56 from daal.algorithms.neural_networks
import layers
58 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
59 if utils_folder
not in sys.path:
60 sys.path.insert(0, utils_folder)
61 from utils
import printNumericTable, printTensor, readTensorFromCSV
64 datasetName = os.path.join(
"..",
"data",
"batch",
"layer.csv")
67 if __name__ ==
"__main__":
70 tensorDataCollection = layers.LayerData()
71 for i
in range(nInputs):
72 tensorDataCollection[i] = readTensorFromCSV(datasetName)
75 eltwiseSumLayerForward = layers.eltwise_sum.forward.Batch()
78 eltwiseSumLayerForward.input.setInputLayerData(layers.forward.inputLayerData, tensorDataCollection)
81 forwardResult = eltwiseSumLayerForward.compute()
83 printTensor(forwardResult.getResult(layers.forward.value),
84 "Forward element-wise sum layer result (first 5 rows):", 5)
85 printNumericTable(forwardResult.getLayerDataNumericTable(layers.eltwise_sum.auxNumberOfCoefficients),
86 "Forward element-wise sum layer number of inputs (number of coefficients)", 1)
89 eltwiseSumLayerBackward = layers.eltwise_sum.backward.Batch()
92 eltwiseSumLayerBackward.input.setInput(layers.backward.inputGradient, readTensorFromCSV(datasetName))
93 eltwiseSumLayerBackward.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
96 backwardResult = eltwiseSumLayerBackward.compute()
98 for i
in range(tensorDataCollection.size()):
99 printTensor(backwardResult.getResultLayerData(layers.backward.resultLayerData, i),
100 "Backward element-wise sum layer backward result (first 5 rows):", 5)