34 from daal.algorithms.neural_networks
import layers
35 from daal.data_management
import HomogenTensor
37 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
38 if utils_folder
not in sys.path:
39 sys.path.insert(0, utils_folder)
40 from utils
import printTensor, printNumericTable
44 dataArray = np.array([[[[2, 4, 6, 8],
51 [-10, -12, -14, -16]],
52 [[-18, -20, -22, -24],
53 [-26, -28, -30, -32]],
54 [[-34, -36, -38, -40],
55 [-42, -44, -46, -48]]]],
58 if __name__ ==
"__main__":
59 data = HomogenTensor(dataArray)
62 printTensor(data,
"Forward two-dimensional spatial pyramid average pooling layer input (first 10 rows):", 10)
65 forwardLayer = layers.spatial_average_pooling2d.forward.Batch(2, nDim)
66 forwardLayer.input.setInput(layers.forward.data, data)
70 forwardResult = forwardLayer.compute()
72 printTensor(forwardResult.getResult(layers.forward.value),
73 "Forward two-dimensional spatial pyramid average pooling layer result (first 5 rows):",
75 printNumericTable(forwardResult.getLayerData(layers.spatial_average_pooling2d.auxInputDimensions),
76 "Forward two-dimensional spatial pyramid average pooling layer input dimensions:")
79 backwardLayer = layers.spatial_average_pooling2d.backward.Batch(2, nDim)
80 backwardLayer.input.setInput(layers.backward.inputGradient, forwardResult.getResult(layers.forward.value))
81 backwardLayer.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
85 backwardResult = backwardLayer.compute()
87 printTensor(backwardResult.getResult(layers.backward.gradient),
88 "Backward two-dimensional spatial pyramid average pooling layer result (first 10 rows):",