Skip to content

Tag: keras

Keras and Tensorflow OS resource requirement

I keep getting F tensorflow/core/platform/default/] Check failed: ret == 0 (11 vs. 0)Thread tf_data_private_threadpool creation via pthread_create() failed. errors during training, although the machine is quite powerful: altogether 64 logical cores ulimit -s gives 32768, ulimit -u gives 1030608 I want to train the following network with a bunch of online generated 512*512 grayscale images along with two additional parameters

layer.get_weights() is not equal in the same model layers

Why not all the layer weights equal: Here is the output: The a_weights == b_weights are not all the “True”. What’s the problem? Answer Notice that the only time a_weights == b_weights is True, is when you are referencing a layer, which does not have any weights. np.array_equal is returning False because you are actually comparing lists of arrays and

Prediction with keras embedding leads to indices not in list

I have a model that I trained with For the embedding I use Glove as a pre-trained embedding dictionary. Where I first build the tokenizer and text sequence with: t = Tokenizer() t.fit_on_texts(all_text) and then I’m calculating the embedding matrix with: now I’m using a new dataset for the prediction. This leads to an error: Node: ‘model/synopsis_embedd/embedding_lookup’ indices[38666,63] = 136482