30 from daal.algorithms.neural_networks
import layers
32 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
33 if utils_folder
not in sys.path:
34 sys.path.insert(0, utils_folder)
35 from utils
import printNumericTable, printTensor, readTensorFromCSV
38 datasetName = os.path.join(
"..",
"data",
"batch",
"layer.csv")
41 if __name__ ==
"__main__":
44 tensorDataCollection = layers.LayerData()
45 for i
in range(nInputs):
46 tensorDataCollection[i] = readTensorFromCSV(datasetName)
49 eltwiseSumLayerForward = layers.eltwise_sum.forward.Batch()
52 eltwiseSumLayerForward.input.setInputLayerData(layers.forward.inputLayerData, tensorDataCollection)
55 forwardResult = eltwiseSumLayerForward.compute()
57 printTensor(forwardResult.getResult(layers.forward.value),
58 "Forward element-wise sum layer result (first 5 rows):", 5)
59 printNumericTable(forwardResult.getLayerDataNumericTable(layers.eltwise_sum.auxNumberOfCoefficients),
60 "Forward element-wise sum layer number of inputs (number of coefficients)", 1)
63 eltwiseSumLayerBackward = layers.eltwise_sum.backward.Batch()
66 eltwiseSumLayerBackward.input.setInput(layers.backward.inputGradient, readTensorFromCSV(datasetName))
67 eltwiseSumLayerBackward.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
70 backwardResult = eltwiseSumLayerBackward.compute()
72 for i
in range(tensorDataCollection.size()):
73 printTensor(backwardResult.getResultLayerData(layers.backward.resultLayerData, i),
74 "Backward element-wise sum layer backward result (first 5 rows):", 5)