56 from daal.algorithms.neural_networks
import layers
57 from daal.algorithms.neural_networks.layers
import maximum_pooling2d
59 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
60 if utils_folder
not in sys.path:
61 sys.path.insert(0, utils_folder)
62 from utils
import printTensor, readTensorFromCSV
65 datasetFileName = os.path.join(
"..",
"data",
"batch",
"layer.csv")
67 if __name__ ==
"__main__":
70 data = readTensorFromCSV(datasetFileName)
71 nDim = data.getNumberOfDimensions()
73 printTensor(data,
"Forward two-dimensional maximum pooling layer input (first 10 rows):", 10)
76 forwardLayer = maximum_pooling2d.forward.Batch(nDim)
77 forwardLayer.input.setInput(layers.forward.data, data)
80 forwardLayer.compute()
83 forwardResult = forwardLayer.getResult()
85 printTensor(forwardResult.getResult(layers.forward.value),
"Forward two-dimensional maximum pooling layer result (first 5 rows):", 5)
86 printTensor(forwardResult.getLayerData(layers.maximum_pooling2d.auxSelectedIndices),
87 "Forward two-dimensional maximum pooling layer selected indices (first 10 rows):", 10)
90 backwardLayer = layers.maximum_pooling2d.backward.Batch(nDim)
91 backwardLayer.input.setInput(layers.backward.inputGradient, forwardResult.getResult(layers.forward.value))
92 backwardLayer.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
95 backwardLayer.compute()
98 backwardResult = backwardLayer.getResult()
100 printTensor(backwardResult.getResult(layers.backward.gradient),
101 "Backward two-dimensional maximum pooling layer result (first 10 rows):", 10)