update tensorgraph to tensorgraphx

Author: hyciswu

.travis.yml

@@ -9,17 +9,17 @@ install:
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
       pip install --only-binary=numpy,scipy numpy nose scipy pytest sklearn;
       pip install tensorflow;
-      pip install git+https://github.com/hycis/TensorGraph.git@master;
+      pip install git+https://github.com/hycis/TensorGraphX.git@master;
     fi
 
   - if [[ "$TRAVIS_PYTHON_VERSION" == "3.5" ]]; then
       pip3 install --only-binary=numpy,scipy numpy nose scipy pytest sklearn;
       pip3 install tensorflow;
-      pip3 install git+https://github.com/hycis/TensorGraph.git@master;
+      pip3 install git+https://github.com/hycis/TensorGraphX.git@master;
     fi
 
 script:
-  - echo "TensorGraph Testing.."
+  - echo "TensorGraphX Testing.."
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
       python -m pytest test;
     fi

LICENCE

@@ -1,4 +1,4 @@
-Copyright 2015 The TensorGraph Authors.  All rights reserved.
+Copyright 2015 The TensorGraphX Authors.  All rights reserved.
 
                                  Apache License
                            Version 2.0, January 2004
@@ -188,7 +188,7 @@ Copyright 2015 The TensorGraph Authors.  All rights reserved.
       same "printed page" as the copyright notice for easier
       identification within third-party archives.
 
-   Copyright 2015, The TensorGraph Authors.
+   Copyright 2015, The TensorGraphX Authors.
 
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.

MANIFEST.in

@@ -1,2 +1,2 @@
 include README.md LICENCE
-recursive-include tensorgraph *.py
+recursive-include tensorgraphx *.py

README.md

@@ -1,11 +1,11 @@
 
 import tensorflow as tf
-import tensorgraph as tg
-from tensorgraph.layers import Reshape, Embedding, Conv2D, RELU, Linear, Flatten, ReduceSum, Softmax
+import tensorgraphx as tg
+from tensorgraphx.layers import Reshape, Embedding, Conv2D, RELU, Linear, Flatten, ReduceSum, Softmax
 from nltk.tokenize import RegexpTokenizer
 from nlpbox import CharNumberEncoder, CatNumberEncoder
-from tensorgraph.utils import valid, split_df, make_one_hot
-from tensorgraph.cost import entropy, accuracy
+from tensorgraphx.utils import valid, split_df, make_one_hot
+from tensorgraphx.cost import entropy, accuracy
 import pandas
 import numpy as np
 
@@ -75,7 +75,7 @@ def tweets(word_len, sent_len, train_valid_ratio=[5,1]):
 
 
 def train():
-    from tensorgraph.trainobject import train as mytrain
+    from tensorgraphx.trainobject import train as mytrain
     with tf.Session() as sess:
         word_len = 20
         sent_len = 50

examples/charcnn_text_classifier.py

@@ -7,15 +7,15 @@
 
 from __future__ import division, print_function, absolute_import
 
-from tensorgraph.layers import Conv2D, RELU, MaxPooling, LRN, Tanh, Dropout, \
+from tensorgraphx.layers import Conv2D, RELU, MaxPooling, LRN, Tanh, Dropout, \
                                Softmax, Flatten, Linear, AvgPooling, \
                                Lambda, BatchNormalization, IdentityBlock, \
                                TransitionLayer, DenseNet
-from tensorgraph.utils import same, valid, same_nd, valid_nd
-import tensorgraph as tg
+from tensorgraphx.utils import same, valid, same_nd, valid_nd
+import tensorgraphx as tg
 import tensorflow as tf
-from tensorgraph.cost import entropy, accuracy, mse
-from tensorgraph.dataset import Mnist, Cifar10
+from tensorgraphx.cost import entropy, accuracy, mse
+from tensorgraphx.dataset import Mnist, Cifar10
 from tensorflow.python.framework import ops
 import numpy as np
 
@@ -158,7 +158,7 @@ def train():
 
 
 def train_with_trainobject():
-    from tensorgraph.trainobject import train as mytrain
+    from tensorgraphx.trainobject import train as mytrain
     config = tf.ConfigProto()
     config.gpu_options.allow_growth = True
     with tf.Session(config = config) as sess:
@@ -187,7 +187,7 @@ def train_with_trainobject():
 
 
 def train_with_VGG():
-    from tensorgraph.trainobject import train as mytrain
+    from tensorgraphx.trainobject import train as mytrain
     config = tf.ConfigProto()
     config.gpu_options.allow_growth = True
     with tf.Session(config = config) as sess:
@@ -196,7 +196,7 @@ def train_with_VGG():
         _, nclass = y_train.shape
         print('X max', np.max(X_train))
         print('X min', np.min(X_train))
-        from tensorgraph.layers import VGG19
+        from tensorgraphx.layers import VGG19
         seq = tg.Sequential()
         layer = VGG19(input_channels=c, input_shape=(h,w))
         seq.add(layer)
@@ -223,7 +223,7 @@ def train_with_VGG():
 
 
 def train_with_Resnet():
-    from tensorgraph.trainobject import train as mytrain
+    from tensorgraphx.trainobject import train as mytrain
     config = tf.ConfigProto()
     config.gpu_options.allow_growth = True
     with tf.Session(config = config) as sess:
@@ -268,7 +268,7 @@ def train_with_Resnet():
 
 
 def train_with_Densenet():
-    from tensorgraph.trainobject import train as mytrain
+    from tensorgraphx.trainobject import train as mytrain
     config = tf.ConfigProto()
     config.gpu_options.allow_growth = True
     with tf.Session(config = config) as sess:

examples/cifar10_allcnn.py

@@ -1,9 +1,9 @@
 
 import tensorflow as tf
 import numpy as np
-from tensorgraph import Graph, StartNode, HiddenNode, EndNode
-from tensorgraph.layers import Linear, RELU, Concat, Mean, Sum
-from tensorgraph import ProgressBar, SequentialIterator
+from tensorgraphx import Graph, StartNode, HiddenNode, EndNode
+from tensorgraphx.layers import Linear, RELU, Concat, Mean, Sum
+from tensorgraphx import ProgressBar, SequentialIterator
 
 
 def model():

examples/example.py

@@ -1,12 +1,12 @@
 
-from tensorgraph.node import StartNode, HiddenNode, EndNode
+from tensorgraphx.node import StartNode, HiddenNode, EndNode
 import tensorflow as tf
-from tensorgraph.layers.linear import Linear
-from tensorgraph.layers.activation import RELU, Softmax
-from tensorgraph.layers.merge import Concat, Mean, Sum
-from tensorgraph.graph import Graph
+from tensorgraphx.layers.linear import Linear
+from tensorgraphx.layers.activation import RELU, Softmax
+from tensorgraphx.layers.merge import Concat, Mean, Sum
+from tensorgraphx.graph import Graph
 import numpy as np
-from tensorgraph.data_iterator import SequentialIterator
+from tensorgraphx.data_iterator import SequentialIterator
 
 ## params
 x_dim = 50

examples/hierachical_softmax.py

@@ -11,13 +11,13 @@
 
 from __future__ import division, print_function, absolute_import
 
-from tensorgraph.layers import Conv2D, RELU, MaxPooling, LRN, Tanh, Dropout, \
+from tensorgraphx.layers import Conv2D, RELU, MaxPooling, LRN, Tanh, Dropout, \
                                Softmax, Flatten, Linear, BatchNormalization
-from tensorgraph.utils import same
-import tensorgraph as tg
+from tensorgraphx.utils import same
+import tensorgraphx as tg
 import tensorflow as tf
-from tensorgraph.cost import entropy, accuracy
-from tensorgraph.dataset import Mnist
+from tensorgraphx.cost import entropy, accuracy
+from tensorgraphx.dataset import Mnist
 from tensorflow.python.framework import ops
 
 def model():
@@ -135,7 +135,7 @@ def train():
 
 
 def train_with_trainobject():
-    from tensorgraph.trainobject import train as mytrain
+    from tensorgraphx.trainobject import train as mytrain
     with tf.Session() as sess:
         seq = model()
         X_train, y_train, X_test, y_test = Mnist(flatten=False, onehot=True, binary=True, datadir='.')

examples/mnist_cnn.py

@@ -1,5 +1,5 @@
 
-import tensorgraph as tg
+import tensorgraphx as tg
 import numpy as np
 import tensorflow as tf
 import horovod.tensorflow as hvd