[RELEASE]: v0.9.9

.circleci/config.yml

@@ -1,3 +1,5 @@
+
+
 # Use the latest 2.1 version of CircleCI pipeline process engine.
 version: 2.1
 
@@ -54,6 +56,7 @@ jobs:
       TOXENV: coverage,doctest,type,check 
       TOX_INSTALL_DIR: .env
       JAVA_HOME: /usr/lib/jvm/java-8-openjdk-amd64
+      PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION: python
 
     steps:
       - checkout
@@ -69,6 +72,7 @@ jobs:
       TOXENV: coverage,doctest,type,check 
       TOX_INSTALL_DIR: .env
       JAVA_HOME: /usr/lib/jvm/java-8-openjdk-amd64
+      PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION: python
 
     steps:
       - checkout
@@ -101,16 +105,29 @@ jobs:
 
     steps:
       - checkout
+      - run:
+          name: Setup python3
+          command: |
+            pyenv global 3.8.13 > /dev/null && activated=0 || activated=1
+            if [[ $activated -ne 0 ]]; then
+              for i in {1..6}; do
+                pyenv install 3.8.13 && break || sleep $((2 ** $i))
+              done
+              pyenv global 3.8.13
+            fi
       - setup_dependencies
       - run:
           name: "Run Tox"
-          command:  tox
+          no_output_timeout: 60m
+          command: |
+            export PYTHONUNBUFFERED=1
+            tox
 
   Python37-Integration-Tests: 
     docker:
       - image: cimg/python:3.7
     environment:
-      TOXENV: complex,spark,type,check
+      TOXENV: complex,type,check
       TOX_INSTALL_DIR: .env
       JAVA_HOME: /usr/lib/jvm/java-8-openjdk-amd64
 
@@ -119,7 +136,10 @@ jobs:
       - setup_dependencies
       - run:
           name: "Run Tox"
-          command:  tox
+          no_output_timeout: 60m
+          command: |
+            export PYTHONUNBUFFERED=1
+            tox
 
   Python36-Integration-Tests: 
     docker:
@@ -139,17 +159,16 @@ jobs:
 workflows:
   version: 2
 
-  Interation-Tests: 
+  Integration-Tests: 
     jobs:
       - Python38-Integration-Tests:
           <<: *run_complex
       - Python37-Integration-Tests:
-         <<: *run_complex
+          <<: *run_complex
       - Python36-Integration-Tests:
           <<: *run_complex
   Unit-Tests:
     jobs:
       - Python37-Unit-Tests
       - Python36-Unit-Tests
       - Python38-Unit-Tests
-

CHANGELOG.md

@@ -5,13 +5,31 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
 ## [Unreleased]
-## [0.9.9]
+## [0.9.10]
 ### [Breaking Changes]
 ### [Added]
 ### [Changed]
 ### [Deprecated]
 ### [Removed]
 
+## [0.9.9] - 2022-04-14
+### [Added]
+
+* PR #1690: Bump numpy version for Mac M1 compat
+* PR #1696: Fix linting
+* PR #1694: Fix test loss
+* PR #1693: Update black version to fix build
+* PR #1671: Fix flaky test
+* PR #1688: Fix branch filtering for complex tests
+* PR #1686: Switch to CircleCI badge
+* PR #1685: Migrating travis -> circle 
+
+
+### [Contributors]
+
+Thanks to @rsmith49, @zexuan-zhou, @humzaiqbal, @fpoms, @crawlingcub, and @henryre for contributions!
+
+
 ## [0.9.8] - 2021-09-23
 ### [Added]
 

requirements.txt

@@ -10,46 +10,47 @@
 
 # General scientific computing
 
-numpy>=1.16.5,<=1.22.3
-scipy>=1.2.0,<2.0.0
+numpy>=1.16.5
+scipy>=1.2.0
 
 # Data storage and function application
-pandas>=1.0.0,<2.0.0
-tqdm>=4.33.0,<5.0.0
+pandas>=1.0.0
+tqdm>=4.33.0
 
 # Internal models
-scikit-learn>=0.20.2,<1.1
-torch>=1.2.0,<2.0.0
+scikit-learn>=0.20.2
+torch>=1.2.0
 munkres>=1.0.6
 
 # LF dependency learning
-networkx>=2.2,<2.7
+networkx>=2.2
 
 # Model introspection tools
-tensorboard>=2.0.0,<2.7.0
+tensorboard>=2.9.1
 
 #### EXTRA/TEST LIBRARIES
 
 # spaCy (NLP)
-spacy>=2.1.0,<3.0.0
-blis>=0.3.0,<=0.7.7
+spacy>=2.1.0
+blis>=0.3.0
 
 # Dask (parallelism)
-dask[dataframe]>=2020.12.0,<2022.04.1
-distributed>=2020.12.0,<2022.04.1
+dask[dataframe]>=2020.12.0
+distributed>=2020.12.0
 
 # Dill (serialization)
-dill>=0.3.0,<0.4.0
+dill>=0.3.0
 
 
 #### DEV TOOLS
 
 black>=22.3
-flake8>=3.7.0,<4.0.0
-isort>=4.3.0,<5.0.0
-mypy==0.931
-pydocstyle>=4.0.0,<5.0.0
+flake8>=3.7.0
+isort>=4.3.0
+mypy==0.760
+pydocstyle>=4.0.0
 pytest>=5.0.0,<6.0.0
-pytest-cov>=2.7.0,<3.0.0
-pytest-doctestplus>=0.3.0,<0.4.0
-tox>=3.13.0,<4.0.0
+pytest-cov>=2.7.0
+pytest-doctestplus>=0.3.0
+tox>=3.13.0
+protobuf==3.19.4

setup.py

@@ -36,14 +36,14 @@
     include_package_data=True,
     install_requires=[
         "munkres>=1.0.6",
-        "numpy>=1.16.5,<=1.22.3",
-        "scipy>=1.2.0,<2.0.0",
-        "pandas>=1.0.0,<2.0.0",
-        "tqdm>=4.33.0,<5.0.0",
-        "scikit-learn>=0.20.2,<1.1",
-        "torch>=1.2.0,<2.0.0",
-        "tensorboard>=2.0.0,<2.7.0",
-        "networkx>=2.2,<2.7",
+        "numpy>=1.16.5",
+        "scipy>=1.2.0",
+        "pandas>=1.0.0",
+        "tqdm>=4.33.0",
+        "scikit-learn>=0.20.2",
+        "torch>=1.2.0",
+        "tensorboard>=2.9.1",
+        "networkx>=2.2",
     ],
     python_requires=">=3.6",
     keywords="machine-learning ai weak-supervision",

snorkel/labeling/model/label_model.py

@@ -569,14 +569,14 @@ def _set_class_balance(
         3) Assume uniform class distribution
         """
         if class_balance is not None:
-            self.p = np.array(class_balance)
+            self.p = np.array(class_balance)  # type: ignore
             if len(self.p) != self.cardinality:
                 raise ValueError(
                     f"class_balance has {len(self.p)} entries. Does not match LabelModel cardinality {self.cardinality}."
                 )
         elif Y_dev is not None:
-            class_counts = Counter(Y_dev)
-            sorted_counts = np.array([v for k, v in sorted(class_counts.items())])
+            class_counts = Counter(Y_dev)  # type: ignore
+            sorted_counts = np.array([v for k, v in sorted(class_counts.items())])  # type: ignore
             self.p = sorted_counts / sum(sorted_counts)
             if len(self.p) != self.cardinality:
                 raise ValueError(

snorkel/version.py

@@ -1,6 +1,6 @@
 _MAJOR = "0"
 _MINOR = "9"
-_REVISION = "9+dev"
+_REVISION = "9"
 
 VERSION_SHORT = f"{_MAJOR}.{_MINOR}"
 VERSION = f"{_MAJOR}.{_MINOR}.{_REVISION}"

test/labeling/apply/test_lf_applier.py

@@ -70,7 +70,7 @@ def f_bad(x: DataPoint) -> int:
 L_EXPECTED_BAD = np.array([[-1, -1], [0, -1], [-1, -1], [-1, -1], [-1, -1]])
 L_PREPROCESS_EXPECTED = np.array([[-1, -1], [0, 0], [-1, 0], [-1, 0], [-1, -1]])
 
-TEXT_DATA = ["Jane", "Jane plays soccer.", "Jane plays soccer."]
+TEXT_DATA = ["Jane.", "Jane plays soccer.", "Jane plays soccer."]
 L_TEXT_EXPECTED = np.array([[0, -1], [0, 0], [0, 0]])