PR #79: Fix TravisCI

 * Disable distributed tests which cause timeouts.
 * Fix failing logging in distributed placement tests.
 * Clean up install script.
 * Add TF 1.13.
 * Add requirements.txt for installing dependencies.

PiperOrigin-RevId: 238671430

.gitignore

@@ -6,6 +6,7 @@ docs/build*
 
 # Bazel outputs.
 bazel-*
+*_pb2.py
 
 # Byte-compiled
 _pycache__/

.travis.yml

@@ -1,4 +1,5 @@
 sudo: required
+dist: xenial
 language: python
 git:
   depth: 10
@@ -8,8 +9,8 @@ python:
   - "3.6"
 env:
   global:
-    - TF_LATEST="1.12.*"
     - CODECOV_TOKEN="0d2c482b-f42c-4d4c-b092-cb628ad20857"
+    - BAZEL_VERSION=0.20.0
   matrix:
     # We test against recent versions of TensorFlow and tf-nightly.
     # If updating, also update TF_LATEST above
@@ -18,12 +19,24 @@ env:
     - TF_VERSION="1.10.*"
     - TF_VERSION="1.11.*"
     - TF_VERSION="1.12.*"
+    - TF_VERSION="1.13.*"
     - TF_VERSION="tf-nightly"
+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
+  - chmod +x bazel-"$BAZEL_VERSION"-installer-linux-x86_64.sh
+  - ./bazel-"$BAZEL_VERSION"-installer-linux-x86_64.sh --user
+addons:
+  apt:
+    update: true
 install:
-  # Install codecov for tracking coverage over time.
-  - pip install codecov
+  - pip install -r requirements.txt
+  - pip install numpy --upgrade
   - ./oss_scripts/oss_pip_install.sh
 script:
-  - ./oss_scripts/oss_test.sh
+  - nosetests
+  - cat /tmp/absl_testing/**/*.txt || true  # Don't error if file does not exist.
 after_success:
+  # Install codecov for tracking coverage over time.
+  - pip install codecov
   - codecov

adanet/core/distributed/placement.py

@@ -232,8 +232,8 @@ def _worker_task(self, num_subnetworks):
                                                            self._num_workers):
       tf.logging.log_first_n(
           tf.logging.WARN,
-          "With drop_remainer=True, {} workers and {} subnetworks, the last {} "
-          "subnetworks will be dropped and will not be trained",
+          "With drop_remainer=True, %s workers and %s subnetworks, the last %s "
+          "subnetworks will be dropped and will not be trained", 1,
           self._num_workers, num_subnetworks,
           num_subnetworks - self._num_workers - 1)
     # The first worker will always build the ensemble so we add 1.

adanet/core/iteration.py

@@ -187,18 +187,18 @@ def _check_numerics(self, features, labels):
       if not _is_numeric(features[name]):
         continue
       tf.logging.info("DEBUG: Checking numerics of float feature '%s'.", name)
-      checked_features[name] = tf.debugging.check_numerics(
-          features[name], "features '{}'".format(name))
+      checked_features[name] = tf.check_numerics(features[name],
+                                                 "features '{}'".format(name))
     if isinstance(labels, dict):
       for name in sorted(labels):
         if not _is_numeric(labels[name]):
           continue
         tf.logging.info("DEBUG: Checking numerics of float label '%s'.", name)
-        checked_labels[name] = tf.debugging.check_numerics(
-            labels[name], "labels '{}'".format(name))
+        checked_labels[name] = tf.check_numerics(labels[name],
+                                                 "labels '{}'".format(name))
     elif labels is not None and _is_numeric(labels):
       tf.logging.info("DEBUG: Checking numerics of labels.")
-      checked_labels = tf.debugging.check_numerics(labels, "'labels'")
+      checked_labels = tf.check_numerics(labels, "'labels'")
     return checked_features, checked_labels
 
   def build_iteration(self,

adanet/pip_package/setup.py

@@ -26,8 +26,11 @@
   exec(in_file.read())
 
 REQUIRED_PACKAGES = [
-    'numpy >= 1.12.0',
-    'six >= 1.10.0',
+    'six==1.11.*',
+    'numpy==1.15.*',
+    'nose==1.3.*',
+    'rednose==1.3.*',
+    'coverage==4.5.*',
     'protobuf >= 3.6.0',
 ]
 

oss_scripts/oss_pip_install.sh

@@ -28,31 +28,8 @@ else
   pip install -q "tensorflow==$TF_VERSION"
 fi
 
-# Make sure we have the latest version of numpy - avoid problems we were
-# seeing with Python 3
-pip install -q -U numpy
-
-# Install Bazel for tests.
-# Step 1: Install required packages
-sudo apt-get install pkg-config zip g++ zlib1g-dev unzip python
-
-# Step 2: Download Bazel binary installer
-wget https://github.com/bazelbuild/bazel/releases/download/"$BAZEL_VERSION"/bazel-"$BAZEL_VERSION"-installer-linux-x86_64.sh
-
-# Step 3: Install Bazel
-chmod +x bazel-"$BAZEL_VERSION"-installer-linux-x86_64.sh
-./bazel-"$BAZEL_VERSION"-installer-linux-x86_64.sh --user
-export PATH="$PATH:$HOME/bin"
-
 # Build adanet pip packaging script
-bazel build //adanet/pip_package:build_pip_package
-
-# Create the adanet pip package
-bazel-bin/adanet/pip_package/build_pip_package /tmp/adanet_pkg
-
-# Install and test the pip package
-pip install /tmp/adanet_pkg/*.whl
+bazel build -c opt //... --local_resources 2048,.5,1.0
 
-# Finally try importing `adanet` in Python outside the cloned directory:
-cd ..
-python -c "import adanet"
+# Copy generated proto files.
+cp bazel-genfiles/adanet/core/report_pb2.py adanet/core

requirements.txt

@@ -0,0 +1,6 @@
+six==1.11.*
+numpy==1.15.*
+nose==1.3.*
+rednose==1.3.*
+coverage==4.5.*
+protobuf==3.6.*

setup.cfg

@@ -1,5 +1,6 @@
 [nosetests]
+verbosity=3
 rednose=1
 with-coverage=1
 cover-package=adanet
-exclude=.*nasnet.*.py
+exclude=.*nasnet.*.py|.*estimator_distributed_test.py