5916
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-76-52ca495a8e09> in <module>() ----> 1 model, layer_dict, classifier_sizes = load_model('./model_0.h5') /Users/pierluigiferrari/anaconda/envs/carnd-term1/lib/python3.5/site-packages/keras/models.py in load_model(filepath, custom_objects) 258 metrics=metrics, 259 l
Can't load `Sequential` with custom layers · Issue #5956 · keras-team/keras · GitHub
#!/usr/bin/env python import os from keras.models import Model, Sequential, load_model from keras.layers import Input, InputLayer from keras.engine.topology import Layer class MyLayer(Layer): def __init__(self, **kwargs): super(MyLayer, self).__init__(**kwargs) def call(self, inputs): return inputs + 1 def compute_output_shape(self, input_shape): return input_shape def get_config(self): return sup
out of memory when using BatchNormalization on convolutional layers · Issue #6661 · keras-team/keras
Please make sure that the boxes below are checked before you submit your issue. If your issue is an implementation question, please ask your question on StackOverflow or join the Keras Slack channel and ask there instead of filing a GitHub issue. Thank you! [v ] Check that you are up-to-date with the master branch of Keras. You can update with: pip install git+git://github.com/fchollet/keras.git -
LSTM Autoencoder · Issue #1401 · keras-team/keras
Hello everyone and happy new year I am trying to create an LSTM Autoencoder as shown on the image bellow. The encoder consumes the input "the cat sat", and creates a vector depicted as the big red arrow. The decoder takes this vector and tries to reconstruct the sequence given the position in the sentence. I would like to save this vector (big red arrow) to use it on another model. The code i have
Refactor regularizers and add add_weight method. by fchollet · Pull Request #4703 · keras-team/keras
Keras use only single thread · Issue #1245 · keras-team/keras
I have installed keras on a redhat 6 server, it is really a attractive framework cause it is really easy to build a deep neural network. However, I found my keras use only single thread(or single core). I ran examples given in the source code package, such as "mnist_mlp.py", and used "top" command, found the usage of CPU is 100%, never more than CPU, I have 6 cores, each with four threads, no GPU,
Keras 2.0 release notes
The nb_epoch argument has been renamed epochs everywhere. The methods fit_generator, evaluate_generator and predict_generator now work by drawing a number of batches from a generator (number of training steps), rather than a number of samples. samples_per_epoch was changed to steps_per_epoch in fit_generator. It now refers to the number of batches an epoch is considered as done. nb_val_samples was
A concrete example for using data generator for large datasets such as ImageNet · Issue #1627 · keras-team/keras
I am already aware of some discussions on how to use Keras for very large datasets (>1,000,000 images) such as this and this. However, for my scenario, I can't figure out the appropriate way to use the ImageDataGenerator or write my own dataGenerator. Specifically, I have the following four questions: From this link: when we do datagen.fit(X_sample), do we assume that X_sample is a big enough chun
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keras/examples at master · keras-team/keras
Issues in Keras model loading in Tensorflow Serving · Issue #2310 · keras-team/keras
Batch Normalization Problem · Issue #1446 · keras-team/keras
changing loss weight during training · Issue #6446 · keras-team/keras
changeable loss weights for multiple output · Issue #2595 · keras-team/keras
Does it make sense that the validation loss is lower than training loss? · Issue #472 · keras-team/keras
keras/topology.py at master · keras-team/keras · GitHub
Incorporating Word Vectors rather than using an Embedding class · Issue #853 · keras-team/keras
None is not supported in input_shape [bug] · Issue #5900 · keras-team/keras![None is not supported in input_shape [bug] · Issue #5900 · keras-team/keras](https://cdn-ak-scissors.b.st-hatena.com/image/square/f3b23ea18582763f7fe3950c8b608e59cbecd218/height=288;version=1;width=512/https%3A%2F%2Fopengraph.githubassets.com%2Fbe4c96e0b64dc5304fb220281174e37548224728be1cfc311301231353dcb379%2Fkeras-team%2Fkeras%2Fissues%2F5900)
keras/mnist_mlp.py at master · keras-team/keras · GitHub
Memory leak during model.fit() · Issue #5935 · keras-team/keras
How to obtain the gradient of each parameter in the last epoch of training · Issue #2226 · keras-team/keras
