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 printTensor, printNumericTable
68 dataArray = np.array([[[[2, 4, 6, 8],
75 [-10, -12, -14, -16]],
76 [[-18, -20, -22, -24],
77 [-26, -28, -30, -32]],
78 [[-34, -36, -38, -40],
79 [-42, -44, -46, -48]]]],
82 if __name__ ==
"__main__":
83 data = HomogenTensor(dataArray)
86 printTensor(data,
"Forward two-dimensional spatial pyramid average pooling layer input (first 10 rows):", 10)
89 forwardLayer = layers.spatial_average_pooling2d.forward.Batch(2, nDim)
90 forwardLayer.input.setInput(layers.forward.data, data)
94 forwardResult = forwardLayer.compute()
96 printTensor(forwardResult.getResult(layers.forward.value),
97 "Forward two-dimensional spatial pyramid average pooling layer result (first 5 rows):",
99 printNumericTable(forwardResult.getLayerData(layers.spatial_average_pooling2d.auxInputDimensions),
100 "Forward two-dimensional spatial pyramid average pooling layer input dimensions:")
103 backwardLayer = layers.spatial_average_pooling2d.backward.Batch(2, nDim)
104 backwardLayer.input.setInput(layers.backward.inputGradient, forwardResult.getResult(layers.forward.value))
105 backwardLayer.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
109 backwardResult = backwardLayer.compute()
111 printTensor(backwardResult.getResult(layers.backward.gradient),
112 "Backward two-dimensional spatial pyramid average pooling layer result (first 10 rows):",