Fixes #82: Split up quick and end-to-end tests

Imported from GitHub PR #82

PiperOrigin-RevId: 239996667

.coveragerc

@@ -2,6 +2,7 @@
 [run]
 branch = True
 source = adanet
+parallel = True
 
 [report]
 # Regexes for lines to exclude from consideration

.travis.yml

@@ -11,16 +11,25 @@ env:
   global:
     - CODECOV_TOKEN="0d2c482b-f42c-4d4c-b092-cb628ad20857"
     - BAZEL_VERSION=0.20.0
+    - COVERAGE_PROCESS_START=$PWD/.coveragerc
   matrix:
     # We test against recent versions of TensorFlow and tf-nightly.
-    # If updating, also update TF_LATEST above
-    # TODO: Enable recent versions on release
-    - TF_VERSION="1.9.*"
-    - TF_VERSION="1.10.*"
-    - TF_VERSION="1.11.*"
-    - TF_VERSION="1.12.*"
-    - TF_VERSION="1.13.*"
-    - TF_VERSION="tf-nightly"
+
+    # Quick test suite.
+    - TF_VERSION="1.9.*" SUITE="quick"
+    - TF_VERSION="1.10.*" SUITE="quick"
+    - TF_VERSION="1.11.*" SUITE="quick"
+    - TF_VERSION="1.12.*" SUITE="quick"
+    - TF_VERSION="1.13.*" SUITE="quick"
+    - TF_VERSION="tf-nightly" SUITE="quick"
+
+    # E2E Tests.
+    - TF_VERSION="1.9.*" SUITE="e2e"
+    - TF_VERSION="1.10.*" SUITE="e2e"
+    - TF_VERSION="1.11.*" SUITE="e2e"
+    - TF_VERSION="1.12.*" SUITE="e2e"
+    - TF_VERSION="1.13.*" SUITE="e2e"
+    - TF_VERSION="tf-nightly" SUITE="e2e"
 before_install:
   - sudo apt-get -y install pkg-config zip g++ zlib1g-dev unzip
   - wget https://github.com/bazelbuild/bazel/releases/download/"$BAZEL_VERSION"/bazel-"$BAZEL_VERSION"-installer-linux-x86_64.sh
@@ -32,9 +41,15 @@ addons:
 install:
   - pip install -r requirements.txt
   - pip install numpy --upgrade
+  - pip install coverage-enable-subprocess
   - ./oss_scripts/oss_pip_install.sh
 script:
-  - nosetests
+  - |
+    if [ $SUITE == "e2e" ]; then
+      NOSE_EXCLUDE='.*workers.*' nosetests adanet/core/estimator_distributed_test.py
+    else
+      NOSE_EXCLUDE='.*nasnet.*.py|.*test_distributed_training.*' nosetests
+    fi
   - cat /tmp/absl_testing/**/*.txt || true  # Don't error if file does not exist.
 after_success:
   # Install codecov for tracking coverage over time.

README.md

@@ -39,8 +39,8 @@ AdaNet provides the following AutoML features:
  * Regression, binary and multi-class classification, and multi-head task support.
  * A [`tf.estimator.Estimator`](https://www.tensorflow.org/guide/estimators) API for training, evaluation, prediction, and serving models.
  * The [`adanet.AutoEnsembleEstimator`](https://github.com/tensorflow/adanet/blob/master/adanet/autoensemble/estimator.py) for learning to ensemble user-defined `tf.estimator.Estimators`.
- * The ability to define subnetworks that change structure over time using [`tf.keras.layers`](https://www.tensorflow.org/guide/keras#functional_api) via the [`adanet.subnetwork` API](https://github.com/tensorflow/adanet/blob/master/adanet/subnetwork/generator.py).
- * CPU, GPU, and TPU support.
+ * The ability to define subnetworks that change structure over time using [`tf.keras.layers`](https://www.tensorflow.org/guide/keras#functional_api) via the [`adanet.subnetwork` API](https://github.com/tensorflow/adanet/blob/master/adanet/core/subnetwork/generator.py).
+ * CPU and GPU support (TPU coming soon).
  * [Distributed multi-server training](https://cloud.google.com/blog/products/gcp/easy-distributed-training-with-tensorflow-using-tfestimatortrain-and-evaluate-on-cloud-ml-engine).
  * TensorBoard integration.
 
@@ -148,3 +148,17 @@ If you use this AdaNet library for academic research, you are encouraged to cite
 ## License
 
 AdaNet is released under the [Apache License 2.0](LICENSE).
+
+<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/katex@0.10.1/dist/katex.min.css" integrity="sha384-dbVIfZGuN1Yq7/1Ocstc1lUEm+AT+/rCkibIcC/OmWo5f0EA48Vf8CytHzGrSwbQ" crossorigin="anonymous">
+<script defer src="https://cdn.jsdelivr.net/npm/katex@0.10.1/dist/katex.min.js" integrity="sha384-2BKqo+exmr9su6dir+qCw08N2ZKRucY4PrGQPPWU1A7FtlCGjmEGFqXCv5nyM5Ij" crossorigin="anonymous"></script>
+<script defer src="https://cdn.jsdelivr.net/npm/katex@0.10.1/dist/contrib/auto-render.min.js" integrity="sha384-kWPLUVMOks5AQFrykwIup5lo0m3iMkkHrD0uJ4H5cjeGihAutqP0yW0J6dpFiVkI" crossorigin="anonymous"></script>
+<script>
+    document.addEventListener("DOMContentLoaded", function() {
+        renderMathInElement(document.body, {
+            delimiters: [
+                {left: "$$", right: "$$", display: true},
+                {left: "$", right: "$", display: false},
+            ]
+        });
+    });
+</script>

adanet/core/estimator_distributed_test.py

@@ -294,7 +294,7 @@ def test_distributed_training(self,
       self._wait_for_processes(
           worker_processes + evaluator_processes,
           kill_processes=ps_processes,
-          timeout_secs=180)
+          timeout_secs=300)
     finally:
       for process in worker_processes + ps_processes + evaluator_processes:
         try:

oss_scripts/oss_pip_install.sh

@@ -17,8 +17,6 @@
 set -v  # print commands as they're executed
 set -e  # fail and exit on any command erroring
 
-BAZEL_VERSION=0.20.0
-
 : "${TF_VERSION:?}"
 
 if [[ "$TF_VERSION" == "tf-nightly"  ]]

setup.cfg

@@ -3,4 +3,3 @@ verbosity=3
 rednose=1
 with-coverage=1
 cover-package=adanet
-exclude=.*nasnet.*.py|.*estimator_distributed_test.py