56 from daal.algorithms.neural_networks
import layers
57 from daal.data_management
import HomogenTensor, TensorIface
59 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
60 if utils_folder
not in sys.path:
61 sys.path.insert(0, utils_folder)
62 from utils
import printTensor
65 datasetFileName = os.path.join(
"..",
"data",
"batch",
"layer.csv")
67 if __name__ ==
"__main__":
71 tensorData = HomogenTensor(inDims, TensorIface.doAllocate, 1.0)
74 transposedConv2dLayerForward = layers.transposed_conv2d.forward.Batch()
75 transposedConv2dLayerForward.input.setInput(layers.forward.data, tensorData)
78 forwardResult = transposedConv2dLayerForward.compute()
80 printTensor(forwardResult.getResult(layers.forward.value),
"Two-dimensional transposed convolution layer result (first 5 rows):", 5, 15)
81 printTensor(forwardResult.getLayerData(layers.transposed_conv2d.auxWeights),
82 "Two-dimensional transposed convolution layer weights (first 5 rows):", 5, 15)
84 gDims = forwardResult.getResult(layers.forward.value).getDimensions()
87 tensorDataBack = HomogenTensor(gDims, TensorIface.doAllocate, 0.01)
90 transposedConv2dLayerBackward = layers.transposed_conv2d.backward.Batch()
91 transposedConv2dLayerBackward.input.setInput(layers.backward.inputGradient, tensorDataBack)
92 transposedConv2dLayerBackward.input.setInputLayerData(layers.backward.inputFromForward, forwardResult.getResultLayerData(layers.forward.resultForBackward))
95 backwardResult = transposedConv2dLayerBackward.compute()
97 printTensor(backwardResult.getResult(layers.backward.gradient),
98 "Two-dimensional transposed convolution layer backpropagation gradient result (first 5 rows):", 5, 15)
99 printTensor(backwardResult.getResult(layers.backward.weightDerivatives),
100 "Two-dimensional transposed convolution layer backpropagation weightDerivative result (first 5 rows):", 5, 15)
101 printTensor(backwardResult.getResult(layers.backward.biasDerivatives),
102 "Two-dimensional transposed convolution layer backpropagation biasDerivative result (first 5 rows):", 5, 15)