Fix dependencies

.travis.yml

@@ -5,10 +5,8 @@ env:
   global:
     - COVERALLS_PARALLEL=true
   matrix:
-    - KERAS_BACKEND=tensorflow TF_KERAS=1 TF_2=1
-    - KERAS_BACKEND=tensorflow TF_KERAS=1 TF_EAGER=1
-    - KERAS_BACKEND=tensorflow TF_KERAS=1
     - KERAS_BACKEND=tensorflow
+    - KERAS_BACKEND=tensorflow TF_KERAS=1
 install:
   - wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
   - bash miniconda.sh -b -p $HOME/miniconda
@@ -22,12 +20,10 @@ install:
   - pip install --upgrade pip
   - pip install -r requirements.txt
   - pip install -r requirements-dev.txt
-  - if [[ $TF_2 == "1" ]]; then pip install tensorflow==2.0.0-beta1; fi
   - pip install coveralls
 script:
   - ./test.sh
 after_success:
   coveralls
 notifications:
-  webhooks:
-    - https://coveralls.io/webhook
+  webhooks: https://coveralls.io/webhook

README.md

@@ -2,22 +2,15 @@
 
 [![Travis](https://travis-ci.org/CyberZHG/keras-lr-multiplier.svg)](https://travis-ci.org/CyberZHG/keras-lr-multiplier)
 [![Coverage](https://coveralls.io/repos/github/CyberZHG/keras-lr-multiplier/badge.svg?branch=master)](https://coveralls.io/github/CyberZHG/keras-lr-multiplier)
-[![Version](https://img.shields.io/pypi/v/keras-lr-multiplier.svg)](https://pypi.org/project/keras-lr-multiplier/)
-![Downloads](https://img.shields.io/pypi/dm/keras-lr-multiplier.svg)
 
-![](https://img.shields.io/badge/keras-tensorflow-blue.svg)
-![](https://img.shields.io/badge/keras-tf.keras-blue.svg)
-![](https://img.shields.io/badge/keras-tf.keras/eager-blue.svg)
-![](https://img.shields.io/badge/keras-tf.keras/2.0_beta-blue.svg)
-
-\[[中文](https://github.com/CyberZHG/keras-lr-multiplier/blob/master/README.zh-CN.md)|[English](https://github.com/CyberZHG/keras-lr-multiplier/blob/master/README.md)\]
+**This repo is outdated and will no longer be maintained.**
 
 Learning rate multiplier wrapper for optimizers.
 
 ## Install
 
 ```bash
-pip install keras-lr-multiplier
+pip install git+https://github.com/CyberZHG/keras-lr-multiplier.git
 ```
 
 ## Usage

keras_lr_multiplier/__init__.py

@@ -1,3 +1,3 @@
 from .multiplier import *
 
-__version__ = '0.8.0'
+__version__ = '0.9.0'

keras_lr_multiplier/backend.py

@@ -2,37 +2,23 @@
 from distutils.util import strtobool
 
 __all__ = [
-    'keras', 'utils', 'activations', 'applications', 'backend', 'datasets', 'engine',
-    'layers', 'preprocessing', 'wrappers', 'callbacks', 'constraints', 'initializers',
-    'metrics', 'models', 'losses', 'optimizers', 'regularizers', 'TF_KERAS', 'EAGER_MODE'
+    'keras', 'utils', 'activations', 'backend',
+    'layers', 'callbacks', 'constraints', 'initializers',
+    'metrics', 'models', 'losses', 'optimizers', 'regularizers', 'TF_KERAS',
 ]
 
-TF_KERAS = False
-EAGER_MODE = False
+TF_KERAS = strtobool(os.environ.get('TF_KERAS', '0'))
 
-if strtobool(os.environ.get('TF_KERAS', '0')):
+if TF_KERAS:
     import tensorflow as tf
-    from tensorflow.python import keras
-    TF_KERAS = True
-    if strtobool(os.environ.get('TF_EAGER', '0')):
-        try:
-            tf.enable_eager_execution()
-            raise AttributeError()
-        except AttributeError as e:
-            pass
-    EAGER_MODE = tf.executing_eagerly()
+    keras = tf.keras
 else:
     import keras
 
 utils = keras.utils
 activations = keras.activations
-applications = keras.applications
 backend = keras.backend
-datasets = keras.datasets
-engine = keras.engine
 layers = keras.layers
-preprocessing = keras.preprocessing
-wrappers = keras.wrappers
 callbacks = keras.callbacks
 constraints = keras.constraints
 initializers = keras.initializers

keras_lr_multiplier/multiplier.py

@@ -1,7 +1,6 @@
 from .backend import optimizers
 from .backend import backend as K
 
-
 __all__ = ['LRMultiplier']
 
 
@@ -25,6 +24,7 @@ def __init__(self,
             self.lr_attr = 'learning_rate'
         else:
             self.lr_attr = 'lr'
+        self.updates, self.weights = [], []
 
     @property
     def lr(self):
@@ -75,9 +75,9 @@ def get_updates(self, loss, params):
             setattr(self, self.lr_attr, lr)
             with K.name_scope('Group_{}'.format(i)):
                 self.updates += self.optimizer.get_updates(loss, params)
-            print(self.multipliers, i, self.optimizer.weights)
+            names = set(map(lambda x: x.name, self.weights))
             for w in self.optimizer.weights:
-                if w not in self.weights:
+                if w.name not in names:
                     self.weights.append(w)
         setattr(self, self.lr_attr, origin_lr)
 

requirements-dev.txt

@@ -1,7 +1,7 @@
 setuptools>=38.6.0
 twine>=1.11.0
 wheel>=0.31.0
-tensorflow
+tensorflow==1.13.2
 nose
 pycodestyle
 coverage

requirements.txt

@@ -1,2 +1,3 @@
 numpy
-Keras
+Keras==2.2.4
+h5py==2.10.0