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Code for reproducing key results in the paper "Improving Variational Inference with Inverse Autoregressive Flow"
class IAFLayer(object): def __init__(self, hps, mode, downsample): self.hps = hps self.mode = mode self.downsample = downsample def up(self, input, **_): hps = self.hps h_size = hps.h_size z_size = hps.z_size stride...
I am executing tf_train.py (num_gpus=1). In forward function for two for loops it is running fine for i=0,j=0;i=0,j=1; but continuously it is taking huge memory. For i=1,j=0 of for loop...
After some fixes to the summary & split calls (i.e. they were refactored in tf1.0) I still can't get this code to work: ```bash (.venv) ➜ iaf git:(master) ✗ CIFAR10_PATH="./CIFAR10"...
Added learning rate bias correction and, `m_t = m.assign(tf.maximum(beta2_t * m + eps, tf.abs(grad)))` this line is wrong because if `(beta2_t * m+eps)
If I run the TensorFlow version of this code (`tf_train.py`) with https://github.com/openai/iaf/pull/8 applied, I get a NaN within the first few iterations and training stops. If I remove that change,...
Hi, I am running the tf_train.py and tf_utils code out of the box. Our tensorflow's version is 1.3.0 and GPU is GeForce GTX TITAN X. The conv2d function in tf_utils/layers.py...
Why are we using constant variance for the generating network of autoencoder instead of learning it like mean from the network itself. What advantage does it have over the learnable...
In line 70 I think there is a small mistake, it should be: `int(input_shape[2] * strides[2]), int(input_shape[3] * strides[3])]` It's not a major bug, as it would throw an error...
In line 93 of the above file, it looks like the normalisation is performed over the `out_channels`, instead of `in_channels`. I think instead it should be: `v_norm = tf.nn.l2_normalize(v, [0,...
Using gpu device 0: GeForce GTX 980 (CNMeM is enabled with initial size: 80.0% of memory, cuDNN 5105) /home/vismod/anaconda2/envs/tensorflow/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.py:600: UserWarning: Your cuDNN version is more recent than the one Theano...
