Found the solution: I reinstalled nvidia-381, CUDA-8.0 (using the runfile) and cuDNN 6.0. Then I added the following in my .bashrc: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64/
There is just one cross (Shannon) entropy defined as: H(P||Q) = – SUM_i P(X=i) log Q(X=i) In machine learning usage, P is the actual (ground truth) distribution, and Q is the predicted distribution. All the functions you listed are just helper functions which accepts different ways to represent P and Q. There are basically 3 … Read more
The simplest way I can think of, if you have this matrix correctly shaped, is to derive the Dense layer and simply add the matrix in the code multiplying the original weights: class CustomConnected(Dense): def __init__(self,units,connections,**kwargs): #this is matrix A self.connections = connections #initalize the original Dense with all the usual arguments super(CustomConnected,self).__init__(units,**kwargs) def call(self,inputs): … Read more
You can achieve the effect of np.repeat() using a combination of tf.tile() and tf.reshape(): idx = tf.range(len(yp)) idx = tf.reshape(idx, [-1, 1]) # Convert to a len(yp) x 1 matrix. idx = tf.tile(idx, [1, len(yp)]) # Create multiple columns. idx = tf.reshape(idx, [-1]) # Convert back to a vector. You can simply compute jdx using … Read more
As suggested by François Chollet (creator of Keras) in his book, one way to handle missing values is to replace them with zero: In general, with neural networks, it’s safe to input missing values as 0, with the condition that 0 isn’t already a meaningful value. The network will learn from exposure to the data … Read more
The data format for storing training/test is defined in the FSNS paper https://arxiv.org/pdf/1702.03970.pdf (Table 4). To store tfrecord files with tf.Example protos you can use tf.python_io.TFRecordWriter. There is a nice tutorial, an existing answer on the stackoverflow and a short gist. Assume you have an numpy ndarray img which has num_of_views images stored side-by-side (see … Read more
First, for the following error: ImportError: libcudart.so.8.0: cannot open shared object file: No such file or directory make sure your LD_LIBRARY_PATH includes your lib64 directory in whichever path you installed your cuda package in. You can do this by adding an export line in your .bashrc. For Omar, it looked like the following: I fixed … Read more
TL;DR: If you want tf.cond() to perform a side effect (like an assignment) in one of the branches, you must create the op that performs the side effect inside the function that you pass to tf.cond(). The behavior of tf.cond() is a little unintuitive. Because execution in a TensorFlow graph flows forward through the graph, … Read more
Assume you are using Tensorflow 2.0 preview release which has eager execution enabled by default. There is a disable_eager_execution() in v1 API, which you can put in the front of your code like: import tensorflow as tf tf.compat.v1.disable_eager_execution() On the other hand, if you are not using 2.0 preview, please check if you accidentally enabled … Read more