Sudivate/fixdeployaci (#178)

diabetes_regression/ci_dependencies.yml

@@ -1,31 +1,28 @@
 name: mlopspython_ci
 
 dependencies:
-
   # The python interpreter version.
-- python=3.7.5
+  - python=3.7.5
 
   # dependencies with versions aligned with conda_dependencies.yml.
-- numpy=1.18.1
-- pandas=1.0.0
-- scikit-learn=0.22.1
-
-  # dependencies for MLOps with R.
-- r=3.6.0
-- r-essentials=3.6.0
+  - numpy=1.18.1
+  - pandas=1.0.0
+  - scikit-learn=0.22.1
+    # dependencies for MLOps with R.
+  - r=3.6.0
+  - r-essentials=3.6.0
 
-- pip=20.0.2
-- pip:
-
-  # dependencies with versions aligned with conda_dependencies.yml.
-  - azureml-sdk==1.0.79
+  - pip=20.0.2
+  - pip:
+      # dependencies with versions aligned with conda_dependencies.yml.
+      - azureml-sdk==1.0.85
 
-  # Additional pip dependencies for the CI environment.
-  - pytest==5.3.1
-  - pytest-cov==2.8.1
-  - requests==2.22.0
-  - python-dotenv==0.10.3
-  - flake8==3.7.9
-  - flake8_formatter_junit_xml==0.0.6
-  - azure-cli==2.0.77
-  - tox==3.14.3
+      # Additional pip dependencies for the CI environment.
+      - pytest==5.3.1
+      - pytest-cov==2.8.1
+      - requests==2.22.0
+      - python-dotenv==0.10.3
+      - flake8==3.7.9
+      - flake8_formatter_junit_xml==0.0.6
+      - azure-cli==2.0.81
+      - tox==3.14.3

diabetes_regression/conda_dependencies.yml

@@ -4,30 +4,28 @@
 name: diabetes_regression_sklearn
 
 dependencies:
-
   # The python interpreter version.
-- python=3.7.5
+  - python=3.7.5
 
   # Required by azureml-defaults, installed separately through Conda to
   # get a prebuilt version and not require build tools for the install.
-- psutil=5.6 #latest
-
-- numpy=1.18.1
-- pandas=1.0.0
-- scikit-learn=0.22.1
-#- r-essentials
-#- tensorflow
-#- keras
+  - psutil=5.6 #latest
 
-- pip=20.0.2
-- pip:
+  - numpy=1.18.1
+  - pandas=1.0.0
+  - scikit-learn=0.22.1
+  #- r-essentials
+  #- tensorflow
+  #- keras
 
-  # Dependencies for training environment.
+  - pip=20.0.2
+  - pip:
+      # Dependencies for training environment.
 
-  - azureml-core==1.0.79
+      - azureml-core==1.0.85
 
-  # Dependencies for scoring environment.
+      # Dependencies for scoring environment.
 
-  # You must list azureml-defaults as a pip dependency
-  - azureml-defaults==1.0.79
-  - inference-schema[numpy-support]==1.0.1
+      # You must list azureml-defaults as a pip dependency
+      - azureml-defaults==1.0.85
+      - inference-schema[numpy-support]==1.0.1

environment_setup/Dockerfile

@@ -1,19 +1,16 @@
 FROM conda/miniconda3
 
 LABEL org.label-schema.vendor = "Microsoft" \
-      org.label-schema.url = "https://hub.docker.com/r/microsoft/mlopspython" \
-      org.label-schema.vcs-url = "https://github.com/microsoft/MLOpsPython"
+    org.label-schema.url = "https://hub.docker.com/r/microsoft/mlopspython" \
+    org.label-schema.vcs-url = "https://github.com/microsoft/MLOpsPython"
 
 COPY diabetes_regression/ci_dependencies.yml /setup/
 
-RUN conda env create -f /setup/ci_dependencies.yml
-
 # activate environment
 ENV PATH /usr/local/envs/mlopspython_ci/bin:$PATH
-RUN /bin/bash -c "source activate mlopspython_ci"
 
-# Verify conda installation.
-# This serves as workaround for https://github.com/conda/conda/issues/8537 (conda env create doesn't fail
-# if pip installation fails, for example due to a wrong package version).
-# The `az` command is not available if pip has not run (and installed azure-cli).
-RUN az --version
+RUN conda update -n base -c defaults conda && \
+    conda install python=3.7.5 && \
+    conda env create -f /setup/ci_dependencies.yml && \
+    /bin/bash -c "source activate mlopspython_ci" && \
+    az --version

ml_service/util/create_scoring_image.py

@@ -3,6 +3,7 @@
 from azureml.core import Workspace
 from azureml.core.image import ContainerImage, Image
 from azureml.core.model import Model
+import shutil
 from ml_service.util.env_variables import Env
 
 e = Env()
@@ -29,8 +30,10 @@
     sources_dir = 'diabetes_regression'
 path_to_scoring = os.path.join(".", sources_dir, "scoring")
 cwd = os.getcwd()
+# Copy conda_dependencies.yml into scoring as this method does not accept relative paths. # NOQA: E501
+shutil.copy(os.path.join(".", sources_dir,
+                         "conda_dependencies.yml"), path_to_scoring)
 os.chdir(path_to_scoring)
-
 image_config = ContainerImage.image_configuration(
     execution_script=e.score_script,
     runtime="python",
@@ -40,7 +43,8 @@
 )
 
 image = Image.create(
-    name=e.image_name, models=[model], image_config=image_config, workspace=ws
+    name=e.image_name, models=[
+        model], image_config=image_config, workspace=ws
 )
 
 os.chdir(cwd)

tests/unit/code_test.py

@@ -15,7 +15,7 @@ def test_train_model():
     run = Mock(Run)
     reg = train_model(run, data, alpha=1.2)
 
-    run.log.assert_called_with("mse", 0.029843893480256872,
+    run.log.assert_called_with("mse", 0.029843893480257067,
                                description='Mean squared error metric')
 
     preds = reg.predict([[1], [2]])