider: pypi
-        username: __token__
-        distributions: "sdist bdist_wheel"
-        password:
-          secure: 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
-        on:
-          tags: true
-          skip_existing: true
-
-# The password is encrypted with:
-# `cd prototorch && travis encrypt your-pypi-api-token --add deploy.password`
-# See https://docs.travis-ci.com/user/deployment/pypi and
-# https://github.com/travis-ci/travis.rb#installation
-# for more details
-# Note: The encrypt command does not work well in ZSH.

README.md

@@ -1,6 +1,5 @@
 # ProtoTorch Models
 
-[![Build Status](https://api.travis-ci.com/si-cim/prototorch_models.svg?branch=main)](https://travis-ci.com/github/si-cim/prototorch_models)
 [![GitHub tag (latest by date)](https://img.shields.io/github/v/tag/si-cim/prototorch_models?color=yellow&label=version)](https://github.com/si-cim/prototorch_models/releases)
 [![PyPI](https://img.shields.io/pypi/v/prototorch_models)](https://pypi.org/project/prototorch_models/)
 [![GitHub license](https://img.shields.io/github/license/si-cim/prototorch_models)](https://github.com/si-cim/prototorch_models/blob/master/LICENSE)

examples/ksom_colors.py

@@ -10,6 +10,7 @@ from prototorch.utils.colors import hex_to_rgb
 
 
 class Vis2DColorSOM(pl.Callback):
+
     def __init__(self, data, title="ColorSOMe", pause_time=0.1):
         super().__init__()
         self.title = title

examples/lvqmln_iris.py

@@ -8,6 +8,7 @@ import torch
 
 
 class Backbone(torch.nn.Module):
+
     def __init__(self, input_size=4, hidden_size=10, latent_size=2):
         super().__init__()
         self.input_size = input_size

examples/siamese_glvq_iris.py

@@ -8,6 +8,7 @@ import torch
 
 
 class Backbone(torch.nn.Module):
+
     def __init__(self, input_size=4, hidden_size=10, latent_size=2):
         super().__init__()
         self.input_size = input_size

examples/siamese_gtlvq_iris.py

@@ -8,6 +8,7 @@ import torch
 
 
 class Backbone(torch.nn.Module):
+
     def __init__(self, input_size=4, hidden_size=10, latent_size=2):
         super().__init__()
         self.input_size = input_size

prototorch/models/__init__.py

@@ -19,9 +19,23 @@ from .glvq import (
     SiameseGTLVQ,
 )
 from .knn import KNN
-from .lvq import LVQ1, LVQ21, MedianLVQ
+from .lvq import (
-from .probabilistic import CELVQ, PLVQ, RSLVQ, SLVQ
+    LVQ1,
-from .unsupervised import GrowingNeuralGas, HeskesSOM, KohonenSOM, NeuralGas
+    LVQ21,
+    MedianLVQ,
+)
+from .probabilistic import (
+    CELVQ,
+    PLVQ,
+    RSLVQ,
+    SLVQ,
+)
+from .unsupervised import (
+    GrowingNeuralGas,
+    HeskesSOM,
+    KohonenSOM,
+    NeuralGas,
+)
 from .vis import *
 
 __version__ = "0.3.0"

prototorch/models/abstract.py

@@ -14,6 +14,7 @@ from ..nn.wrappers import LambdaLayer
 
 class ProtoTorchBolt(pl.LightningModule):
     """All ProtoTorch models are ProtoTorch Bolts."""
+
     def __init__(self, hparams, **kwargs):
         super().__init__()
 
@@ -52,6 +53,7 @@ class ProtoTorchBolt(pl.LightningModule):
 
 
 class PrototypeModel(ProtoTorchBolt):
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -81,6 +83,7 @@ class PrototypeModel(ProtoTorchBolt):
 
 
 class UnsupervisedPrototypeModel(PrototypeModel):
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -103,6 +106,7 @@ class UnsupervisedPrototypeModel(PrototypeModel):
 
 
 class SupervisedPrototypeModel(PrototypeModel):
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -178,6 +182,7 @@ class ProtoTorchMixin(object):
 
 class NonGradientMixin(ProtoTorchMixin):
     """Mixin for custom non-gradient optimization."""
+
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self.automatic_optimization = False
@@ -188,6 +193,7 @@ class NonGradientMixin(ProtoTorchMixin):
 
 class ImagePrototypesMixin(ProtoTorchMixin):
     """Mixin for models with image prototypes."""
+
     def on_train_batch_end(self, outputs, batch, batch_idx, dataloader_idx):
         """Constrain the components to the range [0, 1] by clamping after updates."""
         self.proto_layer.components.data.clamp_(0.0, 1.0)

prototorch/models/callbacks.py

@@ -11,6 +11,7 @@ from .extras import ConnectionTopology
 
 
 class PruneLoserPrototypes(pl.Callback):
+
     def __init__(self,
                  threshold=0.01,
                  idle_epochs=10,
@@ -67,6 +68,7 @@ class PruneLoserPrototypes(pl.Callback):
 
 
 class PrototypeConvergence(pl.Callback):
+
     def __init__(self, min_delta=0.01, idle_epochs=10, verbose=False):
         self.min_delta = min_delta
         self.idle_epochs = idle_epochs  # epochs to wait
@@ -89,6 +91,7 @@ class GNGCallback(pl.Callback):
     Based on "A Growing Neural Gas Network Learns Topologies" by Bernd Fritzke.
 
     """
+
     def __init__(self, reduction=0.1, freq=10):
         self.reduction = reduction
         self.freq = freq

prototorch/models/cbc.py

@@ -13,6 +13,7 @@ from .glvq import SiameseGLVQ
 
 class CBC(SiameseGLVQ):
     """Classification-By-Components."""
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 

prototorch/models/extras.py

@@ -54,6 +54,7 @@ def ltangent_distance(x, y, omegas):
 
 
 class GaussianPrior(torch.nn.Module):
+
     def __init__(self, variance):
         super().__init__()
         self.variance = variance
@@ -63,6 +64,7 @@ class GaussianPrior(torch.nn.Module):
 
 
 class RankScaledGaussianPrior(torch.nn.Module):
+
     def __init__(self, lambd):
         super().__init__()
         self.lambd = lambd
@@ -72,6 +74,7 @@ class RankScaledGaussianPrior(torch.nn.Module):
 
 
 class ConnectionTopology(torch.nn.Module):
+
     def __init__(self, agelimit, num_prototypes):
         super().__init__()
         self.agelimit = agelimit

prototorch/models/glvq.py

@@ -4,9 +4,17 @@ import torch
 from torch.nn.parameter import Parameter
 
 from ..core.competitions import wtac
-from ..core.distances import lomega_distance, omega_distance, squared_euclidean_distance
+from ..core.distances import (
+    lomega_distance,
+    omega_distance,
+    squared_euclidean_distance,
+)
 from ..core.initializers import EyeTransformInitializer
-from ..core.losses import GLVQLoss, lvq1_loss, lvq21_loss
+from ..core.losses import (
+    GLVQLoss,
+    lvq1_loss,
+    lvq21_loss,
+)
 from ..core.transforms import LinearTransform
 from ..nn.wrappers import LambdaLayer, LossLayer
 from .abstract import ImagePrototypesMixin, SupervisedPrototypeModel
@@ -15,6 +23,7 @@ from .extras import ltangent_distance, orthogonalization
 
 class GLVQ(SupervisedPrototypeModel):
     """Generalized Learning Vector Quantization."""
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -99,6 +108,7 @@ class SiameseGLVQ(GLVQ):
     transformation pipeline are only learned from the inputs.
 
     """
+
     def __init__(self,
                  hparams,
                  backbone=torch.nn.Identity(),
@@ -165,6 +175,7 @@ class LVQMLN(SiameseGLVQ):
     rather in the embedding space.
 
     """
+
     def compute_distances(self, x):
         latent_protos, _ = self.proto_layer()
         latent_x = self.backbone(x)
@@ -180,6 +191,7 @@ class GRLVQ(SiameseGLVQ):
     TODO Make a RelevanceLayer. `bb_lr` is ignored otherwise.
 
     """
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -205,6 +217,7 @@ class SiameseGMLVQ(SiameseGLVQ):
     Implemented as a Siamese network with a linear transformation backbone.
 
     """
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -235,6 +248,7 @@ class GMLVQ(GLVQ):
     function. This makes it easier to implement a localized variant.
 
     """
+
     def __init__(self, hparams, **kwargs):
         distance_fn = kwargs.pop("distance_fn", omega_distance)
         super().__init__(hparams, distance_fn=distance_fn, **kwargs)
@@ -269,6 +283,7 @@ class GMLVQ(GLVQ):
 
 class LGMLVQ(GMLVQ):
     """Localized and Generalized Matrix Learning Vector Quantization."""
+
     def __init__(self, hparams, **kwargs):
         distance_fn = kwargs.pop("distance_fn", lomega_distance)
         super().__init__(hparams, distance_fn=distance_fn, **kwargs)
@@ -285,6 +300,7 @@ class LGMLVQ(GMLVQ):
 
 class GTLVQ(LGMLVQ):
     """Localized and Generalized Tangent Learning Vector Quantization."""
+
     def __init__(self, hparams, **kwargs):
         distance_fn = kwargs.pop("distance_fn", ltangent_distance)
         super().__init__(hparams, distance_fn=distance_fn, **kwargs)
@@ -323,6 +339,7 @@ class SiameseGTLVQ(SiameseGLVQ, GTLVQ):
 
 class GLVQ1(GLVQ):
     """Generalized Learning Vector Quantization 1."""
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
         self.loss = LossLayer(lvq1_loss)
@@ -331,6 +348,7 @@ class GLVQ1(GLVQ):
 
 class GLVQ21(GLVQ):
     """Generalized Learning Vector Quantization 2.1."""
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
         self.loss = LossLayer(lvq21_loss)
@@ -362,6 +380,7 @@ class ImageGTLVQ(ImagePrototypesMixin, GTLVQ):
     after updates.
 
     """
+
     def on_train_batch_end(self, outputs, batch, batch_idx, dataloader_idx):
         """Constrain the components to the range [0, 1] by clamping after updates."""
         self.proto_layer.components.data.clamp_(0.0, 1.0)

prototorch/models/knn.py

@@ -4,13 +4,17 @@ import warnings
 
 from ..core.competitions import KNNC
 from ..core.components import LabeledComponents
-from ..core.initializers import LiteralCompInitializer, LiteralLabelsInitializer
+from ..core.initializers import (
+    LiteralCompInitializer,
+    LiteralLabelsInitializer,
+)
 from ..utils.utils import parse_data_arg
 from .abstract import SupervisedPrototypeModel
 
 
 class KNN(SupervisedPrototypeModel):
     """K-Nearest-Neighbors classification algorithm."""
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 

prototorch/models/lvq.py

@@ -9,6 +9,7 @@ from .glvq import GLVQ
 
 class LVQ1(NonGradientMixin, GLVQ):
     """Learning Vector Quantization 1."""
+
     def training_step(self, train_batch, batch_idx, optimizer_idx=None):
         protos, plables = self.proto_layer()
         x, y = train_batch
@@ -38,6 +39,7 @@ class LVQ1(NonGradientMixin, GLVQ):
 
 class LVQ21(NonGradientMixin, GLVQ):
     """Learning Vector Quantization 2.1."""
+
     def training_step(self, train_batch, batch_idx, optimizer_idx=None):
         protos, plabels = self.proto_layer()
 
@@ -70,6 +72,7 @@ class MedianLVQ(NonGradientMixin, GLVQ):
     # TODO Avoid computing distances over and over
 
     """
+
     def __init__(self, hparams, verbose=True, **kwargs):
         self.verbose = verbose
         super().__init__(hparams, **kwargs)

prototorch/models/probabilistic.py

@@ -11,6 +11,7 @@ from .glvq import GLVQ, SiameseGMLVQ
 
 class CELVQ(GLVQ):
     """Cross-Entropy Learning Vector Quantization."""
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -29,6 +30,7 @@ class CELVQ(GLVQ):
 
 
 class ProbabilisticLVQ(GLVQ):
+
     def __init__(self, hparams, rejection_confidence=0.0, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -62,6 +64,7 @@ class ProbabilisticLVQ(GLVQ):
 
 class SLVQ(ProbabilisticLVQ):
     """Soft Learning Vector Quantization."""
+
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self.loss = LossLayer(nllr_loss)
@@ -70,6 +73,7 @@ class SLVQ(ProbabilisticLVQ):
 
 class RSLVQ(ProbabilisticLVQ):
     """Robust Soft Learning Vector Quantization."""
+
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self.loss = LossLayer(rslvq_loss)
@@ -81,6 +85,7 @@ class PLVQ(ProbabilisticLVQ, SiameseGMLVQ):
 
     TODO: Use Backbone LVQ instead
     """
+
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self.conditional_distribution = RankScaledGaussianPrior(

prototorch/models/unsupervised.py

@@ -18,6 +18,7 @@ class KohonenSOM(NonGradientMixin, UnsupervisedPrototypeModel):
     TODO Allow non-2D grids
 
     """
+
     def __init__(self, hparams, **kwargs):
         h, w = hparams.get("shape")
         # Ignore `num_prototypes`
@@ -69,6 +70,7 @@ class KohonenSOM(NonGradientMixin, UnsupervisedPrototypeModel):
 
 
 class HeskesSOM(UnsupervisedPrototypeModel):
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -78,6 +80,7 @@ class HeskesSOM(UnsupervisedPrototypeModel):
 
 
 class NeuralGas(UnsupervisedPrototypeModel):
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 
@@ -110,6 +113,7 @@ class NeuralGas(UnsupervisedPrototypeModel):
 
 
 class GrowingNeuralGas(NeuralGas):
+
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
 

prototorch/models/vis.py

@@ -11,6 +11,7 @@ from ..utils.utils import mesh2d
 
 
 class Vis2DAbstract(pl.Callback):
+
     def __init__(self,
                  data,
                  title="Prototype Visualization",
@@ -118,6 +119,7 @@ class Vis2DAbstract(pl.Callback):
 
 
 class VisGLVQ2D(Vis2DAbstract):
+
     def on_epoch_end(self, trainer, pl_module):
         if not self.precheck(trainer):
             return True
@@ -141,6 +143,7 @@ class VisGLVQ2D(Vis2DAbstract):
 
 
 class VisSiameseGLVQ2D(Vis2DAbstract):
+
     def __init__(self, *args, map_protos=True, **kwargs):
         super().__init__(*args, **kwargs)
         self.map_protos = map_protos
@@ -179,6 +182,7 @@ class VisSiameseGLVQ2D(Vis2DAbstract):
 
 
 class VisGMLVQ2D(Vis2DAbstract):
+
     def __init__(self, *args, ev_proj=True, **kwargs):
         super().__init__(*args, **kwargs)
         self.ev_proj = ev_proj
@@ -212,6 +216,7 @@ class VisGMLVQ2D(Vis2DAbstract):
 
 
 class VisCBC2D(Vis2DAbstract):
+
     def on_epoch_end(self, trainer, pl_module):
         if not self.precheck(trainer):
             return True
@@ -235,6 +240,7 @@ class VisCBC2D(Vis2DAbstract):
 
 
 class VisNG2D(Vis2DAbstract):
+
     def on_epoch_end(self, trainer, pl_module):
         if not self.precheck(trainer):
             return True
@@ -262,6 +268,7 @@ class VisNG2D(Vis2DAbstract):
 
 
 class VisImgComp(Vis2DAbstract):
+
     def __init__(self,
                  *args,
                  random_data=0,

setup.cfg

@@ -1,8 +1,23 @@
-[isort]
-profile = hug
-src_paths = isort, test
-
 [yapf]
 based_on_style = pep8
 spaces_before_comment = 2
 split_before_logical_operator = true
+
+[pylint]
+disable =
+	too-many-arguments,
+	too-few-public-methods,
+	fixme,
+
+
+[pycodestyle]
+max-line-length = 79
+
+[isort]
+profile = hug
+src_paths = isort, test
+multi_line_output = 3
+include_trailing_comma = True
+force_grid_wrap = 3
+use_parentheses = True
+line_length = 79

tests/test_.py

@@ -4,6 +4,7 @@ import unittest
 
 
 class TestDummy(unittest.TestCase):
+
     def setUp(self):
         pass