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workbench.main.js:3313 [Extension Host] debugger listening on port 41068
workbench.main.js:3311 Extension Host
workbench.main.js:3311 Debugger listening on ws://127.0.0.1:41068/e4a995f0-d848-45d7-836c-3acdce098a58
For help, see: https://nodejs.org/en/docs/inspector

workbench.main.js:238 [Extension Host] (node:22448) [DEP0005] DeprecationWarning: Buffer() is deprecated due to security and usability issues. Please use the Buffer.alloc(), Buffer.allocUnsafe(), or Buffer.from() methods instead.
t.log @ workbench.main.js:238
workbench.main.js:238 [Extension Host] [vscode-icons] v8.7.0 activated!
workbench.main.js:238 [Extension Host] Info Python Extension: 2019-06-07 21:52:01: Display locator refreshing progress, Class name = p, completed in 1ms, , Return Value: undefined
workbench.main.js:238 [Extension Host] Info Python Extension: 2019-06-07 21:52:01: Notify locators are locating, Class name = p, completed in 2ms, , Return Value: undefined

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workbench.main.js:3272 [Extension Host] debugger listening on port 16367
workbench.main.js:3270 Extension Host
workbench.main.js:3270 Debugger listening on ws://127.0.0.1:16367/d86fbd32-94fb-45fe-a384-4880d4073811
For help, see: https://nodejs.org/en/docs/inspector

workbench.main.js:238 [Extension Host] [vscode-icons] v8.7.0 activated!
workbench.main.js:238 [Extension Host] (node:8044) [DEP0005] DeprecationWarning: Buffer() is deprecated due to security and usability issues. Please use the Buffer.alloc(), Buffer.allocUnsafe(), or Buffer.from() methods instead.
t.log @ workbench.main.js:238
workbench.main.js:238 [Extension Host] Info Python Extension: 2019-06-04 01:29:01: Display locator refreshing progress, Class name = p, completed in 1ms, , Return Value: undefined
workbench.main.js:238 [Extension Host] Info Python Extension: 2019-06-04 01:29:01: Notify locators are locating, Class name = p, completed in 2ms, , Return Value: undefined

Coderx7

=> creating model 'simplenetv1_imagenet_3p'
=> Model : simplenetv1_imagenet_3p(
  (features): Sequential(
    (0): Conv2d(3, 64, kernel_size=[3, 3], stride=(2, 2), padding=(1, 1))
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.05, affine=True)
    (2): ReLU(inplace)
    (3): Conv2d(64, 128, kernel_size=[3, 3], stride=(2, 2), padding=(1, 1))
    (4): BatchNorm2d(128, eps=1e-05, momentum=0.05, affine=True)
    (5): ReLU(inplace)
    (6): Conv2d(128, 128, kernel_size=[3, 3], stride=(1, 1), padding=(1, 1))

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# https://github.com/pytorch/vision/blob/master/torchvision/models/__init__.py
import argparse
import os
import shutil
import time
import os, sys, pdb, shutil, time, random, datetime

import torch
import torch.nn as nn
import torch.nn.parallel

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# https://github.com/pytorch/vision/blob/master/torchvision/models/__init__.py
import argparse
import os
import shutil
import time
import os, sys, pdb, shutil, time, random, datetime

import torch
import torch.nn as nn
import torch.nn.parallel

Coderx7

Here's my experience of installing the NVIDIA CUDA kit 8.0 on a fresh install of Ubuntu Desktop 16.04.3 LTS.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install CUDA
• Install cuDNN

Table of contents generated with markdown-toc

1. Install NVIDIA Graphics Driver via apt-get

Coderx7

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

Coderx7

#برای نمایش بلادرنگ نمودار ترینینگ و تست ما 
import numpy as np
from matplotlib import pyplot as plt

class LivePlotNotebook(object):
    """
    Live plot using %matplotlib notebook in jupyter notebook
    original url : https://gist.github.com/wassname/04e77eb821447705b399e8e7a6d082ce
    """

Coderx7

# Dinesh Jayaraman

# Based on code by
# Authors: Fabian Pedregosa <fabian.pedregosa@inria.fr>
#          Olivier Grisel <olivier.grisel@ensta.org>
#          Mathieu Blondel <mathieu@mblondel.org>
#          Gael Varoquaux
# License: BSD 3 clause (C) INRIA 2011

print(__doc__)

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import argparse
import time

start_time=time.time();
################## Argument Parsing #####################################
parser=argparse.ArgumentParser();
parser.add_argument('-s','--solver', default='', type=str); # if empty, solver is created, else read
parser.add_argument('-res', '--resume_from', default='', type=str); #if not empty, resumes training from given file
parser.add_argument('-ft', '--finetune_from', default='', type=str);