32 from daal.algorithms.neural_networks
import layers
33 from daal.algorithms.neural_networks.layers
import stochastic_pooling2d
35 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
36 if utils_folder
not in sys.path:
37 sys.path.insert(0, utils_folder)
38 from utils
import printTensor, readTensorFromCSV
41 datasetFileName = os.path.join(
"..",
"data",
"batch",
"layer_non_negative.csv")
43 if __name__ ==
"__main__":
46 data = readTensorFromCSV(datasetFileName)
47 nDim = data.getNumberOfDimensions()
48 printTensor(data,
"Forward two-dimensional stochastic pooling layer input (first 10 rows):", 10)
51 forwardLayer = stochastic_pooling2d.forward.Batch(nDim)
52 forwardLayer.input.setInput(layers.forward.data, data)
55 forwardLayer.compute()
58 forwardResult = forwardLayer.getResult()
60 printTensor(forwardResult.getResult(layers.forward.value),
"Forward two-dimensional stochastic pooling layer result (first 5 rows):", 5)
61 printTensor(forwardResult.getLayerData(layers.stochastic_pooling2d.auxSelectedIndices),
62 "Forward two-dimensional stochastic pooling layer selected indices (first 10 rows):", 10)
65 backwardLayer = layers.stochastic_pooling2d.backward.Batch(nDim)
66 backwardLayer.input.setInput(layers.backward.inputGradient, forwardResult.getResult(layers.forward.value))
67 backwardLayer.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
70 backwardLayer.compute()
73 backwardResult = backwardLayer.getResult()
75 printTensor(backwardResult.getResult(layers.backward.gradient),
76 "Backward two-dimensional stochastic pooling layer result (first 10 rows):", 10)