Navigation Menu

Skip to content

Instantly share code, notes, and snippets.

View szagoruyko's full-sized avatar

Sergey Zagoruyko szagoruyko

View GitHub Profile
require 'optim'
require 'image'
require 'xlua'
require 'cudnn'
local json = require 'cjson'
local tnt = require 'torchnet'
local utils = require 'models.utils'
-- local tds = require 'tds'
local iterm = require 'iterm'
from pathlib import Path
from tqdm import tqdm
import subprocess as sp
import multiprocessing as mp
def convert(nef):
jpg = nef.with_suffix('.JPG')
n = str(nef)
command0 = f'sips -s format jpeg {nef} --out {jpg}'
  • BiasAdd function (with CUDNN and not)
  • PTX execution in pytorch (cutorch-rtc equivalent)
  • cublas<C>dgmm wrappers for torch and cutorch
  • zeros_like, new_like, ones_like
  • docs for torch.nn.functional
  • F.pad: constant, reflect, replicate
  • gradcheck
  • model.train(False)
json_stats: {"cudnn":"fastest","LR":0.1,"nClasses":0,"batchSize":256,"trainTop1":94.67290368859,"netType":"wide-resnet","resetClassifier":false,"optimState":"none","gen":"gen","nGPU":4,"optnet":false,"dataset":"imagenet","manualSeed":0,"resume":"none","trainTop5":85.619985528819,"weightDecay":0.0001,"testTop5":66.992,"nThreads":8,"testTop1":85.918,"save":"logs\/resnet50_2_3249617253","shortcutType":"B","epoch":1,"depth":50,"retrain":"none","shareGradInput":true,"epochNumber":1,"tenCrop":false,"testOnly":false,"bottleneck":2,"nEpochs":100,"momentum":0.9,"trainLoss":5.7109265497228,"backend":"cudnn","data":"\/media\/SuperSSD\/ILSVRC2012","width":2}
json_stats: {"cudnn":"fastest","LR":0.1,"nClasses":0,"batchSize":256,"trainTop1":76.088909564483,"netType":"wide-resnet","resetClassifier":false,"optimState":"none","gen":"gen","nGPU":4,"optnet":false,"dataset":"imagenet","manualSeed":0,"resume":"none","trainTop5":52.913632648983,"weightDecay":0.0001,"testTop5":40.876,"nThreads":8,"testTop1":67.222,"save":"logs\/resn
json_stats: {"cudnn":"fastest","LR":0.1,"nClasses":0,"batchSize":256,"data":"\/home\/zagoruys\/ILSVRC2012_256","netType":"wrn","resetClassifier":false,"optimState":"none","gen":"gen","nGPU":2,"dataset":"imagenet","momentum":0.9,"resume":"none","trainTop5":72.685875640967,"weightDecay":0.0001,"testTop5":52.24609375,"nThreads":8,"testTop1":76.534598214286,"save_folder":"logs\/resnet18","shortcutType":"B","epoch":1,"depth":18,"retrain":"none","epochNumber":1,"tenCrop":false,"trainTop1":88.313161379704,"manualSeed":0,"nEpochs":90,"width":1,"trainLoss":4.8664443903512,"backend":"cudnn","testOnly":false,"shareGradInput":true}
json_stats: {"cudnn":"fastest","LR":0.1,"nClasses":0,"batchSize":256,"data":"\/home\/zagoruys\/ILSVRC2012_256","netType":"wrn","resetClassifier":false,"optimState":"none","gen":"gen","nGPU":2,"dataset":"imagenet","momentum":0.9,"resume":"none","trainTop5":48.085244628623,"weightDecay":0.0001,"testTop5":37.587292729592,"nThreads":8,"testTop1":64.885204081633,"save_folder":"logs\/resnet18","shor
commit 3948543212d3d8286a687ef7783783bae720f65f
Author: Sergey Zagoruyko <zagoruyko2@gmail.com>
Date: Mon Nov 21 18:01:56 2016 +0100
do gc only on val
diff --git a/dataloader.lua b/dataloader.lua
index a995bff..b69482a 100644
--- a/dataloader.lua
+++ b/dataloader.lua
diff --git a/main.lua b/main.lua
index 5e827c0..6305a20 100644
--- a/main.lua
+++ b/main.lua
@@ -10,6 +10,7 @@ require 'torch'
require 'paths'
require 'optim'
require 'nn'
+local json = require 'cjson'
local DataLoader = require 'dataloader'
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.357
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.534
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.393
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.156
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.528
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.318
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.492
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.512
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.282
require 'xlua'
require 'sys'
local matio = require 'matio'
local data = {}
local labels = {}
local train_data = matio.load'./cifar-100-matlab/train.mat'
local test_data = matio.load'./cifar-100-matlab/test.mat'
require 'xlua'
require 'sys'
local batches_folder = '/opt/rocks/cifar.torch/cifar-10-batches-t7'
local data = {}
local labels = {}
for i=1,5 do
local name = paths.concat(batches_folder, 'data_batch_'..i..'.t7')