0.17rc

.flake8

@@ -1,2 +1,4 @@
 [flake8]
-exclude = tmp.py, tests/
+ignore = E203
+exclude = tmp.py, tests/
+max-line-length = 120

.github/workflows/test.yml

@@ -13,7 +13,16 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.7, 3.8, 3.9]
+        include:
+          - python-version: '3.7'
+            tf-version: '2.7'
+          - python-version: '3.7'
+            tf-version: '2.11'
+          - python-version: '3.10'
+            # Python 3.10 only supports TF >= 2.8
+            tf-version: '2.8'
+          - python-version: '3.10'
+            tf-version: '2.11'
 
     steps:
     - uses: actions/checkout@v2
@@ -26,9 +35,13 @@ jobs:
         python -m pip install --upgrade pip
         pip install coveralls
 
-    - name: Install package
+    - name: Install dev packages
       run: |
-        pip install ".[tensorflow,dev]"
+        pip install ".[dev]"
+
+    - name: Install TF package
+      run: |
+        pip install tensorflow==${{ matrix.tf-version }}
 
     - name: Lint with flake8
       run: |

.gitignore

@@ -11,7 +11,6 @@ release.sh
 benchmark/supervised/datasets/
 benchmark/supervised/models/
 datasets/
-models/
 
 # Byte-compiled / optimized / DLL files
 __pycache__/

examples/README.md

@@ -6,4 +6,5 @@
 | [Hello World](./supervised_hello_world.ipynb) | Supervised | Train and use an image similarity model to find similar looking MNIST digits |
 | [Self-Supervised Learning](./unsupervised_hello_world.ipynb) | Unsupervised | Train an image model using the SimSiam based self-supervised contrastive learning. |
 | [visualization](./supervised/visualization.ipynb) | Supervised | Train an image similarity model on the Stanford Dogs dataset using Evaluation Callbacks and the interactive visualizer |
-| [Sampler IO Cookbook](./sampler_io_cookbook.ipynb) | Utils | Examples demonstrating how to use the various in memory batch samplers.
+| [Sampler IO Cookbook](./sampler_io_cookbook.ipynb) | Utils | Examples demonstrating how to use the various in memory batch samplers. |
+| [CLIP finetuning](./multimodal_example.ipynb) | Supervised | Finetune CLIP on atric-dataset using multiple negatives ranking loss.