| """adapted from https://github.com/OlavHN/bnlstm to store separate population statistics per state""" | |
| import tensorflow as tf, numpy as np | |
| RNNCell = tf.nn.rnn_cell.RNNCell | |
| class BNLSTMCell(RNNCell): | |
| '''Batch normalized LSTM as described in arxiv.org/abs/1603.09025''' | |
| def __init__(self, num_units, is_training_tensor, max_bn_steps, initial_scale=0.1, activation=tf.tanh, decay=0.95): | |
| """ | |
| * max bn steps is the maximum number of steps for which to store separate population stats | |
| """ |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman