Restructuring examples and tutorials

.gitattributes

@@ -119,8 +119,8 @@ TIMIT*.statelist text
 TIMIT*.tfsa text
 TIMIT*.transitions text
 
-Examples/Text/ATIS/Data/ATIS.* text
-Examples/Text/ATIS/*.wl text
+Examples/LanguageUnderstanding/ATIS/Data/ATIS.* text
+Examples/LanguageUnderstanding/ATIS/BrainScript/*.wl text
 
 Examples/SequenceToSequence/CMUDict/Data/cmudict-0.7b* text
 

.gitignore

@@ -27,6 +27,34 @@ Examples/Image/DataSets/Pascal/VOC*
 Examples/Image/DataSets/Pascal/selective_search_data*
 Examples/Image/Detection/FastRCNN/proc/
 
+Source/Readers/ImageReader/ImageTransformers - Copy.cpp
+Source/Readers/ImageReader/ImageTransformers - Copy.h
+Examples/Evaluation/packages/
+Examples/Image/Classification/ConvNet/Ndl/
+Examples/Image/DataSets/CIFAR-10/CIFAR-10_mean.xml
+Examples/Image/DataSets/CIFAR-10/Test_cntk_text.txt
+Examples/Image/DataSets/CIFAR-10/Train_cntk_text.txt
+Examples/Image/DataSets/CIFAR-10/cifar-10-batches-py/
+Examples/Image/DataSets/CIFAR-10/test/
+Examples/Image/DataSets/CIFAR-10/test_map.txt
+Examples/Image/DataSets/CIFAR-10/test_regrLabels.txt
+Examples/Image/DataSets/CIFAR-10/train/
+Examples/Image/DataSets/CIFAR-10/train_map.txt
+Examples/Image/DataSets/CIFAR-10/train_regrLabels.txt
+Examples/Image/DataSets/MNIST/Test-28x28_cntk_text.txt
+Examples/Image/DataSets/MNIST/Train-28x28_cntk_text.txt
+Examples/Image/DataSets/grocery/
+Examples/Image/Detection/FastRCNN/data/
+Examples/Image/Detection/FastRCNN/fastrcnn_ResNet_AvgPooling.cntk
+Examples/Image/Detection/FastRCNN/fastrcnn_Resnet_Roi_between_ConvLayers.cntk
+Examples/Image/Detection/FastRCNN/fastrcnn_master.cntk
+Examples/Image/Detection/FastRCNN/testConfigs/
+Examples/Image/PretrainedModels/
+bindings/python/tutorials/.ipynb_checkpoints/
+bindings/python/tutorials/atis.test.ctf
+bindings/python/tutorials/atis.train.ctf
+bindings/python/tutorials/data/
+
 
 
 # Enable "build/" folder in the NuGet Packages folder since NuGet packages use it for MSBuild targets

Examples/Evaluation/CSEvalClient/Program.cs

@@ -244,7 +244,7 @@ private static void EvaluateNetworkSingleLayer()
             {
                 // The examples assume the executable is running from the data folder
                 // We switch the current directory to the data folder (assuming the executable is in the <CNTK>/x64/Debug|Release folder
-                string workingDirectory = Path.Combine(initialDirectory, @"..\..\Examples\Other\Simple2d\Config");
+                string workingDirectory = Path.Combine(initialDirectory, @"..\..\Tests\EndToEndTests\Simple2d");
                 Environment.CurrentDirectory = initialDirectory;
 
                 List<float> outputs;
@@ -291,7 +291,7 @@ private static void EvaluateNetworkSingleLayerNoInput()
             {
                 // The examples assume the executable is running from the data folder
                 // We switch the current directory to the data folder (assuming the executable is in the <CNTK>/x64/Debug|Release folder
-                string workingDirectory = Path.Combine(initialDirectory, @"..\..\Examples\Other\Simple2d\Config");
+                string workingDirectory = Path.Combine(initialDirectory, @"..\..\Tests\EndToEndTests\Simple2d");
                 Environment.CurrentDirectory = initialDirectory;
 
                 List<float> outputs;

bindings/python/examples/CifarConvNet/CifarConvNet.py → Examples/Image/Classification/ConvNet/Python/CifarConvNet.py

@@ -23,7 +23,7 @@
 # Paths relative to current python file.
 #
 abs_path   = os.path.dirname(os.path.abspath(__file__))
-cntk_path  = os.path.normpath(os.path.join(abs_path, "..", "..", "..", ".."))
+cntk_path  = os.path.normpath(os.path.join(abs_path, "..", "..", "..", "..", ".."))
 data_path  = os.path.join(cntk_path, "Examples", "Image", "DataSets", "CIFAR-10")
 model_path = os.path.join(abs_path, "Models")
 

Examples/Image/Classification/MLP/MLP_MNIST.cntk → Examples/Image/Classification/MLP/BrainScript/MLP_MNIST.cntk

@@ -4,7 +4,7 @@ command = trainNetwork:testNetwork
 
 precision = "float"; traceLevel = 1 ; deviceId = "auto"
 
-rootDir = "../.." ; dataDir = "$rootDir$/DataSets/MNIST" ;
+rootDir = "../../.." ; dataDir = "$rootDir$/DataSets/MNIST" ;
 outputDir = "./Output" ;
 
 modelPath = "$outputDir$/Models/MLP_MNIST"

bindings/python/examples/MNIST/SimpleMNIST.py → Examples/Image/Classification/MLP/Python/SimpleMNIST.py

@@ -14,8 +14,8 @@
 from cntk.ops import input_variable, cross_entropy_with_softmax, classification_error, relu, element_times, constant
 
 abs_path = os.path.dirname(os.path.abspath(__file__))
-sys.path.append(os.path.join(abs_path, "..", ".."))
-from examples.common.nn import fully_connected_classifier_net, print_training_progress
+sys.path.append(os.path.join(abs_path, "..", "..", "..", "..", "..", "Tests", "EndToEndTests", "CNTKv2Python", "Examples", "common"))
+from nn import fully_connected_classifier_net, print_training_progress
 
 def check_path(path):
     if not os.path.exists(path):

bindings/python/examples/CifarResNet/CifarResNet.py → Examples/Image/Classification/ResNet/Python/CifarResNet.py

@@ -23,7 +23,7 @@
 # Paths relative to current python file.
 #
 abs_path   = os.path.dirname(os.path.abspath(__file__))
-cntk_path  = os.path.normpath(os.path.join(abs_path, "..", "..", "..", ".."))
+cntk_path  = os.path.normpath(os.path.join(abs_path, "..", "..", "..", "..", ".."))
 data_path  = os.path.join(cntk_path, "Examples", "Image", "DataSets", "CIFAR-10")
 model_path = os.path.join(abs_path, "Models")
 

bindings/python/examples/Distributed/CifarResNet_Distributed.py → Examples/Image/Classification/ResNet/Python/CifarResNet_Distributed.py

@@ -20,9 +20,9 @@
 from cntk.initializer import he_normal, glorot_uniform
 
 abs_path = os.path.dirname(os.path.abspath(__file__))
-sys.path.append(os.path.join(abs_path, "..", ".."))
-from examples.CifarResNet.CifarResNet import create_reader, create_resnet_model
-from examples.common.nn import conv_bn_relu_layer, conv_bn_layer, linear_layer, print_training_progress
+sys.path.append(os.path.join(abs_path, "..", "..", "..", "..", "..", "Tests", "EndToEndTests", "CNTKv2Python", "Examples", "common"))
+from CifarResNet import create_reader, create_resnet_model
+from nn import conv_bn_relu_layer, conv_bn_layer, linear_layer, print_training_progress
 
 TRAIN_MAP_FILENAME = 'train_map.txt'
 MEAN_FILENAME = 'CIFAR-10_mean.xml'

Examples/Image/GettingStarted/README.md

@@ -1,4 +1,4 @@
-# CNTK Examples: Image/Getting Started
+# CNTK Examples: Image - Getting Started
 
 ## Overview
 

Examples/Text/ATIS/ATIS.cntk → Examples/LanguageUnderstanding/ATIS/BrainScript/ATIS.cntk

@@ -2,7 +2,7 @@
 # An LSTM model is built to tag each word in sentences with its semantic label.
 
 WorkDir = work
-DataDir = Data
+DataDir = ../Data
 
 makeMode = false
 modelPath = $WorkDir$/ATIS.slot.lstm

Examples/Text/ATIS/README.md → Examples/LanguageUnderstanding/ATIS/BrainScript/README.md

@@ -1,6 +1,6 @@
 # Build Language Understanding Models with CNTK
 
-This example demonstrates how to use build language understanding model with CNTK using ATIS data set. The recipeice in this example are in BrainScript. For Python click [here](https://github.com/Microsoft/CNTK/blob/master/bindings/python/examples/LanguageUnderstanding/LanguageUnderstanding.py).  This example is similar to 
+This example demonstrates how to use build language understanding model with CNTK using ATIS data set. The recipes in this example are in BrainScript. For Python click [here](https://github.com/Microsoft/CNTK/blob/master/bindings/python/examples/LanguageUnderstanding/LanguageUnderstanding.py).  This example is similar to 
 [SLU example](https://github.com/Microsoft/CNTK/tree/master/Examples/Text/Miscellaneous/SLU). They are different in that
   - CNTKTextFormatReader is used here, instead of LUSequenceReader
   - With CNTKTextFormatReader, the input format is much more flexible. In the example setting, sparse contextual feature vectors are explored

bindings/python/examples/LanguageUnderstanding/LanguageUnderstanding.py → Examples/LanguageUnderstanding/ATIS/Python/LanguageUnderstanding.py

@@ -20,7 +20,7 @@
 ########################
 
 cntk_dir = os.path.dirname(os.path.abspath(__file__)) + "/../../../.."  # data resides in the CNTK folder
-data_dir = cntk_dir + "/Examples/Tutorials/SLUHandsOn"                  # under Examples/Tutorials
+data_dir = cntk_dir + "/Examples/LanguageUnderstanding/ATIS/Data"       # under Examples/LanguageUnderstanding/ATIS
 vocab_size = 943 ; num_labels = 129 ; num_intents = 26    # number of words in vocab, slot labels, and intent labels
 
 model_dir = "./Models"