My question in brief: Is the Long Short Term Memory Network detailed below appropriately designed to generate new dance sequences, given dance sequence training data? Context: I am working with a dancer who wishes to use a neural network to generate new dance sequences. She sent me the 2016 chor-rnn paper that accomplished this task using an LSTM network with
Tag: keras
Save and load model optimizer state
I have a set of fairly complicated models that I am training and I am looking for a way to save and load the model optimizer states. The “trainer models” consist of different combinations of several other “weight models”, of which some have shared weights, some have frozen weights depending on the trainer, etc. It is a bit too complicated
How do you use Keras LeakyReLU in Python?
I am trying to produce a CNN using Keras, and wrote the following code: I want to use Keras’s LeakyReLU activation layer instead of using Activation(‘relu’). However, I tried using LeakyReLU(alpha=0.1) in place, but this is an activation layer in Keras, and I get an error about using an activation layer and not an activation function. How can I use
What is the use of verbose in Keras while validating the model?
I’m running the LSTM model for the first time. Here is my model: What is the use of verbose while training the model? Answer Check documentation for model.fit here. By setting verbose 0, 1 or 2 you just say how do you want to ‘see’ the training progress for each epoch. verbose=0 will show you nothing (silent) verbose=1 will show
Getting a list of all known classes of vgg-16 in keras
I use the pre-trained VGG-16 model from Keras. My working source code so far is like this: I wound out that the model is trained on 1000 classes. It there any possibility to get the list of the classes this model is trained on? Printing out all the prediction labels is not an option because there are only 5 returned.
Mixture usage of CPU and GPU in Keras
I am building a neural network on Keras, including multiple layers of LSTM, Permute and Dense. It seems LSTM is GPU-unfriendly. So I did research and use But based on my understanding about with, with is try…finally block to ensure that clean-up code is executed. I don’t know whether the following CPU/GPU mixture usage code works or not? Will they
Keras LSTM – why different results with “same” model & same weights?
(NOTE: Properly fixing the RNG state before each model creating as described in comment in comment practically fixed my problem, as within 3 decimals results are consistent, but they aren’t exactly so, so there’s somewhere a hidden source of randomness not fixed by seeding the RNG… probably some lib uses time milisecs or smth…if anyone has an idea on that,
load weights require h5py
Im trying to run a keras model,trying to use pre-trained VGGnet- When i run this Command base_model = applications.VGG16(weights=’imagenet’, include_top=False, input_shape=(img_rows, img_cols, img_channel)) I get this error: I went through some github issues page where a relevant question was asked,but no solutions were given. Any suggestions? Answer Install h5py: Or if using conda:
Keras confusion about number of layers
I’m a bit confused about the number of layers that are used in Keras models. The documentation is rather opaque on the matter. According to Jason Brownlee the first layer technically consists of two layers, the input layer, specified by input_dim and a hidden layer. See the first questions on his blog. In all of the Keras documentation the first
How to disable printing reports after each epoch in Keras?
After each epoch I have printout like below: I am not using built-in epochs, so I would like to disable these printouts and print something myself. How to do that? I am using tensorflow backend if it matters. Answer Set verbose=0 to the fit method of your model.