30 from daal.algorithms.neural_networks
import layers
31 from daal.algorithms.neural_networks.layers
import stochastic_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_non_negative.csv")
41 if __name__ ==
"__main__":
44 data = readTensorFromCSV(datasetFileName)
45 nDim = data.getNumberOfDimensions()
46 printTensor(data,
"Forward two-dimensional stochastic pooling layer input (first 10 rows):", 10)
49 forwardLayer = stochastic_pooling2d.forward.Batch(nDim)
50 forwardLayer.input.setInput(layers.forward.data, data)
53 forwardLayer.compute()
56 forwardResult = forwardLayer.getResult()
58 printTensor(forwardResult.getResult(layers.forward.value),
"Forward two-dimensional stochastic pooling layer result (first 5 rows):", 5)
59 printTensor(forwardResult.getLayerData(layers.stochastic_pooling2d.auxSelectedIndices),
60 "Forward two-dimensional stochastic pooling layer selected indices (first 10 rows):", 10)
63 backwardLayer = layers.stochastic_pooling2d.backward.Batch(nDim)
64 backwardLayer.input.setInput(layers.backward.inputGradient, forwardResult.getResult(layers.forward.value))
65 backwardLayer.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
68 backwardLayer.compute()
71 backwardResult = backwardLayer.getResult()
73 printTensor(backwardResult.getResult(layers.backward.gradient),
74 "Backward two-dimensional stochastic pooling layer result (first 10 rows):", 10)