readme add test status badge

.github/workflows/main.yml

@@ -1,68 +1,48 @@
-# Adapted from https://github.com/pytorch/examples/blob/master/.github/workflows/main.yml
+# Example of how to open issues on failed tests: https://git.io/JUfDd
 
-name: Run Tests
+name: tests
 
 on:
   push:
     paths:
       - '**.py' # only run workflow when source files changed
   pull_request:
     paths:
-      - '**.py' # only run workflow when source files changed
+      - '**.py'
 
 jobs:
   tests:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
 
+      - name: Set up latest Python 3
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.x
+
       - name: Cache dependencies
         # Adapted from https://git.io/JUfrK
         uses: actions/cache@v2
         id: cache-deps
         with:
-          # This path is specific to Ubuntu
-          path: ~/.cache/pip
+          path: ${ pip cache dir } # requires pip 20.1+
           # Look to see if there is a cache hit for the corresponding environment file
-          key: ${{ runner.os }}-pip-${{ hashFiles('env.yml') }}
-          # Ordered list of keys to use for restoring the cache if no cache hit occurred for key
+          key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}
+          # Optional ordered list of alternative keys to use for restoring the cache
+          # if no cache was found for key
           restore-keys: |
             ${{ runner.os }}-pip-
-            ${{ runner.os }}-
-
-      - name: Set up latest Python 3
-        if: steps.cache-deps.outputs.cache-hit != 'true'
-        uses: actions/setup-python@v2
-        with:
-          python-version: 3.x
 
       - name: Install dependencies
-        if: steps.cache-deps.outputs.cache-hit != 'true'
         run: |
-          python -m pip install -U pip
-          pip install -U pytest sklearn flake8
-          # Install CPU-based pytorch
-          pip install --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
+          pip install -r requirements.txt
           pip install .
-          # Maybe use the CUDA 10.2 version instead?
-          # pip install --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cu102/torch_nightly.html
 
       - name: Run Tests
         run: |
           python -m pytest
 
-      - name: Open issue on failure
-        if: ${{ failure() }}
-        uses: rishabhgupta/git-action-issue@v2
-        with:
-          token: ${{ secrets.GITHUB_TOKEN }}
-          title: Test suite failed on CI
-          body: Commit ${{ github.sha }} caused [CI run](https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}) to fail, please check why.
-          assignees: janosh
-
-  linting:
-    runs-on: ubuntu-latest
-    steps:
       - name: Lint with flake8
         # Adapted from https://git.io/JUfPw
         run: |

readme.md

@@ -1,4 +1,4 @@
-# Torch MNF
+# Torch MNF   [![Test Status](https://github.com/janosh/torch-mnf/workflows/tests/badge.svg)](https://github.com/janosh/torch-mnf/actions)
 
 PyTorch implementation of Multiplicative Normalizing Flows [[1]](#mnf-bnn).
 

requirements.txt

@@ -0,0 +1,10 @@
+flake8
+matplotlib
+numpy
+pandas
+pytest
+seaborn
+scikit-learn
+scipy
+torch
+torchvision

torch_mnf/notebooks/2d.py

@@ -71,7 +71,7 @@
 print(f"number of params: {sum(p.numel() for p in model.parameters()):,}")
 
 
-def train(steps=1000, n_samples=128, report_every=100, cb=None):
+def train_flow(steps=1000, n_samples=128, report_every=100, cb=None):
     for step in range(steps + 1):
         x = sample_target_dist(n_samples)
 
@@ -91,7 +91,7 @@ def train(steps=1000, n_samples=128, report_every=100, cb=None):
 
 
 # %%
-train()
+train_flow()
 
 
 # %%
@@ -202,4 +202,4 @@ def plot_learning():
 
 
 # %%
-train(steps=400, cb=plot_learning)
+train_flow(steps=400, cb=plot_learning)