Python ISTA_Time примеры использования

Пример #1

Файл: imagenet_time_demo.py Проект: slundqui/TFSparseCode

    'batchSize':       1,
    #Learning rate for optimizer
    'learningRateA':   1e-4,
    'learningRateW':   1e-4,
    #Lambda in energy function
    'thresh':          .03,
    #Number of features in V1
    'numV':            1536,
    #Time dimension
    'nT':              7,
    #Stride of V1
    'VStrideT':        1,
    'VStrideY':        4,
    'VStrideX':        4,
    #Patch size
    'patchSizeT':      4,
    'patchSizeY':      16,
    'patchSizeX':      16,
}

#Allocate tensorflow object
#This will build the graph
tfObj = ISTA_Time(params, trainDataObj)

print "Done init"
tfObj.runModel()
print "Done run"

tfObj.closeSess()

Пример #2

    'batchSize':       1,
    #Learning rate for optimizer
    'learningRateA':   1e-4,
    'learningRateW':   1e-4,
    #Lambda in energy function
    'thresh':          .03,
    #Number of features in V1
    'numV':            1536,
    #Time dimension
    'nT':              7,
    #Stride of V1
    'VStrideT':        1,
    'VStrideY':        4,
    'VStrideX':        4,
    #Patch size
    'patchSizeT':      4,
    'patchSizeY':      16,
    'patchSizeX':      16,
}

#Allocate tensorflow object
#This will build the graph
tfObj = ISTA_Time(params, trainDataObj)

print("Done init")
tfObj.runModel()
print("Done run")

tfObj.closeSess()

Пример #3

Файл: imagenet_time_writepvp.py Проект: slundqui/TFSparseCode

    'batchSize':       1,
    #Learning rate for optimizer
    'learningRateA':   1e-4,
    'learningRateW':   1e-4,
    #Lambda in energy function
    'thresh':          .03,
    #Number of features in V1
    'numV':            1536,
    #Time dimension
    'nT':              7,
    #Stride of V1
    'VStrideT':        1,
    'VStrideY':        4,
    'VStrideX':        4,
    #Patch size
    'patchSizeT':      4,
    'patchSizeY':      16,
    'patchSizeX':      16,
}

#Allocate tensorflow object
#This will build the graph
tfObj = ISTA_Time(params, trainDataObj)

print("Done init")
tfObj.writePvpWeights(outPvpPrefix)

print("Done run")
tfObj.closeSess()

Пример #4

Файл: imagenet_time_writepvp.py Проект: xueyangfu/TFSparseCode

    #Batch size
    'batchSize': 1,
    #Learning rate for optimizer
    'learningRateA': 1e-4,
    'learningRateW': 1e-4,
    #Lambda in energy function
    'thresh': .03,
    #Number of features in V1
    'numV': 1536,
    #Time dimension
    'nT': 7,
    #Stride of V1
    'VStrideT': 1,
    'VStrideY': 4,
    'VStrideX': 4,
    #Patch size
    'patchSizeT': 4,
    'patchSizeY': 16,
    'patchSizeX': 16,
}

#Allocate tensorflow object
#This will build the graph
tfObj = ISTA_Time(params, trainDataObj)

print("Done init")
tfObj.writePvpWeights(outPvpPrefix)

print("Done run")
tfObj.closeSess()

Пример #5

    #Learning rate for optimizer
    'learningRateA': 1e-4,
    'learningRateW': 1e-5,
    #Lambda in energy function
    'thresh': .03,
    #Number of features in V1
    'numV': 1536,
    #Time dimension
    'nT': 7,
    #Stride of V1
    'VStrideT': 1,
    'VStrideY': 4,
    'VStrideX': 4,
    #Patch size
    'patchSizeT': 4,
    'patchSizeY': 16,
    'patchSizeX': 16,
}

#Allocate tensorflow object
#This will build the graph
tfObj = ISTA_Time(params, trainDataObj)

print("Done init")
tfObj.evalSet(
    trainDataObj,
    "/home/slundquist/mountData/tfLCA/imagenetTime_eval/train_data/imagenet_time_"
)

tfObj.closeSess()

Пример #6

Файл: imagenet_time_traineval.py Проект: slundqui/TFSparseCode

    #Batch size
    'batchSize':       1,
    #Learning rate for optimizer
    'learningRateA':   1e-4,
    'learningRateW':   1e-5,
    #Lambda in energy function
    'thresh':          .03,
    #Number of features in V1
    'numV':            1536,
    #Time dimension
    'nT':              7,
    #Stride of V1
    'VStrideT':        1,
    'VStrideY':        4,
    'VStrideX':        4,
    #Patch size
    'patchSizeT':      4,
    'patchSizeY':      16,
    'patchSizeX':      16,
}

#Allocate tensorflow object
#This will build the graph
tfObj = ISTA_Time(params, trainDataObj)

print "Done init"
tfObj.evalSet(trainDataObj, "/home/slundquist/mountData/tfLCA/imagenetTime_eval/train_data/imagenet_time_")

tfObj.closeSess()