Classic Networks
LeNet-5: LeCun et al, "Gradient-Based Learning Applied to Document Recognition": http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf
AlexNet: Krizhevsky et al, "ImageNet Classification with Deep Convolutional Neural Networks": https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
VGG-16: Simonyan et al, "Very Deep Convolutional Networks for Large-Scale Image Recognition": https://arxiv.org/pdf/1409.1556.pdf
Resnets
| """RNN Example.""" | |
| from __future__ import print_function, division | |
| import numpy as np | |
| import tensorflow as tf | |
| import matplotlib.pyplot as plt | |
| num_epochs = 100 | |
| total_series_length = 50000 | |
| truncated_backprop_length = 15 | |
| state_size = 4 |
| """Example RNN.""" | |
| from __future__ import print_function, division | |
| import numpy as np | |
| import tensorflow as tf | |
| import matplotlib.pyplot as plt | |
| num_epochs = 100 | |
| total_series_length = 50000 | |
| truncated_backprop_length = 15 | |
| state_size = 4 |
| """Example RNN.""" | |
| from __future__ import print_function, division | |
| import numpy as np | |
| import tensorflow as tf | |
| import matplotlib.pyplot as plt | |
| num_epochs = 100 | |
| total_series_length = 50000 | |
| truncated_backprop_length = 15 | |
| state_size = 4 |
| #!/bin/bash | |
| usage() | |
| { | |
| cat << EOF | |
| usage: $0 options | |
| This script set ownership for all table, sequence and views for a given database | |
| Credit: Based on http://stackoverflow.com/a/2686185/305019 by Alex Soto |
