58 from daal.algorithms.neural_networks
import layers
59 from daal.data_management
import HomogenTensor
61 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
62 if utils_folder
not in sys.path:
63 sys.path.insert(0, utils_folder)
64 from utils
import printTensor3d, printNumericTable
68 dataArray = np.array([[[1, 2, 3, 4],
76 if __name__ ==
"__main__":
78 dataTensor = HomogenTensor(dataArray)
80 printTensor3d(dataTensor,
"Forward average pooling layer input:")
83 forwardLayer = layers.average_pooling3d.forward.Batch(nDim)
84 forwardLayer.input.setInput(layers.forward.data, dataTensor)
88 forwardResult = forwardLayer.compute()
90 printTensor3d(forwardResult.getResult(layers.forward.value),
"Forward average pooling layer result:")
91 printNumericTable(forwardResult.getLayerData(layers.average_pooling3d.auxInputDimensions),
92 "Forward pooling layer input dimensions:")
95 backwardLayer = layers.average_pooling3d.backward.Batch(nDim)
96 backwardLayer.input.setInput(layers.backward.inputGradient, forwardResult.getResult(layers.forward.value))
97 backwardLayer.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
101 backwardResult = backwardLayer.compute()
103 printTensor3d(backwardResult.getResult(layers.backward.gradient),
"Backward average pooling layer result:")