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Generative Handwriting using LSTM Mixture Density Network with TensorFlow

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I'm getting crappy-looking samples from networks that seem to train properly. Loss converges nicely (see last screenshot), but samples don't compare with @hardmaru's results. Here are some examples... Any ideas...

First, thanks a lot for this very cool code! Running the pretrained model with the suggested command: python sample.py --filename example_name --sample_length 1000 Produces this error: WARNING:tensorflow:: Using a concatenated...

I think it's better to provide a `requirements.txt`, indicating the python libraries and version it needed .

Hi, thanks for the nice work. In the paper, the training loss can go down to -1000. I can only get to -5. I wonder how your training loss curve...

When I run train.py, got this errors. I think is kind of version problems, my tf version is 1.3 File "/home/lxt/tf_project/HyperNetwork/write-rnn-tensorflow/model.py", line 50, in __init__ outputs, state_out = tf.contrib.legacy_seq2seq.rnn_decoder(inputs, self.state_in,...

When i tried to run train.py file..... I got the following error **"IOError: [Errno 2] No such file or directory: './data/strokes_training_data.cpkl'** Please provide some suggestions