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problem 1: i changed my code from fit to fit_generator, however, i found it converged slower than using fit. Using fit it converges at 5th epoch, however, it doesn't converge even at 10th epoch when i change to fit_generator. Moreover, when validation_data also uses fit_generator, the performance becomes much worse. Is my generator function has errors? def batch_iter(x, y, batch_size): """ Generat
Hi! Keras: 2.0.4 I recently spent some time trying to build metrics for multi-class classification outputting a per class precision, recall and f1 score. I want to have a metric that's correctly aggregating the values out of the different batches and gives me a result on the global training process with a per class granularity. The way I understand it is currently working is by calling the functio
Keras examples directory Vision models examples mnist_mlp.py Trains a simple deep multi-layer perceptron on the MNIST dataset. mnist_cnn.py Trains a simple convnet on the MNIST dataset. cifar10_cnn.py Trains a simple deep CNN on the CIFAR10 small images dataset. cifar10_cnn_capsule.py Trains a simple CNN-Capsule Network on the CIFAR10 small images dataset. cifar10_resnet.py Trains a ResNet on the
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