Merge pull request #2 from keisen/develop

Release v0.2.0

.gitignore

@@ -105,7 +105,8 @@ venv.bak/
 
 # Add by keisen
 *.swp
-examples/**/*.gif
 examples/core*
 examples/sandbox.ipynb
+/*.ipynb
 .node-version
+*.nbconvert.ipynb

.travis.yml

@@ -0,0 +1,21 @@
+dist: xenial
+branches:
+  except:
+    - gh-pages
+language: python
+python:
+  - "3.5"
+  - "3.6"
+  - "3.7"
+env:
+  - TF_VERSION=2.0.0 TF_KERAS_VIS_MAX_STEPS=3
+  - TF_VERSION=2.0.1 TF_KERAS_VIS_MAX_STEPS=3
+  - TF_VERSION=2.1.0 TF_KERAS_VIS_MAX_STEPS=3
+install:
+  - pip install -U pip
+  - pip install -U --force-reinstall -e .[development,examples] tensorflow==$TF_VERSION
+script:
+  - PYTHONPATH=$PWD:$PYTHONPATH py.test
+  - jupyter-nbconvert --ExecutePreprocessor.timeout=600 --to notebook --execute examples/attentions.ipynb
+  - jupyter-nbconvert --ExecutePreprocessor.timeout=600 --to notebook --execute examples/visualize_dense_layer.ipynb
+  - jupyter-nbconvert --ExecutePreprocessor.timeout=600 --to notebook --execute examples/visualize_conv_filters.ipynb

Dockerfile

@@ -0,0 +1,19 @@
+FROM tensorflow/tensorflow:2.1.0-py3
+
+# Default ENV Settings
+ARG TF_KERAS_VIS_VERSION=0.2.0
+
+# Setting for jupyter
+RUN export JUPYTER_HOME=/root/.jupyter                           && \
+    export JUPYTER_CONF=$JUPYTER_HOME/jupyter_notebook_config.py && \
+    mkdir -p $JUPYTER_HOME                                       && \
+    touch $JUPYTER_CONF                                          && \
+    echo 'c.NotebookApp.allow_root = True' >> $JUPYTER_CONF      && \
+    echo 'c.NotebookApp.ip = "0.0.0.0"' >> $JUPYTER_CONF         && \
+    echo 'c.NotebookApp.token = ""' >> $JUPYTER_CONF
+
+# Install essential python libraries
+RUN pip install --no-cache-dir            \
+      tf-keras-vis==$TF_KERAS_VIS_VERSION \
+      numpy scipy imageio pillow          \
+      jupyterlab matplotlib

Dockerfile-gpu

@@ -0,0 +1,19 @@
+FROM tensorflow/tensorflow:2.1.0-gpu-py3
+
+# Default ENV Settings
+ARG TF_KERAS_VIS_VERSION=0.2.0
+
+# Setting for jupyter
+RUN export JUPYTER_HOME=/root/.jupyter                           && \
+    export JUPYTER_CONF=$JUPYTER_HOME/jupyter_notebook_config.py && \
+    mkdir -p $JUPYTER_HOME                                       && \
+    touch $JUPYTER_CONF                                          && \
+    echo 'c.NotebookApp.allow_root = True' >> $JUPYTER_CONF      && \
+    echo 'c.NotebookApp.ip = "0.0.0.0"' >> $JUPYTER_CONF         && \
+    echo 'c.NotebookApp.token = ""' >> $JUPYTER_CONF
+
+# Install essential python libraries
+RUN pip install --no-cache-dir            \
+      tf-keras-vis==$TF_KERAS_VIS_VERSION \
+      numpy scipy imageio pillow          \
+      jupyterlab matplotlib

README.md

@@ -1,5 +1,10 @@
 # tf-keras-vis
-tf-keras-vis is a visualization toolkit for debugging Keras models with Tensorflow 2.0, but not original Keras.
+[![Downloads](https://pepy.tech/badge/tf-keras-vis)](https://pepy.tech/project/tf-keras-vis)
+[![PyPI version](https://badge.fury.io/py/tf-keras-vis.svg)](https://badge.fury.io/py/tf-keras-vis)
+[![Build Status](https://travis-ci.org/keisen/tf-keras-vis.svg?branch=master)](https://travis-ci.org/keisen/tf-keras-vis)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+tf-keras-vis is a visualization toolkit for debugging Keras models with Tensorflow2, but not original Keras.
 
 The features of tf-keras-vis are based on [keras-vis](https://github.com/raghakot/keras-vis), but tf-keras-vis's APIs doesn't have compatibility with keras-vis's because, instead of getting it, we prioritized to get following features.
 
@@ -16,44 +21,29 @@ And then we will add some algorisms such as below.
 
 ## Requirements
 
-* Python 3.6+
-* (tensorflow or tensorflow-gpu) >= 2.0
+* Python 3.5, 3.6 or 3.7
+* tensorflow>=2.0.0
 
 
 ## Installation
 
 * PyPI
 
 ```bash
-$ pip install tf-keras-vis
+$ pip install tf-keras-vis tensorflow
 ```
 
-* Sources
+* Docker
 
-```bash
-$ cd tf-keras-vis
-$ pip install -e .
 ```
-
-Or
-
-```bash
-$ cd tf-keras-vis
-$ python setup.py install
+$ docker pull keisen/tf-keras-vis
 ```
 
-
 ## Usage
 
-T.B.D.
-
-For now, Please see [examples/activation_maximization.ipynb](https://github.com/keisen/tf-keras-vis/blob/master/examples/activation_maximization.ipynb) and [examples/attention.ipynb](https://github.com/keisen/tf-keras-vis/blob/master/examples/attention.ipynb).
-When you want to run jupyter notebook, we recommend that install tf-keras-vis such as follow:
+For now, Please see [examples/attentions.ipynb](https://github.com/keisen/tf-keras-vis/blob/master/examples/attentions.ipynb), [examples/visualize_dense_layer.ipynb](https://github.com/keisen/tf-keras-vis/blob/master/examples/visualize_dense_layer.ipynb) and [examples/visualize_conv_filters.ipynb](https://github.com/keisen/tf-keras-vis/blob/master/examples/visualize_conv_filters.ipynb).
 
-```bash
-$ cd tf-keras-vis
-$ pip install -e .[examples]
-```
+T.B.D.
 
 
 ## API Documentation
@@ -63,6 +53,6 @@ T.B.D
 
 ## Known Issues
 
-* With InceptionV3 ActivationMaximization doesn't work well, that's, it might generate meanninglessly bulr image.
-* With cascading model gradcam doesn't work well, that's, it might occur some error.
-* Unsupport `channels-first` models and datas.
+* With InceptionV3, ActivationMaximization doesn't work well, that's, it might generate meanninglessly bulr image.
+* With cascading model, Gradcam doesn't work well, that's, it might occur some error.
+* Unsupported `channels-first` models and datas.

setup.cfg

@@ -4,9 +4,9 @@ description-file = README.md
 [flake8]
 exclude =
     .git
-    .venv
     __pycache__
     dist/*
+    docker/*
     examples/*
 max-line-length = 100
 max-complexity = 10
@@ -18,10 +18,10 @@ spaces_before_comment = 2
 [isort]
 skip =
     .git
-    .venv
     __pycache__
-    build
-    deprecated
+    dist
+    docker
+    examples
 
 [pyls]
 configurationSources = ['flake8']
@@ -31,13 +31,12 @@ addopts =
     -v
     --durations=10
     --cache-clear
-    --cov=ml/
+    --cov=tf_keras_vis/
     --cov-report=term-missing
 
 [coverage:run]
 omit =
     tests/*
-    .venv/*
     __pycache__/*
 
 [coverage:report]

setup.py

@@ -5,7 +5,7 @@
 
 setup(
     name="tf-keras-vis",
-    version="0.1.0",
+    version="0.2.0",
     author="keisen",
     author_email="[email protected]",
     description="Neural network visualization toolkit for tf.keras",
@@ -18,15 +18,11 @@
         "License :: OSI Approved :: MIT License",
         "Operating System :: OS Independent",
     ],
-    python_requires='>=3.6',
+    python_requires='>=3.5, <3.8',
     install_requires=['numpy', 'scipy', 'imageio', 'pillow'],
     extras_require={
-        'cpu': ['tensorflow >= 2.0'],
-        'gpu': ['tensorflow-gpu >= 2.0'],
-        'development': [
-            'flake8', 'isort==4.3.*', 'yapf==0.28.*', 'pytest', 'pytest-pep8', 'pytest-xdist',
-            'pytest-cov'
-        ],
+        'development':
+        ['flake8', 'isort', 'yapf', 'pytest', 'pytest-pep8', 'pytest-xdist', 'pytest-cov'],
         'examples': ['jupyterlab', 'matplotlib'],
     },
     include_package_data=True,

tests/tf-keras-vis/test__init__.py

@@ -0,0 +1,40 @@
+import numpy as np
+import pytest
+import tensorflow as tf
+from tensorflow.keras.layers import Dense
+from tensorflow.keras.models import Sequential
+
+from tf_keras_vis import ModelVisualization
+
+
+@pytest.fixture(scope="function", autouse=True)
+def model():
+    return Sequential([Dense(5, input_shape=(3, )), Dense(2, activation='softmax')])
+
+
+class MockVisualizer(ModelVisualization):
+    def __call__(self):
+        pass
+
+
+def change_activation(model):
+    model.layers[-1].activation = tf.keras.activations.linear
+
+
+def test__init__(model):
+    mock = MockVisualizer(model)
+    assert mock.model != model
+    assert np.array_equal(mock.model.get_weights()[0], model.get_weights()[0])
+
+    mock = MockVisualizer(model, clone=False)
+    assert mock.model == model
+
+    mock = MockVisualizer(model, change_activation)
+    assert mock.model != model
+    assert mock.model.layers[-1].activation == tf.keras.activations.linear
+    assert model.layers[-1].activation == tf.keras.activations.softmax
+
+    another_model = Sequential([Dense(5, input_shape=(3, ))])
+    mock = MockVisualizer(model, lambda m: another_model)
+    assert mock.model != model
+    assert mock.model == another_model