Integrate eldak/addingTimitExamplesToTests into master

putraxor · Apr 15, 2016 · 55ef117 · 55ef117
2 parents b9ff7c0 + 682d7cb
commit 55ef117
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Showing 64 changed files with 169,266 additions and 327 deletions.
diff --git a/.gitattributes b/.gitattributes
@@ -36,6 +36,7 @@ configure text eol=lf
 generate_build_info text eol=lf
 run-test text eol=lf
 run-test-common text eol=lf
+run-timit-test-common text eol=lf
 make_binary_drop_linux text eol=lf
 
 Makefile text

diff --git a/Examples/Speech/Miscellaneous/TIMIT/config/TIMIT_AdaptLearnRate.cntk b/Examples/Speech/Miscellaneous/TIMIT/config/TIMIT_AdaptLearnRate.cntk
@@ -1,12 +1,14 @@
-stderr=$ExpDir$\TrainAdaptLR\log\log
+# If set to true, always initialize the network on CPU, making initialization consistent across CPU and GPU targets (for testing).
+initOnCPUOnly=true 
+
 command=TIMIT_TrainAdaptLR
 
 precision=float
 
 TIMIT_TrainAdaptLR=[
     action=train
 
-    modelPath=$ExpDir$\TrainAdaptLR\model\cntkSpeech.dnn
+    modelPath=$ExpDir$/TrainAdaptLR/model/cntkSpeech.dnn
 
     # deviceId=-1 for CPU, >=0 for GPU devices 
     deviceId=$DeviceNumber$
@@ -23,7 +25,7 @@ TIMIT_TrainAdaptLR=[
         uniformInit=true
         needPrior=true
     ]
-    
+
     SGD=[
         epochSize=0
         minibatchSize=128
@@ -51,47 +53,42 @@ TIMIT_TrainAdaptLR=[
         clippingThresholdPerSample=1#INF
 
     ]
-       
+
     # Parameter values for the reader
     reader=[
-      # reader to use
-      readerType=HTKMLFReader
-#      readMethod=blockRandomize
-      readMethod=rollingWindow
-      miniBatchMode=Partial
-      randomize=Auto
-      verbosity=1   
-      features=[
-	dim=792	
-     	scpFile=$ScpDir$\TIMIT.train.scp.fbank.fullpath
-      ]
+        # reader to use
+        readerType=HTKMLFReader
+        readMethod=blockRandomize
+        miniBatchMode=Partial
+        randomize=Auto
+        verbosity=0
+        features=[
+            dim=792
+            scpFile=$ScpDir$/TIMIT.train.scp.fbank.fullpath.rnn
+        ]
 
-      labels=[
-	mlfFile=$MlfDir$\TIMIT.train.align_cistate.mlf.cntk
-        labelDim=183
-	labelMappingFile=$MlfDir$\TIMIT.statelist
-      ]
+        labels=[
+            mlfFile=$MlfDir$/TIMIT.train.align_cistate.mlf.cntk
+            labelDim=183
+            labelMappingFile=$MlfDir$/TIMIT.statelist
+        ]
     ]
 
     cvReader=[
-      # reader to use
-      readerType=HTKMLFReader
-#      readMethod=blockRandomize
-      readMethod=rollingWindow
-      miniBatchMode=Partial
-      randomize=Auto
-      verbosity=1   
-      features=[
-	dim=792
-	scpFile=$ScpDir$\TIMIT.dev.scp.fbank.fullpath    
-      ]
+        readerType=HTKMLFReader
+        readMethod=blockRandomize
+        miniBatchMode=Partial
+        randomize=Auto
+        verbosity=0
+        features=[
+            dim=792
+            scpFile=$ScpDir$/TIMIT.dev.scp.fbank.fullpath.rnn
+        ]
 
-      labels=[
-	mlfFile=$MlfDir$\TIMIT.dev.align_cistate.mlf.cntk
-        labelDim=183	
-	labelMappingFile=$MlfDir$\TIMIT.statelist
-      ]
+        labels=[
+            mlfFile=$MlfDir$/TIMIT.dev.align_cistate.mlf.cntk
+            labelDim=183
+            labelMappingFile=$MlfDir$/TIMIT.statelist
+        ]
     ]
-
-]
-
+]
diff --git a/Examples/Speech/Miscellaneous/TIMIT/config/TIMIT_CrossValidateSimpleNetwork.cntk b/Examples/Speech/Miscellaneous/TIMIT/config/TIMIT_CrossValidateSimpleNetwork.cntk
@@ -1,4 +1,6 @@
-stderr=$ExpDir$\CrossValidateSimpleNetwork\log\log
+# If set to true, always initialize the network on CPU, making initialization consistent across CPU and GPU targets (for testing).
+initOnCPUOnly=true
+
 command=TIMIT_CVSimple
 
 precision=float
@@ -10,33 +12,31 @@ precision=float
 TIMIT_CVSimple=[
     action=cv
 
-    modelPath=$ExpDir$\TrainSimpleNetwork\model\cntkSpeech.dnn
+    modelPath=$ExpDir$/TrainSimpleNetwork/model/cntkSpeech.dnn
 
     # deviceId=-1 for CPU, >=0 for GPU devices 
     deviceId=$DeviceNumber$
 
     traceLevel=1
     crossValidationInterval=0:2:25 # evaluate from model 0 to model 10, every 2 models (0,2,4, etc)
-     # Parameter values for the reader
+    # Parameter values for the reader
     reader=[
-      # reader to use
-      readerType=HTKMLFReader
-#     readMethod=blockRandomize
-      readMethod=rollingWindow
-
-      miniBatchMode=Partial
-      randomize=None
-      verbosity=1   
-
-      features=[
-	  dim=792
-	  scpFile=$ScpDir$\TIMIT.dev.scp.fbank.fullpath
-      ]
-
-      labels=[
-	mlfFile=$MlfDir$\TIMIT.dev.align_cistate.mlf.cntk
-        labelDim=183
-	labelMappingFile=$MlfDir$\TIMIT.statelist
-      ]
+        # reader to use
+        readerType=HTKMLFReader
+        miniBatchMode=Partial
+        readMethod=rollingWindow
+        randomize=None
+        verbosity=0
+
+        features=[
+            dim=792
+            scpFile=$ScpDir$/TIMIT.dev.scp.fbank.fullpath
+        ]
+
+        labels=[
+            mlfFile=$MlfDir$/TIMIT.dev.align_cistate.mlf.cntk
+            labelDim=183
+            labelMappingFile=$MlfDir$/TIMIT.statelist
+        ]
     ]
-]
+]
diff --git a/Examples/Speech/Miscellaneous/TIMIT/config/TIMIT_EvalSimpleNetwork.cntk b/Examples/Speech/Miscellaneous/TIMIT/config/TIMIT_EvalSimpleNetwork.cntk
@@ -1,4 +1,6 @@
-stderr=$ExpDir$\EvalSimpleNetwork\log\log
+# If set to true, always initialize the network on CPU, making initialization consistent across CPU and GPU targets (for testing).
+initOnCPUOnly=true
+
 command=TIMIT_EvalSimple
 
 precision=float
@@ -10,7 +12,7 @@ precision=float
 TIMIT_EvalSimple=[
     action=eval
 
-    modelPath=$ExpDir$\TrainSimpleNetwork\model\cntkSpeech.dnn
+    modelPath=$ExpDir$/TrainSimpleNetwork/model/cntkSpeech.dnn
 
     # deviceId=-1 for CPU, >=0 for GPU devices 
     deviceId=$DeviceNumber$
@@ -19,24 +21,22 @@ TIMIT_EvalSimple=[
 
      # Parameter values for the reader
     reader=[
-      # reader to use
-      readerType=HTKMLFReader
-#     readMethod=blockRandomize
-      readMethod=rollingWindow
-
-      miniBatchMode=Partial
-      randomize=None
-      verbosity=1   
-
-      features=[
-	  dim=792
-	  scpFile=$ScpDir$\TIMIT.dev.scp.fbank.fullpath
-      ]
-
-      labels=[
-	mlfFile=$MlfDir$\TIMIT.dev.align_cistate.mlf.cntk
-        labelDim=183
-	labelMappingFile=$MlfDir$\TIMIT.statelist
-      ]
+        # reader to use
+        readerType=HTKMLFReader
+        miniBatchMode=Partial
+        readMethod=rollingWindow
+        randomize=None
+        verbosity=0
+
+        features=[
+            dim=792
+            scpFile=$ScpDir$/TIMIT.dev.scp.fbank.fullpath
+        ]
+
+        labels=[
+            mlfFile=$MlfDir$/TIMIT.dev.align_cistate.mlf.cntk
+            labelDim=183
+            labelMappingFile=$MlfDir$/TIMIT.statelist
+        ]
     ]
-]
+]
diff --git a/Examples/Speech/Miscellaneous/TIMIT/config/TIMIT_TrainAutoEncoder.cntk b/Examples/Speech/Miscellaneous/TIMIT/config/TIMIT_TrainAutoEncoder.cntk
@@ -1,4 +1,6 @@
-stderr=$ExpDir$\TrainAutoEncoder\log\log
+# If set to true, always initialize the network on CPU, making initialization consistent across CPU and GPU targets (for testing).
+initOnCPUOnly=true
+
 command=TIMIT_TrainAutoEncoder
 
 precision=float
@@ -10,7 +12,7 @@ precision=float
 TIMIT_TrainAutoEncoder=[
     action=train
 
-    modelPath=$ExpDir$\TrainAutoEncoder\model\cntkSpeech.dnn
+    modelPath=$ExpDir$/TrainAutoEncoder/model/cntkSpeech.dnn
 
     # deviceId=-1 for CPU, >=0 for GPU devices 
     deviceId=$DeviceNumber$
@@ -20,12 +22,12 @@ TIMIT_TrainAutoEncoder=[
     # notation xxx:yyy*n:zzz is equivalent to xxx, then yyy repeated n times, then zzz
     # example: 10:20*3:5 is equivalent to 10:20:20:20:5
     NDLNetworkBuilder=[
-	ndlMacros=$NdlDir$\default_macros.ndl
-        NetworkDescription=$NdlDir$\ae.ndl
-    ]	
-	
+        ndlMacros=$NdlDir$/default_macros.ndl
+        NetworkDescription=$NdlDir$/ae.ndl
+    ]
+
     SGD=[
-	# epochSize=0 means epochSize is the size of the training set
+        # epochSize=0 means epochSize is the size of the training set
         epochSize=0 
         minibatchSize=256
         learningRatesPerMB=0.1
@@ -36,24 +38,22 @@ TIMIT_TrainAutoEncoder=[
 
     # Parameter values for the reader
     reader=[
-      # reader to use
-      readerType=HTKMLFReader
-
-#     readMethod=blockRandomize
-      readMethod=rollingWindow
-
-      miniBatchMode=Partial
-      randomize=Auto
-      verbosity=1   
-
-      featIn=[
-	  dim=792
-	  scpFile=$ScpDir$\TIMIT.train.scp.fbank.fullpath
-      ]
-
-      featOut=[
-	scpFile=$ScpDir$\TIMIT.train.scp.fbank.fullpath
-        dim=792
-      ]
+        # reader to use
+        readerType=HTKMLFReader
+        readMethod=blockRandomize
+
+        miniBatchMode=Partial
+        randomize=Auto
+        verbosity=0
+
+        featIn=[
+            dim=792
+            scpFile=$ScpDir$/TIMIT.train.scp.fbank.fullpath.rnn
+        ]
+
+        featOut=[
+            scpFile=$ScpDir$/TIMIT.train.scp.fbank.fullpath.rnn
+            dim=792
+        ]
     ]
-]
+]