32 from daal.algorithms.neural_networks
import layers
33 from daal.data_management
import HomogenTensor, TensorIface
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
41 datasetFileName = os.path.join(
"..",
"data",
"batch",
"layer.csv")
43 if __name__ ==
"__main__":
47 tensorData = HomogenTensor(inDims, TensorIface.doAllocate, 1.0)
50 transposedConv2dLayerForward = layers.transposed_conv2d.forward.Batch()
51 transposedConv2dLayerForward.input.setInput(layers.forward.data, tensorData)
54 forwardResult = transposedConv2dLayerForward.compute()
56 printTensor(forwardResult.getResult(layers.forward.value),
"Two-dimensional transposed convolution layer result (first 5 rows):", 5, 15)
57 printTensor(forwardResult.getLayerData(layers.transposed_conv2d.auxWeights),
58 "Two-dimensional transposed convolution layer weights (first 5 rows):", 5, 15)
60 gDims = forwardResult.getResult(layers.forward.value).getDimensions()
63 tensorDataBack = HomogenTensor(gDims, TensorIface.doAllocate, 0.01)
66 transposedConv2dLayerBackward = layers.transposed_conv2d.backward.Batch()
67 transposedConv2dLayerBackward.input.setInput(layers.backward.inputGradient, tensorDataBack)
68 transposedConv2dLayerBackward.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
71 backwardResult = transposedConv2dLayerBackward.compute()
73 printTensor(backwardResult.getResult(layers.backward.gradient),
74 "Two-dimensional transposed convolution layer backpropagation gradient result (first 5 rows):", 5, 15)
75 printTensor(backwardResult.getResult(layers.backward.weightDerivatives),
76 "Two-dimensional transposed convolution layer backpropagation weightDerivative result (first 5 rows):", 5, 15)
77 printTensor(backwardResult.getResult(layers.backward.biasDerivatives),
78 "Two-dimensional transposed convolution layer backpropagation biasDerivative result (first 5 rows):", 5, 15)