awslabs
diff --git a/‎.travis.yml‎
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diff --git a/‎ISSUE_TEMPLATE.md‎
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diff --git a/‎LICENSE‎
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diff --git a/‎README.md‎
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diff --git a/‎benchmark/README.md‎
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diff --git a/‎benchmark/scripts/benchmark_resnet.py‎
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diff --git a/‎benchmark/scripts/run_mxnet_backend.sh‎
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diff --git a/‎benchmark/scripts/run_tf_backend.sh‎
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diff --git a/‎docs/__init__.py‎ b/‎docs/__init__.py‎
@@ -45,6 +45,7 @@ install:
   - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION nose scipy matplotlib pandas pytest h5py
   - source activate test-environment
   - pip install --only-binary=numpy,scipy numpy nose scipy matplotlib h5py theano
+  - pip install keras_applications keras_preprocessing
   - conda install mkl mkl-service
 
   # set library path
@@ -60,17 +61,17 @@ install:
   - pip install -e .[tests]
 
   # install TensorFlow (CPU version).
-  - pip install tensorflow
+  - pip install tensorflow==1.7
 
   # install Apache MXNet (CPU version).
   - pip install mxnet
   - pip install --upgrade numpy
 
   # install cntk
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
-      pip install https://cntk.ai/PythonWheel/CPU-Only/cntk-2.3.1-cp27-cp27mu-linux_x86_64.whl;
+      pip install https://cntk.ai/PythonWheel/CPU-Only/cntk-2.5.1-cp27-cp27mu-linux_x86_64.whl;
     elif [[ "$TRAVIS_PYTHON_VERSION" == "3.6" ]]; then
-      pip install https://cntk.ai/PythonWheel/CPU-Only/cntk-2.3.1-cp36-cp36m-linux_x86_64.whl;
+      pip install https://cntk.ai/PythonWheel/CPU-Only/cntk-2.5.1-cp36-cp36m-linux_x86_64.whl;
     fi
 
   # install pydot for visualization tests
 
@@ -3,7 +3,7 @@ Please make sure that the boxes below are checked before you submit your issue.
 Thank you!
 
 - [ ] Check that you are up-to-date with the master branch of Keras. You can update with:
-pip install git+git://github.com/keras-team/keras.git --upgrade --no-deps
+pip install git+git://github.com/awslabs/keras-apache-mxnet.git --upgrade --no-deps
 
 - [ ] If running on TensorFlow, check that you are up-to-date with the latest version. The installation instructions can be found [here](https://www.tensorflow.org/get_started/os_setup).
 
 
@@ -16,10 +16,6 @@ All contributions by Amazon:
 Copyright (c) 2017 Amazon.com, Inc. or its affiliates
 All rights reserved.
 
-All contributions by Amazon:
-Copyright (c) 2017 Amazon.com, Inc. or its affiliates
-All rights reserved.
-
 All other contributions:
 Copyright (c) 2015 - 2018, the respective contributors.
 All rights reserved.
 
@@ -35,7 +35,7 @@ Keras is compatible with: __Python 2.7-3.6__.
 
 - __User friendliness.__ Keras is an API designed for human beings, not machines. It puts user experience front and center. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear and actionable feedback upon user error.
 
-- __Modularity.__ A model is understood as a sequence or a graph of standalone, fully-configurable modules that can be plugged together with as little restrictions as possible. In particular, neural layers, cost functions, optimizers, initialization schemes, activation functions, regularization schemes are all standalone modules that you can combine to create new models.
+- __Modularity.__ A model is understood as a sequence or a graph of standalone, fully-configurable modules that can be plugged together with as few restrictions as possible. In particular, neural layers, cost functions, optimizers, initialization schemes, activation functions, regularization schemes are all standalone modules that you can combine to create new models.
 
 - __Easy extensibility.__ New modules are simple to add (as new classes and functions), and existing modules provide ample examples. To be able to easily create new modules allows for total expressiveness, making Keras suitable for advanced research.
 
@@ -165,7 +165,7 @@ sudo python setup.py install
 ------------------
 
 
-## Switching from MXNet to TensorFlow, CNTK or Theano
+## Configuring your Keras backend
 
 By default, Keras-MXNet will use MXNet as its tensor manipulation library. [Follow these instructions](https://keras.io/backend/) to configure the Keras backend.
 
 
@@ -260,4 +260,4 @@ For TensorFlow backend benchmarks:
 ## References
 
 * [TensorFlow Keras Benchmarks](https://github.com/tensorflow/benchmarks/tree/keras-benchmarks/scripts/keras_benchmarks)
-* [lstm_text_generation.py](https://github.com/keras-team/keras/blob/master/examples/lstm_text_generation.py)
+* [lstm_text_generation.py](https://github.com/keras-team/keras/blob/master/examples/lstm_text_generation.py)
@@ -1,12 +1,10 @@
 '''Trains a ResNet on the ImageNet/CIFAR10 dataset.
 Credit:
 Script modified from examples/cifar10_resnet.py
-
 Reference:
 ResNet v1
 [a] Deep Residual Learning for Image Recognition
 https://arxiv.org/pdf/1512.03385.pdf
-
 ResNet v2
 [b] Identity Mappings in Deep Residual Networks
 https://arxiv.org/pdf/1603.05027.pdf
 
@@ -32,4 +32,4 @@ echo -e "Running tests with the following config:\n$(cat ~/.keras/keras.json)"
 
 dir=`pwd`
 
-python $dir/run_benchmark.py  --pwd=$dir --mode="$1" --model_name="$2" --dry_run=True --inference="$3" --epochs="$4"
+python $dir/run_benchmark.py  --pwd=$dir --mode="$1" --model_name="$2" --dry_run=True --inference="$3" --epochs="$4"
@@ -32,4 +32,4 @@ echo -e "Running tests with the following config:\n$(cat ~/.keras/keras.json)"
 
 dir=`pwd`
 
-python $dir/run_benchmark.py  --pwd=$dir --mode="$1" --model_name="$2" --dry_run=True --inference="$3" --epochs="$4"
+python $dir/run_benchmark.py  --pwd=$dir --mode="$1" --model_name="$2" --dry_run=True --inference="$3" --epochs="$4"
Original file line number	Diff line number	Diff line change
`@@ -32,4 +32,4 @@ echo -e "Running tests with the following config:\n$(cat ~/.keras/keras.json)"`
`32`	`32`
`33`	`33`	dir=`pwd`
`34`	`34`
`35`		`-python $dir/run_benchmark.py --pwd=$dir --mode="$1" --model_name="$2" --dry_run=True --inference="$3" --epochs="$4"`
	`35`	`+python $dir/run_benchmark.py --pwd=$dir --mode="$1" --model_name="$2" --dry_run=True --inference="$3" --epochs="$4"`