michaellihs

tmux Cheat Sheet

Table of Contents

• General Usage
• Shortcuts
• Commands
• Scripting tmux
• Configuring tmux

cbaziotis

from keras import backend as K, initializers, regularizers, constraints
from keras.engine.topology import Layer


def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:

buoto

# top-most EditorConfig file
root = true

# Unix-style newlines with a newline ending every file
[*]
charset = utf-8
trim_trailing_whitespace = true
end_of_line = lf
insert_final_newline = true

mstfldmr

from matplotlib import pyplot as plt
import cv2

img = cv2.imread('/Users/mustafa/test.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

plt.imshow(gray)
plt.title('my picture')
plt.show()

mrry

# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

kevinzakka

"""
Create train, valid, test iterators for CIFAR-10 [1].
Easily extended to MNIST, CIFAR-100 and Imagenet.

[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4
"""

import torch
import numpy as np

ruslangrimov

import tensorflow as tf
from tensorflow.python.client import timeline
from keras import backend as K

run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
run_metadata = tf.RunMetadata()

model = ...  # A Keras model

fn = K.function(model.inputs, model.outputs, options=run_options, run_metadata=run_metadata)

hsinewu

#include <iostream>
#include <algorithm>
using namespace std;

int find_substring(string str, string pattern) {

	// Step 0. Should not be empty string
	if( str.size() == 0 || pattern.size() == 0)
		return -1;

maxim5

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import print_function

__author__ = 'maxim'

import numpy as np
import gensim
import string

atinfinity

#include <opencv2/core.hpp>
#include <opencv2/core/cuda.hpp>
#include <cuda_runtime.h>
#include <device_launch_parameters.h>
#include <iostream>

int main(int argc, const char * argv[])
{
    cudaFree(0); // dummy call