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@sizmailov
sizmailov / Base.h
Last active October 4, 2019 12:07
Module dependency in pybind11
#pragma once
struct Foo {
};
@spro
spro / pytorch-simple-rnn.py
Last active April 25, 2022 10:50
PyTorch RNN training example
import torch
import torch.nn as nn
from torch.nn import functional as F
from torch.autograd import Variable
from torch import optim
import numpy as np
import math, random
# Generating a noisy multi-sin wave
@jubjamie
jubjamie / pb_viewer.py
Created March 31, 2017 10:01
Load .pb into Tensorboard
import tensorflow as tf
from tensorflow.python.platform import gfile
with tf.Session() as sess:
model_filename ='PATH_TO_PB.pb'
with gfile.FastGFile(model_filename, 'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
g_in = tf.import_graph_def(graph_def)
LOGDIR='/logs/tests/1/'
train_writer = tf.summary.FileWriter(LOGDIR)
@baraldilorenzo
baraldilorenzo / readme.md
Last active November 21, 2023 22:41
VGG-16 pre-trained model for Keras

##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

@PurpleBooth
PurpleBooth / README-Template.md
Last active April 22, 2024 11:45
A template to make good README.md

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

@aronwc
aronwc / lda.py
Last active January 21, 2020 05:46
Example using GenSim's LDA and sklearn
""" Example using GenSim's LDA and sklearn. """
import numpy as np
from gensim import matutils
from gensim.models.ldamodel import LdaModel
from sklearn import linear_model
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer
@yusugomori
yusugomori / RestrictedBoltzmannMachine.py
Last active December 6, 2021 21:07
Restricted Boltzmann Machine (RBM) using Contrastive Divergence
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Restricted Boltzmann Machine (RBM)
References :
- Y. Bengio, P. Lamblin, D. Popovici, H. Larochelle: Greedy Layer-Wise
Training of Deep Networks, Advances in Neural Information Processing
Systems 19, 2007