30 from daal.algorithms.neural_networks
import layers
31 from daal.algorithms.neural_networks.layers
import maximum_pooling2d
33 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
34 if utils_folder
not in sys.path:
35 sys.path.insert(0, utils_folder)
36 from utils
import printTensor, readTensorFromCSV
39 datasetFileName = os.path.join(
"..",
"data",
"batch",
"layer.csv")
41 if __name__ ==
"__main__":
44 data = readTensorFromCSV(datasetFileName)
45 nDim = data.getNumberOfDimensions()
47 printTensor(data,
"Forward two-dimensional maximum pooling layer input (first 10 rows):", 10)
50 forwardLayer = maximum_pooling2d.forward.Batch(nDim)
51 forwardLayer.input.setInput(layers.forward.data, data)
54 forwardLayer.compute()
57 forwardResult = forwardLayer.getResult()
59 printTensor(forwardResult.getResult(layers.forward.value),
"Forward two-dimensional maximum pooling layer result (first 5 rows):", 5)
60 printTensor(forwardResult.getLayerData(layers.maximum_pooling2d.auxSelectedIndices),
61 "Forward two-dimensional maximum pooling layer selected indices (first 10 rows):", 10)
64 backwardLayer = layers.maximum_pooling2d.backward.Batch(nDim)
65 backwardLayer.input.setInput(layers.backward.inputGradient, forwardResult.getResult(layers.forward.value))
66 backwardLayer.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
69 backwardLayer.compute()
72 backwardResult = backwardLayer.getResult()
74 printTensor(backwardResult.getResult(layers.backward.gradient),
75 "Backward two-dimensional maximum pooling layer result (first 10 rows):", 10)