def printTensors(dataTable1,
dataTable2,
title1="",
title2="",
message="",
nPrintedRows=0,
interval=15):
dims1 = dataTable1.getDimensions()
nRows1 = int(dims1[0])
if nPrintedRows != 0:
nPrintedRows = min(nRows1, nPrintedRows)
else:
nPrintedRows = nRows1
block1 = SubtensorDescriptor()
dataTable1.getSubtensor([], 0, nPrintedRows, readOnly, block1)
nCols1 = int(block1.getSize() / nPrintedRows)
dims2 = dataTable2.getDimensions()
nRows2 = int(dims2[0])
if nPrintedRows != 0:
nPrintedRows = min(nRows2, nPrintedRows)
else:
nPrintedRows = nRows2
block2 = SubtensorDescriptor()
dataTable2.getSubtensor([], 0, nPrintedRows, readOnly, block2)
nCols2 = int(block2.getSize() / nPrintedRows)
dataType1 = block1.getArray().flatten()
dataType2 = block2.getArray().flatten()
print(message)
print("{:<{width}}".format(title1, width=(interval * nCols1)), end='')
print("{:<{width}}".format(title2, width=(interval * nCols2)))
for i in range(nPrintedRows):
for j in range(nCols1):
print("{v:<{width}.0f}".format(v=dataType1[i * nCols1 + j],
width=interval),
end='')
for j in range(nCols2):
print("{:<{width}.3f}".format(dataType2[i * nCols2 + j],
width=int(interval / 2)),
end='')
print()
print()
dataTable1.releaseSubtensor(block1)
dataTable2.releaseSubtensor(block2)
def printTensor3d(dataTable,
message="",
nFirstDim=0,
nSecondDim=0,
interval=10):
dims = dataTable.getDimensions()
nRows = int(dims[0])
nCols = int(dims[1])
if nFirstDim != 0:
nFirstDim = min(nRows, nFirstDim)
else:
nFirstDim = nRows
if nSecondDim != 0:
nSecondDim = min(nCols, nSecondDim)
else:
nSecondDim = nCols
block = SubtensorDescriptor()
print(message)
for i in range(nFirstDim):
dataTable.getSubtensor([i], 0, nSecondDim, readOnly, block)
nThirdDim = block.getSize() / nSecondDim
printArray(block.getArray(), int(nThirdDim), int(nSecondDim),
int(nThirdDim), "", interval)
dataTable.releaseSubtensor(block)
def printTensor(dataTable,
message="",
nPrintedRows=0,
nPrintedCols=0,
interval=10):
dims = dataTable.getDimensions()
nRows = int(dims[0])
if nPrintedRows != 0:
nPrintedRows = min(nRows, nPrintedRows)
else:
nPrintedRows = nRows
block = SubtensorDescriptor()
dataTable.getSubtensor([], 0, nPrintedRows, readOnly, block)
nCols = int(block.getSize() / nPrintedRows)
if nPrintedCols != 0:
nPrintedCols = min(nCols, nPrintedCols)
else:
nPrintedCols = nCols
printArray(block.getArray(), int(nPrintedCols), int(nPrintedRows),
int(nCols), message, interval)
dataTable.releaseSubtensor(block)
def findClasses(dataTable):
dims1 = dataTable.getDimensions()
nRows1 = int(dims1[0])
block1 = SubtensorDescriptor()
dataTable.getSubtensor([], 0, nRows1, readOnly, block1)
nCols1 = int(block1.getSize() / nRows1)
dataType = block1.getArray().flatten()
dataType = np.reshape(dataType, (nRows1, nCols1))
classes = np.argmax(dataType, axis=1)
dataTable.releaseSubtensor(block1)
return classes