CICD (#20)

.github/codecov.yml

@@ -6,3 +6,13 @@ ignore:
   - "Pyrado/pyrado/environments/mujoco"
   - "Pyrado/scripts"
   - "Pyrado/tests"
+comment:
+  layout: "reach, diff, flags, files"
+  behavior: default
+  require_changes: false # if true: only post the comment if coverage changes
+  require_base: no # [yes :: must have a base report to post]
+  require_head: yes # [yes :: must have a head report to post]
+  branches: # branch names that can post comment
+    - "master"
+github_checks:
+  annotations: false

.github/workflows/publish_docs.yml

@@ -0,0 +1,39 @@
+name: Deploy Documentation
+
+on:
+  workflow_run:
+    workflows: ["Publish Docker Images"]
+    branches: [cicd]
+    types:
+      - completed
+      - requested
+
+jobs:
+  build-docs:
+    runs-on: ubuntu-latest
+    needs: build-images
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          submodules: true
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@v1
+        with:
+          registry: ghcr.io
+          username: ${{ github.repository_owner }}
+          password: ${{ secrets.PAT }}
+      - name: Build Docs
+        continue-on-error: true
+        run: |
+          mkdir public
+          export PUBLIC=$(realpath ./public)
+          docker run --rm -u 1000:1000 -v $PUBLIC:/var/www ghcr.io/famura/simurlacra:sacher conda run -n pyrado bash -c "./build_docs.sh;sudo mkdir /var/www/pyrado; sudo cp -r Pyrado/doc/build/* /var/www/pyrado;mv RcsPySim/build/doc/html RcsPySim/build/doc/rcspysim; sudo cp -r RcsPySim/build/doc/rcspysim /var/www"
+          echo $PUBLIC
+          ls $PUBLIC quietioet
+      - name: Deploy
+        continue-on-error: true
+        uses: JamesIves/[email protected]
+        with:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          BRANCH: gh-pages
+          FOLDER: public

.github/workflows/run_tests.yml

@@ -12,14 +12,16 @@ jobs:
       - uses: actions/checkout@v2
         with:
           submodules: true
+      - name: Build Image
+        run: |
+          docker pull simurlacra/simurlacra:sacher
+          docker build . -t simurlacra:test --build-arg OPTION=sacher
       - name: Execute tests
         env:
           CC_TEST_REPORTER_ID: ${{ secrets.CC_TEST_REPORTER_ID }}
         run: |
-          docker pull simurlacra/simurlacra:sacher
-          docker build . -t simurlacra:test --build-arg OPTION=sacher --cache-from simurlacra/simurlacra:sacher
           export COVPATH=$(realpath .)
-          docker run --rm -i -v $COVPATH:/cov simurlacra:test conda run -n pyrado bash -c "pytest Pyrado/tests --cov=./Pyrado --cov-report=xml -v -m 'not visualization' -n 4; sudo cp ./coverage.xml /cov"
+          docker run --rm -i -v $COVPATH:/cov simurlacra:test bash -c "pytest Pyrado --cov=./Pyrado --cov-report=xml --verbose -n 2 -m 'not visualization'; sudo cp ./coverage.xml /cov"
           sudo mkdir /home/user/
           sudo mkdir /home/user/SimuRLacra
           sudo ln -s $COVPATH /home/user/SimuRLacra

.github/workflows/run_tests_future.yml

@@ -0,0 +1,60 @@
+name: Run Tests (future)
+
+on:
+  push:
+    branches: [cicd_future]
+  pull_request:
+    branches: [cicd_future]
+
+jobs:
+  build-images:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        flavor: [sacher]
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          submodules: true
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v1
+      - name: Build
+        id: docker_build
+        uses: docker/build-push-action@v2
+        with:
+          context: .
+          outputs: |
+            type=docker
+          tags: |
+            simurlacra:test
+          build-args: |
+            OPTION=${{ matrix.flavor }}
+          cache-from: type=registry,ref=simurlacra/simurlacra:${{ matrix.flavor }}
+      - name: Inspect
+        run: |
+
+          docker image inspect simurlacra:test
+      - name: Execute tests
+        env:
+          CC_TEST_REPORTER_ID: ${{ secrets.CC_TEST_REPORTER_ID }}
+        run: |
+          export COVPATH=$(realpath .)
+          docker run --rm -i -v $COVPATH:/cov simurlacra:test conda run -n pyrado bash -c "pytest Pyrado/tests --cov=./Pyrado --cov-report=xml -n 4 --verbose -m 'not visualization'; sudo cp ./coverage.xml /cov"
+          sudo mkdir /home/user/
+          sudo mkdir /home/user/SimuRLacra
+          sudo ln -s $COVPATH /home/user/SimuRLacra
+          cd Pyrado
+      - name: Send Coverage to Codecov
+        uses: codecov/codecov-action@v1
+        with:
+          file: coverage.xml # optional
+          flags: unittests # optional
+          name: codecov-umbrella # optional
+          fail_ci_if_error: true
+      - name: Test & publish code coverage
+        uses: paambaati/[email protected]
+        env:
+          CC_TEST_REPORTER_ID: ${{ secrets.CC_TEST_REPORTER_ID }}
+        with:
+          coverageLocations: |
+            coverage.xml:cobertura

Dockerfile

@@ -52,9 +52,8 @@ USER user
 WORKDIR /home/user
 
 # Setup conda
-RUN echo "export PATH=/home/user/miniconda3/bin:$PATH" >> ~/.bashrc
-
-RUN wget --quiet     https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
+RUN echo "export PATH=/home/user/miniconda3/bin:$PATH" >> ~/.bashrc \
+    && wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
     && bash Miniconda3-latest-Linux-x86_64.sh -b \
     && rm Miniconda3-latest-Linux-x86_64.sh
 
@@ -71,7 +70,7 @@ RUN conda create -n pyrado python=3.7 blas cmake lapack libgcc-ng mkl mkl-includ
 SHELL ["conda", "run", "-n", "pyrado", "/bin/bash", "-c"]
 
 RUN pip install argparse black box2d colorama coverage cython glfw gym joblib prettyprinter matplotlib numpy optuna pandas pycairo pytest pytest-cov pytest-xdist pyyaml scipy seaborn sphinx sphinx-math-dollar sphinx_rtd_theme tabulate tensorboard tqdm vpython git+https://github.com/Xfel/init-args-serializer.git@master; \
-    conda init bashL; rm -fr /home/user/.cache
+    conda init bash ; rm -fr /home/user/.cache
 
 # Add env variables
 ENV PATH /home/user/miniconda3/envs/pyrado/bin:$PATH

Pyrado/pyrado/algorithms/meta/adr.py

@@ -26,14 +26,12 @@
 # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 # POSSIBILITY OF SUCH DAMAGE.
 
+from typing import Optional, Sequence
+
 import numpy as np
+import pyrado
 import torch as to
 from init_args_serializer import Serializable
-from torch import nn as nn
-from tqdm import tqdm
-from typing import Sequence, Optional
-
-import pyrado
 from pyrado.algorithms.base import Algorithm
 from pyrado.algorithms.step_based.svpg import SVPG
 from pyrado.domain_randomization.domain_parameter import DomainParam
@@ -48,6 +46,8 @@
 from pyrado.sampling.step_sequence import StepSequence
 from pyrado.spaces.box import BoxSpace
 from pyrado.utils.data_types import EnvSpec
+from torch import nn as nn
+from tqdm import tqdm
 
 
 class ADR(Algorithm):

Pyrado/pyrado/algorithms/meta/bayrn.py

@@ -26,37 +26,37 @@
 # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 # POSSIBILITY OF SUCH DAMAGE.
 
-import numpy as np
 import os
 import os.path as osp
+from typing import Optional, Union
+
+import numpy as np
+import pyrado
 import torch as to
-from botorch.models import SingleTaskGP
+from botorch.acquisition import ExpectedImprovement, PosteriorMean, ProbabilityOfImprovement, UpperConfidenceBound
 from botorch.fit import fit_gpytorch_model
-from botorch.acquisition import UpperConfidenceBound, ExpectedImprovement, ProbabilityOfImprovement, PosteriorMean
+from botorch.models import SingleTaskGP
 from botorch.optim import optimize_acqf
 from gpytorch.constraints import GreaterThan
 from gpytorch.mlls import ExactMarginalLogLikelihood
-from tabulate import tabulate
-from typing import Optional, Union
-
-import pyrado
 from pyrado.algorithms.base import Algorithm, InterruptableAlgorithm
 from pyrado.algorithms.utils import until_thold_exceeded
-from pyrado.logger.step import StepLogger
-from pyrado.spaces import BoxSpace
 from pyrado.environment_wrappers.base import EnvWrapper
 from pyrado.environment_wrappers.domain_randomization import MetaDomainRandWrapper
 from pyrado.environment_wrappers.utils import inner_env, typed_env
 from pyrado.environments.real_base import RealEnv
 from pyrado.environments.sim_base import SimEnv
+from pyrado.logger.step import StepLogger
 from pyrado.policies.base import Policy
 from pyrado.sampling.bootstrapping import bootstrap_ci
 from pyrado.sampling.parallel_rollout_sampler import ParallelRolloutSampler
 from pyrado.sampling.rollout import rollout
-from pyrado.utils.order import natural_sort
+from pyrado.spaces import BoxSpace
+from pyrado.utils.data_processing import standardize
 from pyrado.utils.input_output import print_cbt
 from pyrado.utils.math import UnitCubeProjector
-from pyrado.utils.data_processing import standardize
+from pyrado.utils.order import natural_sort
+from tabulate import tabulate
 
 
 class BayRn(InterruptableAlgorithm):
@@ -159,7 +159,8 @@ def __init__(
         self._subrtn.save_name = "subrtn"
         self.ddp_space = ddp_space
         self.ddp_projector = UnitCubeProjector(
-            to.from_numpy(self.ddp_space.bound_lo), to.from_numpy(self.ddp_space.bound_up)
+            to.from_numpy(self.ddp_space.bound_lo).to(dtype=to.get_default_dtype()),
+            to.from_numpy(self.ddp_space.bound_up).to(dtype=to.get_default_dtype()),
         )
         self.cands = None  # called x in the context of GPs
         self.cands_values = None  # called y in the context of GPs
@@ -405,13 +406,16 @@ def step(self, snapshot_mode: str = "latest", meta_info: dict = None):
                 raise pyrado.ValueErr(given=self.acq_fcn_type, eq_constraint="'UCB', 'EI', 'PI'")
 
             # Optimize acquisition function and get new candidate point
-            cand_norm, acq_value = optimize_acqf(
+            cand_norm, _ = optimize_acqf(
                 acq_function=acq_fcn,
-                bounds=to.stack([to.zeros(self.ddp_space.flat_dim), to.ones(self.ddp_space.flat_dim)]),
+                bounds=to.stack([to.zeros(self.ddp_space.flat_dim), to.ones(self.ddp_space.flat_dim)]).to(
+                    dtype=to.float32
+                ),
                 q=1,
                 num_restarts=self.acq_restarts,
                 raw_samples=self.acq_samples,
             )
+            cand_norm = cand_norm.to(dtype=to.get_default_dtype())
             next_cand = self.ddp_projector.project_back(cand_norm)
             print_cbt(f"Found the next candidate: {next_cand.numpy()}", "g")
             self.cands = to.cat([self.cands, next_cand], dim=0)
@@ -484,7 +488,10 @@ def argmax_posterior_mean(
             raise pyrado.TypeErr(given=ddp_space, expected_type=BoxSpace)
 
         # Normalize the input data and standardize the output data
-        uc_projector = UnitCubeProjector(to.from_numpy(ddp_space.bound_lo), to.from_numpy(ddp_space.bound_up))
+        uc_projector = UnitCubeProjector(
+            to.from_numpy(ddp_space.bound_lo).to(dtype=to.get_default_dtype()),
+            to.from_numpy(ddp_space.bound_up).to(dtype=to.get_default_dtype()),
+        )
         cands_norm = uc_projector.project_to(cands)
         cands_values_stdized = standardize(cands_values)
 
@@ -503,14 +510,15 @@ def argmax_posterior_mean(
         fit_gpytorch_model(mll)
 
         # Find position with maximal posterior mean
-        cand_norm, acq_value = optimize_acqf(
+        cand_norm, _ = optimize_acqf(
             acq_function=PosteriorMean(gp),
-            bounds=to.stack([to.zeros(ddp_space.flat_dim), to.ones(ddp_space.flat_dim)]),
+            bounds=to.stack([to.zeros(ddp_space.flat_dim), to.ones(ddp_space.flat_dim)]).to(dtype=to.float32),
             q=1,
             num_restarts=num_restarts,
             raw_samples=num_samples,
         )
 
+        cand_norm = cand_norm.to(dtype=to.get_default_dtype())
         cand = uc_projector.project_back(cand_norm.detach())
         print_cbt(f"Converged to argmax of the posterior mean: {cand.numpy()}", "g", bright=True)
         return cand