32 from daal.algorithms.neural_networks
import layers
33 from daal.algorithms.neural_networks.layers
import loss
34 from daal.algorithms.neural_networks.layers.loss
import logistic_cross
36 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
37 if utils_folder
not in sys.path:
38 sys.path.insert(0, utils_folder)
39 from utils
import printTensor, readTensorFromCSV
42 datasetName = os.path.join(
"..",
"data",
"batch",
"logistic_cross_entropy_layer.csv")
43 datasetGroundTruthName = os.path.join(
"..",
"data",
"batch",
"logistic_cross_entropy_layer_ground_truth.csv")
45 if __name__ ==
"__main__":
48 tensorData = readTensorFromCSV(datasetName)
49 groundTruth = readTensorFromCSV(datasetGroundTruthName)
52 logisticCrossLayerForward = loss.logistic_cross.forward.Batch(method=loss.logistic_cross.defaultDense)
55 logisticCrossLayerForward.input.setInput(layers.forward.data, tensorData)
56 logisticCrossLayerForward.input.setInput(loss.forward.groundTruth, groundTruth)
59 forwardResult = logisticCrossLayerForward.compute()
62 printTensor(forwardResult.getResult(layers.forward.value),
"Forward logistic cross-entropy layer result (first 5 rows):", 5)
63 printTensor(forwardResult.getLayerData(loss.logistic_cross.auxGroundTruth),
"Logistic Cross-Entropy layer ground truth (first 5 rows):", 5)
66 logisticCrossLayerBackward = logistic_cross.backward.Batch(method=loss.logistic_cross.defaultDense)
69 logisticCrossLayerBackward.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
72 backwardResult = logisticCrossLayerBackward.compute()
75 printTensor(backwardResult.getResult(layers.backward.gradient),
"Backward logistic cross-entropy layer result (first 5 rows):", 5)