Merge branch 'master' of https://github.com/Microsoft/CNTK into fseid…

…e/seq2seqsample

CNTK.sln

@@ -805,7 +805,7 @@ Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKTextFormatReader", "Sou
 		{F0A9637C-20DA-42F0-83D4-23B4704DE602} = {F0A9637C-20DA-42F0-83D4-23B4704DE602}
 	EndProjectSection
 EndProject
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "ExperimentalHTKMLFReader", "Source\Readers\ExperimentalHTKMLFReader\ExperimentalHTKMLFReader.vcxproj", "{7B7A51ED-AA8E-4660-A805-D50235A02120}"
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "HTKDeserializers", "Source\Readers\HTKDeserializers\HTKDeserializers.vcxproj", "{7B7A51ED-AA8E-4660-A805-D50235A02120}"
 	ProjectSection(ProjectDependencies) = postProject
 		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
 		{86883653-8A61-4038-81A0-2379FAE4200A} = {86883653-8A61-4038-81A0-2379FAE4200A}
@@ -1052,7 +1052,7 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "SequenceToSequence", "Seque
 EndProject
 Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CPPEvalClient", "Source\Extensibility\CPPEvalClient\CPPEvalClient.vcxproj", "{578D52A0-3928-4405-A016-F016E8B49031}"
 EndProject
-Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "ExperimentalHtkmlfReader", "ExperimentalHtkmlfReader", "{977ECCB7-598D-4548-B95B-BACA9CC7D98B}"
+Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "HtkDeserializers", "HtkDeserializers", "{977ECCB7-598D-4548-B95B-BACA9CC7D98B}"
 EndProject
 Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "DNN", "DNN", "{1DBB2575-F5C8-43F4-B982-D05D6ADC2F9B}"
 EndProject
@@ -1064,13 +1064,13 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "SVD", "SVD", "{BA6A65C5-92A
 EndProject
 Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "FullUtterance", "FullUtterance", "{3BDF52CD-7F3C-42BC-AB78-CF5BBC5F4AB4}"
 	ProjectSection(SolutionItems) = preProject
-		Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\baseline.cpu.txt = Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\baseline.cpu.txt
-		Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\baseline.gpu.txt = Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\baseline.gpu.txt
-		Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\baseline.windows.cpu.txt = Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\baseline.windows.cpu.txt
-		Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\baseline.windows.gpu.txt = Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\baseline.windows.gpu.txt
-		Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\cntk.cntk = Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\cntk.cntk
-		Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\run-test = Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\run-test
-		Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\testcases.yml = Tests\EndToEndTests\Speech\ExperimentalHtkmlfReader\LSTM\FullUtterance\testcases.yml
+		Tests\EndToEndTests\Speech\HtkDeserializers\LSTM\FullUtterance\baseline.cpu.txt = Tests\EndToEndTests\Speech\HtkDeserializers\LSTM\FullUtterance\baseline.cpu.txt
+		Tests\EndToEndTests\Speech\HtkDeserializers\LSTM\FullUtterance\baseline.gpu.txt = Tests\EndToEndTests\Speech\HtkDeserializers\LSTM\FullUtterance\baseline.gpu.txt
+		Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\baseline.windows.cpu.txt = Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\baseline.windows.cpu.txt
+		Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\baseline.windows.gpu.txt = Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\baseline.windows.gpu.txt
+		Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\cntk.cntk = Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\cntk.cntk
+		Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\run-test = Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\run-test
+		Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\testcases.yml = Tests\EndToEndTests\Speech\HTKDeserializers\LSTM\FullUtterance\testcases.yml
 	EndProjectSection
 EndProject
 Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Truncated", "Truncated", "{1141DC61-E014-4DEC-9157-F6B1FC055C7A}"

Examples/Image/MNIST/AdditionalFiles/mnist_convert.py

@@ -6,9 +6,6 @@
 import struct
 import numpy as np
 
-sys.path.append("../../../../Source/Readers/CNTKTextFormatReader")
-from uci_to_cntk_text_format_converter import convert
-
 def loadData(src, cimg):
     print ('Downloading ' + src)
     gzfname, h = urllib.urlretrieve(src, './delete.me')
@@ -53,21 +50,28 @@ def loadLabels(src, cimg):
         os.remove(gzfname)
     return res.reshape((cimg, 1))
 
+def load(dataSrc, labelsSrc, cimg):
+    data = loadData(dataSrc, cimg)
+    labels = loadLabels(labelsSrc, cimg)
+    return np.hstack((data, labels))
+
+def savetxt(filename, ndarray):
+    with open(filename, 'w') as f:
+        labels = map(' '.join, np.eye(10, dtype=np.uint).astype(str))
+        for row in ndarray:
+            row_str = row.astype(str)
+            label_str = labels[row[-1]]
+            feature_str = ' '.join(row_str[:-1])
+            f.write('|labels {} |features {}\n'.format(label_str, feature_str))
 
 if __name__ == "__main__":
-    trnData = loadData('http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz', 60000)
-    trnLbl = loadLabels('http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz', 60000)
-    trn = np.hstack((trnLbl, trnData))
+    train = load('http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz',
+        'http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz', 60000)
     print 'Writing train text file...'
-    np.savetxt(r'./../Data/Train-28x28.txt', trn, fmt = '%u', delimiter='\t')
-    convert(r'./../Data/Train-28x28.txt', r'./../Data/Train-28x28_cntk_text.txt', 1, 784, 0, 1, 10)
-    os.remove(r'./../Data/Train-28x28.txt');
+    savetxt(r'./../Data/Train-28x28_cntk_text.txt', train)
     print 'Done.'
-    testData = loadData('http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz', 10000)
-    testLbl = loadLabels('http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz', 10000)
-    test = np.hstack((testLbl, testData))
+    test = load('http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz',
+        'http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz', 10000)
     print 'Writing test text file...'
-    np.savetxt(r'./../Data/Test-28x28.txt', test, fmt = '%u', delimiter='\t')
-    convert(r'./../Data/Test-28x28.txt', r'./../Data/Test-28x28_cntk_text.txt', 1, 784, 0, 1, 10)
-    os.remove(r'./../Data/Test-28x28.txt');
+    savetxt(r'./../Data/Test-28x28_cntk_text.txt', test)
     print 'Done.'

Examples/Image/MNIST/AdditionalFiles/mnist_convert_python3.py

@@ -5,9 +5,6 @@
 import struct
 import numpy as np
 
-sys.path.append("../../../../Source/Readers/CNTKTextFormatReader")
-from uci_to_cntk_text_format_converter import convert
-
 def loadData(src, cimg):
     print ('Downloading ' + src)
     gzfname, h = urllib.request.urlretrieve(src, './delete.me')
@@ -53,20 +50,28 @@ def loadLabels(src, cimg):
     return res.reshape((cimg, 1))
 
 
+def load(dataSrc, labelsSrc, cimg):
+    data = loadData(dataSrc, cimg)
+    labels = loadLabels(labelsSrc, cimg)
+    return np.hstack((data, labels))
+
+def savetxt(filename, ndarray):
+    with open(filename, 'w', encoding="ascii") as f:
+        labels = list(map(' '.join, np.eye(10, dtype=np.uint).astype(str)))
+        for row in ndarray:
+            row_str = row.astype(str)
+            label_str = labels[row[-1]]
+            feature_str = ' '.join(row_str[:-1])
+            f.write('|labels {} |features {}\n'.format(label_str, feature_str))
+
 if __name__ == "__main__":
-    trnData = loadData('http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz', 60000)
-    trnLbl = loadLabels('http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz', 60000)
-    trn = np.hstack((trnLbl, trnData))
+    train = load('http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz',
+        'http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz', 60000)
     print ('Writing train text file...')
-    np.savetxt(r'./../Data/Train-28x28.txt', trn, fmt = '%u', delimiter='\t')
-    convert(r'./../Data/Train-28x28.txt', r'./../Data/Train-28x28_cntk_text.txt', 1, 784, 0, 1, 10)
-    os.remove(r'./../Data/Train-28x28.txt');
+    savetxt(r'./../Data/Train-28x28_cntk_text.txt', train)  
     print ('Done.')
-    testData = loadData('http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz', 10000)
-    testLbl = loadLabels('http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz', 10000)
-    test = np.hstack((testLbl, testData))
+    test = load('http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz',
+        'http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz', 10000)  
     print ('Writing test text file...')
-    np.savetxt(r'./../Data/Test-28x28.txt', test, fmt = '%u', delimiter='\t')
-    convert(r'./../Data/Test-28x28.txt', r'./../Data/Test-28x28_cntk_text.txt', 1, 784, 0, 1, 10)
-    os.remove(r'./../Data/Test-28x28.txt');
+    savetxt(r'./../Data/Test-28x28_cntk_text.txt', test)
     print ('Done.')

Examples/Image/Miscellaneous/CIFAR-10/CIFAR_convert.py

@@ -11,9 +11,6 @@
 ImgSize = 32
 NumFeat = ImgSize * ImgSize * 3
 
-sys.path.append("../../../../Source/Readers/CNTKTextFormatReader")
-from uci_to_cntk_text_format_converter import convert
-
 def readBatch(src, outFmt):
     with open(src, 'rb') as f:
         d = cp.load(f)
@@ -38,7 +35,8 @@ def readBatch(src, outFmt):
             print ('Format not supported: ' + outFmt)
             usage()
             sys.exit(1)
-    return np.hstack((np.reshape(d['labels'], (len(d['labels']), 1)), feat))
+    res = np.hstack((feat, np.reshape(d['labels'], (len(d['labels']), 1))))
+    return res.astype(np.int)
 
 def loadData(src, outFmt):
     print ('Downloading ' + src)
@@ -50,7 +48,7 @@ def loadData(src, outFmt):
             tar.extractall()
         print ('Done.')
         print ('Preparing train set...')
-        trn = np.empty((0, NumFeat + 1))
+        trn = np.empty((0, NumFeat + 1), dtype=np.int)
         for i in range(5):
             batchName = './cifar-10-batches-py/data_batch_{0}'.format(i + 1)
             trn = np.vstack((trn, readBatch(batchName, outFmt)))
@@ -86,16 +84,22 @@ def parseCmdOpt(argv):
                 sys.exit(1)
             return fmt
 
+def savetxt(filename, ndarray):
+    with open(filename, 'w') as f:
+        labels = map(' '.join, np.eye(10, dtype=np.uint).astype(str))
+        for row in ndarray:
+            row_str = row.astype(str)
+            label_str = labels[row[-1]]
+            feature_str = ' '.join(row_str[:-1])
+            f.write('|labels {} |features {}\n'.format(label_str, feature_str))
+
+
 if __name__ == "__main__":
     fmt = parseCmdOpt(sys.argv[1:])
     trn, tst = loadData('http://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz', fmt)
     print ('Writing train text file...')
-    np.savetxt(r'./Train.txt', trn, fmt = '%u', delimiter='\t')
-    convert(r'./Train.txt', r'./Train_cntk_text.txt', 1, 3072, 0, 1, 10)
-    os.remove(r'./Train.txt');
+    savetxt(r'./Train_cntk_text.txt', trn)
     print ('Done.')
     print ('Writing test text file...')
-    np.savetxt(r'./Test.txt', tst, fmt = '%u', delimiter='\t')
-    convert(r'./Test.txt', r'./Test_cntk_text.txt', 1, 3072, 0, 1, 10)
-    os.remove(r'./Test.txt');
+    savetxt(r'./Test_cntk_text.txt', tst)
     print ('Done.')

Examples/Image/Miscellaneous/ImageNet/ResNet/README.md

@@ -17,6 +17,7 @@ The following table contains results as well as links to pre-trained models that
 | ResNet-18     | 29.57       | 10.41       | [Download](https://www.cntk.ai/resnet/ResNet_18.model)
 | ResNet-34     | 27.31       | 8.97        | [Download](https://www.cntk.ai/resnet/ResNet_34.model)
 | ResNet-50     | 24.74       | 7.56        | [Download](https://www.cntk.ai/resnet/ResNet_50.model)
+| ResNet-152    | 22.57       | 6.44        | [Download](https://www.cntk.ai/resnet/ResNet_152.model)
 
 ## Notes
 This work is an implementation of ResNets in CNTK. If you are interested in the original implementation of ResNet, follow [this link](https://github.com/KaimingHe/deep-residual-networks).

Makefile

@@ -368,25 +368,25 @@ $(LIBDIR)/CompositeDataReader.so: $(COMPOSITEDATAREADER_OBJ) | $(CNTKMATH_LIB)
 	$(CXX) $(LDFLAGS) -shared $(patsubst %,-L%, $(LIBDIR) $(LIBPATH)) $(patsubst %,$(RPATH)%, $(ORIGINDIR) $(LIBPATH)) -o $@ $^ -l$(CNTKMATH)
 
 ########################################
-# ExperimentalHTKMLFReader plugin
+# HTKDeserializers plugin
 ########################################
 
-EXPERIMENTALHTKMLFREADER_SRC =\
+HTKDESERIALIZERS_SRC =\
 	$(SOURCEDIR)/Readers/HTKMLFReader/DataWriterLocal.cpp \
 	$(SOURCEDIR)/Readers/HTKMLFReader/HTKMLFWriter.cpp \
-	$(SOURCEDIR)/Readers/ExperimentalHTKMLFReader/ConfigHelper.cpp \
-	$(SOURCEDIR)/Readers/ExperimentalHTKMLFReader/Exports.cpp \
-	$(SOURCEDIR)/Readers/ExperimentalHTKMLFReader/HTKDataDeserializer.cpp \
-	$(SOURCEDIR)/Readers/ExperimentalHTKMLFReader/HTKMLFReader.cpp \
-	$(SOURCEDIR)/Readers/ExperimentalHTKMLFReader/MLFDataDeserializer.cpp \
+	$(SOURCEDIR)/Readers/HTKDeserializers/ConfigHelper.cpp \
+	$(SOURCEDIR)/Readers/HTKDeserializers/Exports.cpp \
+	$(SOURCEDIR)/Readers/HTKDeserializers/HTKDataDeserializer.cpp \
+	$(SOURCEDIR)/Readers/HTKDeserializers/HTKMLFReader.cpp \
+	$(SOURCEDIR)/Readers/HTKDeserializers/MLFDataDeserializer.cpp \
 
-EXPERIMENTALHTKMLFREADER_OBJ := $(patsubst %.cpp, $(OBJDIR)/%.o, $(EXPERIMENTALHTKMLFREADER_SRC))
+HTKDESERIALIZERS_OBJ := $(patsubst %.cpp, $(OBJDIR)/%.o, $(HTKDESERIALIZERS_SRC))
 
-EXPERIMENTALHTKMLFREADER:=$(LIBDIR)/ExperimentalHTKMLFReader.so
-ALL+=$(EXPERIMENTALHTKMLFREADER)
-SRC+=$(EXPERIMENTALHTKMLFREADER_SRC)
+HTKDESERIALIZERS:=$(LIBDIR)/HTKDeserializers.so
+ALL+=$(HTKDESERIALIZERS)
+SRC+=$(HTKDESERIALIZERS_SRC)
 
-$(LIBDIR)/ExperimentalHTKMLFReader.so: $(EXPERIMENTALHTKMLFREADER_OBJ) | $(CNTKMATH_LIB)
+$(LIBDIR)/HTKDeserializers.so: $(HTKDESERIALIZERS_OBJ) | $(CNTKMATH_LIB)
 	@echo $(SEPARATOR)
 	$(CXX) $(LDFLAGS) -shared $(patsubst %,-L%, $(LIBDIR) $(LIBPATH)) $(patsubst %,$(RPATH)%, $(ORIGINDIR) $(LIBPATH)) -o $@ $^ -l$(CNTKMATH)
 

Source/Common/DataWriter.cpp

@@ -49,10 +49,6 @@ DataWriter::DataWriter(const ConfigRecordType& config)
     {
         writerType = L"HTKMLFReader";
     }
-    else if (writerType == L"ExperimentalHTKMLFWriter" || writerType == L"ExperimentalHTKMLFReader")
-    {
-        writerType = L"ExperimentalHTKMLFReader";
-    }
     else if (writerType == L"BinaryWriter" || writerType == L"BinaryReader")
     {
         writerType = L"BinaryReader";

Source/Readers/CompositeDataReader/CompositeDataReader.h

@@ -38,7 +38,7 @@ struct Minibatch;
 
 // The whole CompositeDataReader is meant as a stopgap to allow deserializers/transformers composition until SGD talkes 
 // directly to the new Reader API. The example of the cntk configuration that this reader supports can be found at
-//     Tests/EndToEndTests/Speech/ExperimentalHtkmlfReader/LSTM/FullUtterance/cntk.cntk
+//     Tests/EndToEndTests/Speech/HtkDeserializers/LSTM/FullUtterance/cntk.cntk
 // CompositeDataReader is a factory for the new readers. Its main responsibility is to read the configuration and create the
 // corresponding set of deserializers, the corpus descriptor, transformers, randomizer and packer, providing the following functionality:
 //     - all input sequences are defined by the corpus descriptor

Source/Readers/CompositeDataReader/stdafx.cpp

@@ -3,7 +3,6 @@
 // Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
 //
 // stdafx.cpp : source file that includes just the standard includes
-// ExperimentalHTKMLFReader.pch will be the pre-compiled header
 // stdafx.obj will contain the pre-compiled type information
 //
 

Source/Readers/ExperimentalHTKMLFReader/Exports.cpp → Source/Readers/HTKDeserializers/Exports.cpp

@@ -16,6 +16,7 @@
 #include "HeapMemoryProvider.h"
 #include "HTKDataDeserializer.h"
 #include "MLFDataDeserializer.h"
+#include "StringUtil.h"
 
 namespace Microsoft { namespace MSR { namespace CNTK {
 
@@ -39,11 +40,11 @@ extern "C" DATAREADER_API void GetReaderD(IDataReader** preader)
 // TODO: Not safe from the ABI perspective. Will be uglified to make the interface ABI.
 extern "C" DATAREADER_API bool CreateDeserializer(IDataDeserializer** deserializer, const std::wstring& type, const ConfigParameters& deserializerConfig, CorpusDescriptorPtr corpus,  bool primary)
 {
-    if (type == L"HTKDataDeserializer")
+    if (type == L"HTKFeatureDeserializer")
     {
         *deserializer = new HTKDataDeserializer(corpus, deserializerConfig, primary);
     }
-    else if (type == L"MLFDataDeserializer")
+    else if (type == L"HTKMLFDeserializer")
     {
         *deserializer = new MLFDataDeserializer(corpus, deserializerConfig, primary);
     }

Source/Readers/ExperimentalHTKMLFReader/ExperimentalHTKMLFReader.vcxproj → Source/Readers/HTKDeserializers/HTKDeserializers.vcxproj

@@ -21,7 +21,7 @@
   <PropertyGroup Label="Globals">
     <ProjectGuid>{7B7A51ED-AA8E-4660-A805-D50235A02120}</ProjectGuid>
     <Keyword>Win32Proj</Keyword>
-    <RootNamespace>ExperimentalHTKMLFReader</RootNamespace>
+    <RootNamespace>HTKDeserializers</RootNamespace>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
   <Import Project="$(SolutionDir)\CNTK.Cpp.props" />

Source/Readers/ExperimentalHTKMLFReader/stdafx.cpp → Source/Readers/HTKDeserializers/stdafx.cpp

@@ -3,7 +3,7 @@
 // Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
 //
 // stdafx.cpp : source file that includes just the standard includes
-// ExperimentalHTKMLFReader.pch will be the pre-compiled header
+// HTKMLFDeserializer.pch will be the pre-compiled header
 // stdafx.obj will contain the pre-compiled type information
 //
 

Source/Readers/ImageReader/Exports.cpp

@@ -38,7 +38,7 @@ extern "C" DATAREADER_API void GetReaderD(IDataReader** preader)
 // A factory method for creating image deserializers.
 extern "C" DATAREADER_API bool CreateDeserializer(IDataDeserializer** deserializer, const std::wstring& type, const ConfigParameters& deserializerConfig, CorpusDescriptorPtr corpus, bool)
 {
-    if (type == L"ImageDataDeserializer")
+    if (type == L"ImageDeserializer")
         *deserializer = new ImageDataDeserializer(corpus, deserializerConfig);
     else
         // Unknown type.

Tests/EndToEndTests/Image/AlexNet/AlexNetComposite.cntk

@@ -9,9 +9,9 @@ Train=[
         useLegacy=false
 
         # A list of deserializers to use.
-        deserializers=[
+        deserializers=(
             [   
-                type="ImageDataDeserializer"
+                type="ImageDeserializer"
                 module="ImageReader"
 
                 # Map file which maps images to labels using the following format:
@@ -23,7 +23,7 @@ Train=[
                 # Description of input streams
                 input=[
                     features=[
-                        transforms=[
+                        transforms=(
                             [
                                 type="Crop"
                                 # Possible values: Center, Random. Default: Center
@@ -48,14 +48,14 @@ Train=[
                             ]:[
                                 type="Transpose"
                             ]
-                        ]
+                        )
                     ]
                     labels=[
                         labelDim=1000
                     ]
                 ]
             ]
-        ]
+        )
     ]    
 ]
 
@@ -65,16 +65,16 @@ Test=[
         randomize=false
 
         # A list of deserializers to use.
-        deserializers=[
+        deserializers=(
             [
-                type="ImageDataDeserializer"
+                type="ImageDeserializer"
                 module="ImageReader"
                 file=$ConfigDir$/val_map.txt
 
                 # Description of input streams
                 input=[
                     features=[
-                        transforms=[
+                        transforms=(
                             [
                                 type="Crop"
                                 cropType=Center
@@ -89,13 +89,13 @@ Test=[
                             ]:[
                                 type="Transpose"
                             ]
-                        ]
+                        )
                     ]
                     labels=[
                         labelDim=1000
                     ]
                 ]
             ]
-        ]
+        )
     ]        
 ]