AbdelmajidB
AbdelmajidB
/ Unet3d.java
Last active
May 14, 2019 01:02
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| public ComputationGraphConfiguration.GraphBuilder unetBuilder() { | |
| ComputationGraphConfiguration.GraphBuilder graph = new NeuralNetConfiguration.Builder().seed(seed) | |
| .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT) | |
| .updater(updater) | |
| .weightInit(weightInit) | |
| .l2(5e-5) | |
| .miniBatch(true) | |
| .cacheMode(cacheMode) | |
| .trainingWorkspaceMode(workspaceMode) |
AbdelmajidB
/ MergeVertex.java
Created
May 14, 2019 02:00
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| /******************************************************************************* | |
| * Copyright (c) 2015-2018 Skymind, Inc. | |
| * | |
| * This program and the accompanying materials are made available under the | |
| * terms of the Apache License, Version 2.0 which is available at | |
| * https://www.apache.org/licenses/LICENSE-2.0. | |
| * | |
| * Unless required by applicable law or agreed to in writing, software | |
| * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT | |
| * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the |
AbdelmajidB
/ error
Last active
May 14, 2019 14:17
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| Exception in thread "main" org.deeplearning4j.exception.DL4JInvalidInputException: Got rank 4 array as input to Convolution3DLayer (layer name = conv1-1, layer index = 1) with shape [1, 1, 256, 256]. Expected rank 5 array with shape [minibatchSize, numChannels, inputHeight, inputWidth, inputDepth]. (layer name: conv1-1, layer index: 1, layer type: Convolution3DLayer) | |
| at org.deeplearning4j.nn.layers.convolution.Convolution3DLayer.preOutput(Convolution3DLayer.java:189) | |
| at org.deeplearning4j.nn.layers.convolution.ConvolutionLayer.activate(ConvolutionLayer.java:437) | |
| at org.deeplearning4j.nn.graph.vertex.impl.LayerVertex.doForward(LayerVertex.java:111) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.ffToLayerActivationsInWS(ComputationGraph.java:2116) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.computeGradientAndScore(ComputationGraph.java:1369) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.computeGradientAndScore(ComputationGraph.java:1338) | |
| at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradien |
AbdelmajidB
/ keras_error
Created
June 11, 2019 10:08
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| Exception in thread "main" org.deeplearning4j.nn.modelimport.keras.exceptions.InvalidKerasConfigurationException: Model configuration attribute missing from C:\Users\bismi\AppData\Local\Temp\DL4JKerasModelImport3875863276192533560.bin archive.. For more information, see http://deeplearning4j.org/model-import-keras. | |
| at org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder.modelHdf5Filename(KerasModelBuilder.java:230) | |
| at org.deeplearning4j.nn.modelimport.keras.KerasModelImport.importKerasModelAndWeights(KerasModelImport.java:171) | |
| at org.deeplearning4j.nn.modelimport.keras.KerasModelImport.importKerasModelAndWeights(KerasModelImport.java:73) | |
| at ma.enset.brain_tumor_segmentation.SemanticSegmentationLoadKeras.run(SemanticSegmentationLoadKeras.java:49) | |
| at ma.enset.brain_tumor_segmentation.SemanticSegmentationLoadKeras.main(SemanticSegmentationLoadKeras.java:132) |
AbdelmajidB
/ keras_error
Created
June 11, 2019 10:08
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| Exception in thread "main" org.deeplearning4j.nn.modelimport.keras.exceptions.InvalidKerasConfigurationException: Model configuration attribute missing from C:\Users\bismi\AppData\Local\Temp\DL4JKerasModelImport3875863276192533560.bin archive.. For more information, see http://deeplearning4j.org/model-import-keras. | |
| at org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder.modelHdf5Filename(KerasModelBuilder.java:230) | |
| at org.deeplearning4j.nn.modelimport.keras.KerasModelImport.importKerasModelAndWeights(KerasModelImport.java:171) | |
| at org.deeplearning4j.nn.modelimport.keras.KerasModelImport.importKerasModelAndWeights(KerasModelImport.java:73) | |
| at ma.enset.brain_tumor_segmentation.SemanticSegmentationLoadKeras.run(SemanticSegmentationLoadKeras.java:49) | |
| at ma.enset.brain_tumor_segmentation.SemanticSegmentationLoadKeras.main(SemanticSegmentationLoadKeras.java:132) |
AbdelmajidB
/ keras_error2
Created
June 11, 2019 12:58
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| Exception in thread "main" org.deeplearning4j.nn.modelimport.keras.exceptions.InvalidKerasConfigurationException: Requires model configuration as either JSON or YAML string.. For more information, see http://deeplearning4j.org/model-import-keras. | |
| at org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils.parseModelConfig(KerasModelUtils.java:333) | |
| at org.deeplearning4j.nn.modelimport.keras.KerasModel.<init>(KerasModel.java:120) | |
| at org.deeplearning4j.nn.modelimport.keras.KerasModel.<init>(KerasModel.java:96) | |
| at org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder.buildModel(KerasModelBuilder.java:307) | |
| at ma.enset.brain_tumor_segmentation.SemanticSegmentationLoadKeras.run(SemanticSegmentationLoadKeras.java:55) | |
| at ma.enset.brain_tumor_segmentation.SemanticSegmentationLoadKeras.main(SemanticSegmentationLoadKeras.java:138) |
AbdelmajidB
/ error
Created
June 21, 2019 10:34
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| Exception in thread "main" java.lang.IllegalStateException: Input and label arrays do not have same shape: [24, 3, 96, 96] vs. [24, 1, 96, 96] | |
| at org.nd4j.base.Preconditions.throwStateEx(Preconditions.java:641) | |
| at org.nd4j.base.Preconditions.checkState(Preconditions.java:340) | |
| at org.deeplearning4j.nn.layers.convolution.CnnLossLayer.backpropGradient(CnnLossLayer.java:80) | |
| at org.deeplearning4j.nn.graph.vertex.impl.LayerVertex.doBackward(LayerVertex.java:149) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.calcBackpropGradients(ComputationGraph.java:2663) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.computeGradientAndScore(ComputationGraph.java:1378) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.computeGradientAndScore(ComputationGraph.java:1338) | |
| at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:160) | |
| at org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(StochasticGradientDescent.java:63) |
AbdelmajidB
/ tiff3d.java
Created
June 25, 2019 08:12
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| ImageRecordReader recordReader = new ImageRecordReader(height, width, channels, labelMaker); | |
| recordReader.initialize(train); | |
| Field f = BaseImageRecordReader.class.getDeclaredField("imageLoader"); | |
| f.setAccessible(true); | |
| f.set(recordReader, new NativeImageLoader(height, width, 1, BaseImageLoader.MultiPageMode.MINIBATCH)); | |
| int labelIndex = 1; //You have 2 Writables ("columns") - index 0 is features image NDArrayWritable, index 1 is labels image NDArrayWritable | |
| // DataSet Iterator | |
| DataSetIterator dataIter = new RecordReaderDataSetIterator(recordReader, batchSize, labelIndex, labelIndex, true); |
AbdelmajidB
/ MyPathLabelGenerator3d.java
Last active
June 25, 2019 08:45
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| package ma.enset.brain_tumor_segmentation; | |
| import java.io.File; | |
| import java.io.IOException; | |
| import java.net.URI; | |
| import java.util.Arrays; | |
| import org.datavec.api.io.labels.PathLabelGenerator; | |
| import org.datavec.api.writable.NDArrayWritable; | |
| import org.datavec.api.writable.Writable; |
AbdelmajidB
/ eval.java
Created
November 25, 2019 16:28
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| while (Iter.hasNext()) { | |
| DataSet next = Iter.next(); | |
| INDArray out2d = modelT.outputSingle(next.getFeatures()).permute(0,2,3,1).dup().reshape('c',height*width,1); | |
| INDArray labels2d = next.getLabels().permute(0,2,3,1).dup().reshape('c',height*width,1); | |
| if(k==0) { | |
| e.eval(labels2d, out2d); | |
| log.info(e.stats()); | |
| } | |
| k++; | |
| } |
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