Merge branch 'master' into t_docs

Author: williamFalcon

.drone.yml

@@ -32,6 +32,8 @@ steps:
     - pip --version
     - nvidia-smi
     - pip install -r ./requirements/devel.txt --upgrade-strategy only-if-needed -v --no-cache-dir
+    # when Image has defined CUDa version we can switch to this package spec "nvidia-dali-cuda${CUDA_VERSION%%.*}0"
+    - pip install --extra-index-url https://developer.download.nvidia.com/compute/redist nvidia-dali-cuda100 --upgrade-strategy only-if-needed
     - pip list
     - coverage run --source pytorch_lightning -m pytest pytorch_lightning tests -v --color=yes --durations=25 # --flake8
     - python -m pytest benchmarks pl_examples -v --color=yes --maxfail=2 --durations=0 # --flake8

.github/PULL_REQUEST_TEMPLATE.md

@@ -4,6 +4,8 @@
 Please include a summary of the change and which issue is fixed.
  Please also include relevant motivation and context.
  List any dependencies that are required for this change.
+
+If we didn't discuss your PR in Github issues there's a high chance it will not be merged.
 -->
 
 Fixes # (issue)
@@ -20,10 +22,14 @@ Fixes # (issue)
 <!-- For CHANGELOG separate each item in unreleased section by a blank line to reduce collisions -->
 
 ## PR review
- - [ ] Is this pull request ready for review? (if not, please submit in draft mode)
+Anyone in the community is free to review the PR once the tests have passed.
+Before you start reviewing make sure you have read [Review guidelines](https://github.com/PyTorchLightning/pytorch-lightning/wiki/Review-guidelines). In in short, see following bullet-list:  
 
-Anyone in the community is free to review the PR once the tests have passed.    
-If we didn't discuss your PR in Github issues there's a high chance it will not be merged.
+ - [ ] Is this pull request ready for review? (if not, please submit in draft mode)
+ - [ ] Check that all items from **Before submitting** are resolved
+ - [ ] Make sure the title is self explanatory and the description concisely explains the PR
+ - [ ] Add labels and milestones (and optionally projects) to the PR so it can be classified; _Bugfixes should be including in bug-fix release milestones (m.f.X) and features should be included in (m.X.b) releases._
+ 
 
 ## Did you have fun?
 Make sure you had fun coding 🙃

.github/workflows/nightly.yml

@@ -29,7 +29,7 @@ jobs:
 
     # We do this, since failures on test.pypi aren't that bad
     - name: Publish to Test PyPI
-      uses: pypa/gh-action-pypi-publish@v1
+      uses: pypa/gh-action-pypi-publish@v1.4.1
       with:
         user: __token__
         password: ${{ secrets.test_pypi_password }}

.github/workflows/pypi-release.yml

@@ -30,7 +30,7 @@ jobs:
     # We do this, since failures on test.pypi aren't that bad
     - name: Publish to Test PyPI
       if: startsWith(github.event.ref, 'refs/tags') || github.event_name == 'release'
-      uses: pypa/gh-action-pypi-publish@v1
+      uses: pypa/gh-action-pypi-publish@v1.4.1
       with:
         user: __token__
         password: ${{ secrets.test_pypi_password }}
@@ -39,7 +39,7 @@ jobs:
 
     - name: Publish distribution 📦 to PyPI
       if: startsWith(github.event.ref, 'refs/tags') || github.event_name == 'release'
-      uses: pypa/gh-action-pypi-publish@v1
+      uses: pypa/gh-action-pypi-publish@v1.4.1
       with:
         user: __token__
         password: ${{ secrets.pypi_password }}

CHANGELOG.md

@@ -30,6 +30,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `fsspec` to tuner ([#4458](https://github.com/PyTorchLightning/pytorch-lightning/pull/4458))
 
 
+- Added metrics aggregation in Horovod and fixed early stopping ([#3775](https://github.com/PyTorchLightning/pytorch-lightning/pull/3775)) 
+
+
 ### Changed
 
 

benchmarks/test_parity.py

@@ -11,7 +11,7 @@
 
 @pytest.mark.parametrize('cls_model,max_diff', [
     (ParityModuleRNN, 0.05),
-    (ParityModuleMNIST, 0.70)
+    (ParityModuleMNIST, 0.8)
 ])
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="test requires GPU machine")
 def test_pytorch_parity(tmpdir, cls_model, max_diff):