The -verbose:class command line option to dump out the To find out which ext dir java.exe is loading from, use Them by setting the java system property. Want and you can put them wherever you please. M圜lassĪs of Java version 1.6, you can have as many ext dirs as you You never know for sure where your javac.exe or
#POSTGRESQL SET CLASSPATH FOR JAVA MAC TERMINAL WINDOWS#
In reality I've got a view which has an NSComboBox as a subview along with some other subviews, but I've created a simple example to display the same issue I'm seeing.įor some reason, the text field isn't exactly vertically entered like I'd expect. I'm trying to layout an NSComboBox in a Mac app and I'm getting some weird behaviour. I really can't wrap my head around why it expects weights of shape is ? That appears nowhere in the summary() command.ĭoes anyone have an idea about what is going wrong here?ĮDIT: I tried to do the same in Python and everything seems to work: import tensorflow as tf Op own name: "d3142824-92ad-41c4-99e0-1111f4f75a5f" - Please see above message (printed out from c++) for a possible cause of error. Attempted to execute with 3 inputs, 1 outputs, 0 targs,0 bargs and 6 iargs. Now causes the following error: Error at :ĬUSTOM CONV1D OP: wrong shape of weights array, expected is, but got instead !Įxception in thread "main" 14:04:45.925 ERROR. - Failed to execute op conv1d. Running the command INDArray output = model.output(input,false) LayerName (LayerType) nIn,nOut TotalParams ParamsShapeĬonv1d (Convolution1DLayer) 1,6 18 b:) The output of model.summary() in Eclipse is: = I load the model with MultiLayerNetwork model = KerasModelImport.importKerasSequentialModelAndWeights('my_model.h5') In Eclipse I am using DeepLearning4J as it provides keras features. I saved the trained model with model.save('my_model.h5'). Max_pooling1d_3 (MaxPooling1 (None, 2, 48) 0 Max_pooling1d_2 (MaxPooling1 (None, 3, 24) 0 Max_pooling1d_1 (MaxPooling1 (None, 4, 12) 0 Max_pooling1d (MaxPooling1D) (None, 5, 6) 0 Model.add(1D(filters=6, kernel_size=2, strides=1, padding="same"))įor better readability, the output of model.summary() is: Model: "sequential" Model.add(1D(filters=48, kernel_size=2, strides=1, padding="same"))
Model.add(1D(filters=24, kernel_size=2, strides=1, padding="same")) Model.add(1D(filters=12, kernel_size=2, strides=1, padding="same")) Its configuration looks as follows: # define model I have a model that was constructed and trained with Tensorflow in Python, and I need to use it in Java with Eclipse.
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