rmcelreath

# prior - likelihood conflict

library(rethinking)

yobs <- 0

mtt <- ulam(
    alist(
        y ~ dstudent(2,mu,1),
        mu ~ dstudent(2,10,1)

guilhermepontes

Get the old VSCode icon back!! 🔥 🔥

First download the new old icon: https://cl.ly/mzTc (based on this)

You can also use the icon you want, but you need to convert it to .icns. You can use this service to convert PNG to ICNS.

Go to Applications and find VSCode, right click there and choose Get Info. Drag 'n drop the new icon.

Dref360

class weighted_categorical_crossentropy:
    def __init__(self, weights):
        self.weights = weights
        self.__name__ = 'wcentroid_loss'

    def __call__(self, y_true, y_pred):
        class0 = K.ones_like(y_pred)[:, :, :, 0] * self.weights[0]
        class1 = K.ones_like(y_pred)[:, :, :, 0] * self.weights[1]
        x = K.tf.where(y_true[:, :, :, 0] > 0, class0, class1)
        result = x * K.categorical_crossentropy(y_pred, y_true)

eldar

import datetime as dt

import tensorflow as tf
import tensorflow.contrib.slim as slim
from tensorflow.contrib.slim.nets import resnet_v1
import threading

from PoseDataset import PoseDataset
from TrainParams import TrainParams

harpone

import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np

# Define custom py_func which takes also a grad op as argument:
def py_func(func, inp, Tout, stateful=True, name=None, grad=None):
    
    # Need to generate a unique name to avoid duplicates:
    rnd_name = 'PyFuncGrad' + str(np.random.randint(0, 1E+8))
    

kastnerkyle

# Author: Kyle Kastner
# License: BSD 3-Clause
# For a reference on parallel processing in Python see tutorial by David Beazley
# http://www.slideshare.net/dabeaz/an-introduction-to-python-concurrency
# Loosely based on IBM example
# http://www.ibm.com/developerworks/aix/library/au-threadingpython/
# If you want to download all the PASCAL VOC data, use the following in bash...
"""
#! /bin/bash
# 2008
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2008/VOCtrainval_14-Jul-2008.tar
# 2009
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2009/VOCtrainval_11-May-2009.tar
# 2010
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2010/VOCtrainval_03-May-2010.tar
# 2011
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2011/VOCtrainval_25-May-2011.tar
# 2012
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
# Latest devkit
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCdevkit_18-May-2011.tar
"""
try:
    import Queue
except ImportError:
    import queue as Queue
import threading
import ti

djsutherland

#!/bin/bash

CUDA_LIB_DIR=/usr/local/cuda/lib
CUDA_VERSION=7.5
CUDA_LIBS="cublas cudart curand"

CUDNN_LIB_DIR=/usr/local/cuda/cudnn-3/lib
CUDNN_VERSION=7.0
CUDNN_LIBS="cudnn"

zchee

CUDA7.5

Now, CUDA did not compatible Apple clang 7.0.0 also Xcode7.0.

e.g,

> cd /Developer/NVIDIA/CUDA-7.5/samples/0_Simple/asyncAPI

> clang -v
Apple LLVM version 7.0.0 (clang-700.1.75)

willurd

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

raibread

#!/usr/bin/env bash

#################################################################################################
# This script installls Torch7 and it's various dependencies.
#
# The script is adapted from:
# https://github.com/clementfarabet/torchinstall/blob/master/install
#
# The above didn't quite work for me on macosx (10.8.2) so the following adjustments were made:
# (1) install gcc 4.7.2 and set as compilers used in Torch build so open OpenMP works