Rework of Sklearn Metrics

.circleci/config.yml

@@ -64,8 +64,12 @@ references:
      name: Make Documentation
      command: |
        # First run the same pipeline as Read-The-Docs
-       sudo apt-get update && sudo apt-get install -y cmake
-       sudo pip install -r docs/requirements.txt
+       # apt-get update && apt-get install -y cmake
+       # using: https://hub.docker.com/r/readthedocs/build
+       # we need to use py3.7 ot higher becase of an issue with metaclass inheritence
+       pyenv global 3.7.3
+       python --version
+       pip install -r docs/requirements.txt
        cd docs; make clean; make html --debug --jobs 2 SPHINXOPTS="-W"
 
   test_docs: &test_docs
@@ -81,7 +85,7 @@ jobs:
 
   Build-Docs:
     docker:
-      - image: circleci/python:3.7
+      - image: readthedocs/build:latest
     steps:
       - checkout
       - *make_docs

.github/workflows/ci-testing.yml

@@ -68,9 +68,9 @@ jobs:
     - name: Set min. dependencies
       if: matrix.requires == 'minimal'
       run: |
-        python -c "req = open('requirements.txt').read().replace('>', '=') ; open('requirements.txt', 'w').write(req)"
-        python -c "req = open('requirements-extra.txt').read().replace('>', '=') ; open('requirements-extra.txt', 'w').write(req)"
-        python -c "req = open('tests/requirements-devel.txt').read().replace('>', '=') ; open('tests/requirements-devel.txt', 'w').write(req)"
+        python -c "req = open('requirements.txt').read().replace('>=', '==') ; open('requirements.txt', 'w').write(req)"
+        python -c "req = open('requirements-extra.txt').read().replace('>=', '==') ; open('requirements-extra.txt', 'w').write(req)"
+        python -c "req = open('tests/requirements-devel.txt').read().replace('>=', '==') ; open('tests/requirements-devel.txt', 'w').write(req)"
 
     # Note: This uses an internal pip API and may not always work
     # https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow

CHANGELOG.md

@@ -4,7 +4,6 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
-
 ## [unreleased] - YYYY-MM-DD
 
 ### Added
@@ -23,7 +22,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 ### Added
 
 - Remove explicit flush from tensorboard logger ([#2126](https://github.com/PyTorchLightning/pytorch-lightning/pull/2126))
-- Add Metric Base Classes ([#1326](https://github.com/PyTorchLightning/pytorch-lightning/pull/1326), [#1877](https://github.com/PyTorchLightning/pytorch-lightning/pull/1877))
+- Added metric Base classes ([#1326](https://github.com/PyTorchLightning/pytorch-lightning/pull/1326), [#1877](https://github.com/PyTorchLightning/pytorch-lightning/pull/1877))
+- Added Sklearn metrics classes ([#1327](https://github.com/PyTorchLightning/pytorch-lightning/pull/1327))
 - Added type hints in `Trainer.fit()` and `Trainer.test()` to reflect that also a list of dataloaders can be passed in ([#1723](https://github.com/PyTorchLightning/pytorch-lightning/pull/1723))
 - Allow dataloaders without sampler field present ([#1907](https://github.com/PyTorchLightning/pytorch-lightning/pull/1907))
 - Added option `save_last` to save the model at the end of every epoch in `ModelCheckpoint` [(#1908)](https://github.com/PyTorchLightning/pytorch-lightning/pull/1908)

docs/source/conf.py

@@ -90,6 +90,7 @@
     'sphinx.ext.linkcode',
     'sphinx.ext.autosummary',
     'sphinx.ext.napoleon',
+    'sphinx.ext.imgmath',
     'recommonmark',
     'sphinx.ext.autosectionlabel',
     # 'm2r',

environment.yml

@@ -26,6 +26,10 @@ dependencies:
     - autopep8
     - check-manifest
     - twine==1.13.0
+    - pillow<7.0.0
+    - scipy>=0.13.3
+    - scikit-learn>=0.20.0
+
 
     - pip:
         - test-tube>=0.7.5

pl_examples/domain_templates/computer_vision_fine_tuning.py

@@ -27,6 +27,8 @@
 from tempfile import TemporaryDirectory
 from typing import Optional, Generator, Union
 
+from torch.nn import Module
+
 import pytorch_lightning as pl
 import torch
 import torch.nn.functional as F
@@ -47,7 +49,7 @@
 #  --- Utility functions ---
 
 
-def _make_trainable(module: torch.nn.Module) -> None:
+def _make_trainable(module: Module) -> None:
     """Unfreezes a given module.
 
     Args:
@@ -58,7 +60,7 @@ def _make_trainable(module: torch.nn.Module) -> None:
     module.train()
 
 
-def _recursive_freeze(module: torch.nn.Module,
+def _recursive_freeze(module: Module,
                       train_bn: bool = True) -> None:
     """Freezes the layers of a given module.
 
@@ -80,7 +82,7 @@ def _recursive_freeze(module: torch.nn.Module,
             _recursive_freeze(module=child, train_bn=train_bn)
 
 
-def freeze(module: torch.nn.Module,
+def freeze(module: Module,
            n: Optional[int] = None,
            train_bn: bool = True) -> None:
     """Freezes the layers up to index n (if n is not None).
@@ -101,7 +103,7 @@ def freeze(module: torch.nn.Module,
         _make_trainable(module=child)
 
 
-def filter_params(module: torch.nn.Module,
+def filter_params(module: Module,
                   train_bn: bool = True) -> Generator:
     """Yields the trainable parameters of a given module.
 
@@ -124,7 +126,7 @@ def filter_params(module: torch.nn.Module,
                 yield param
 
 
-def _unfreeze_and_add_param_group(module: torch.nn.Module,
+def _unfreeze_and_add_param_group(module: Module,
                                   optimizer: Optimizer,
                                   lr: Optional[float] = None,
                                   train_bn: bool = True):

pytorch_lightning/core/grads.py

@@ -4,9 +4,10 @@
 from typing import Dict, Union
 
 import torch
+from torch.nn import Module
 
 
-class GradInformation(torch.nn.Module):
+class GradInformation(Module):
 
     def grad_norm(self, norm_type: Union[float, int, str]) -> Dict[str, float]:
         """Compute each parameter's gradient's norm and their overall norm.

pytorch_lightning/core/hooks.py

@@ -2,6 +2,7 @@
 
 import torch
 from torch import Tensor
+from torch.nn import Module
 from torch.optim.optimizer import Optimizer
 from pytorch_lightning.utilities import move_data_to_device
 
@@ -14,7 +15,7 @@
     APEX_AVAILABLE = True
 
 
-class ModelHooks(torch.nn.Module):
+class ModelHooks(Module):
 
     # TODO: remove in v0.9.0
     def on_sanity_check_start(self):

pytorch_lightning/metrics/__init__.py

@@ -22,3 +22,9 @@
 
 
 """
+
+from pytorch_lightning.metrics.metric import Metric, TensorMetric, NumpyMetric
+from pytorch_lightning.metrics.sklearn import (
+    SklearnMetric, Accuracy, AveragePrecision, AUC, ConfusionMatrix, F1, FBeta,
+    Precision, Recall, PrecisionRecallCurve, ROC, AUROC)
+from pytorch_lightning.metrics.converters import numpy_metric, tensor_metric

pytorch_lightning/metrics/metric.py

@@ -1,8 +1,9 @@
 from abc import ABC, abstractmethod
-from typing import Any, Optional, Union
+from typing import Any, Optional
 
 import torch
 import torch.distributed
+from torch.nn import Module
 
 from pytorch_lightning.metrics.converters import tensor_metric, numpy_metric
 from pytorch_lightning.utilities.apply_func import apply_to_collection
@@ -11,7 +12,7 @@
 __all__ = ['Metric', 'TensorMetric', 'NumpyMetric']
 
 
-class Metric(DeviceDtypeModuleMixin, torch.nn.Module, ABC):
+class Metric(ABC, DeviceDtypeModuleMixin, Module):
     """
     Abstract base class for metric implementation.